%*Hashing with Graphs %@Wei Liu, Jun Wang, Sanjiv Kumar, Shih-Fu Chang %t2011 %cICML %f/ICML/ICML-2011-0.pdf %*Efficient Sparse Modeling with Automatic Feature Grouping %@Wenliang Zhong, James Kwok %t2011 %cICML %f/ICML/ICML-2011-1.pdf %*Multi-Label Classification on Tree- and DAG-Structured Hierarchies %@Wei Bi, James Kwok %t2011 %cICML %f/ICML/ICML-2011-2.pdf %*A Graph-based Framework for Multi-Task Multi-View Learning %@Jingrui He, Rick Lawrence %t2011 %cICML %f/ICML/ICML-2011-3.pdf %*GoDec: Randomized Low-rank & Sparse Matrix Decomposition in Noisy Case %@Tianyi Zhou, Dacheng Tao, University of Technology %t2011 %cICML %f/ICML/ICML-2011-4.pdf %*Unimodal Bandits %@Jia Yuan Yu, Shie Mannor %t2011 %cICML %f/ICML/ICML-2011-5.pdf %*Learning Output Kernels with Block Coordinate Descent %@Francesco Dinuzzo, Cheng Soon Ong, Peter Gehler, Gianluigi Pillonetto %t2011 %cICML %f/ICML/ICML-2011-6.pdf %*Vector-valued Manifold Regularization %@Ha Quang Minh, Vikas Sindhwani %t2011 %cICML %f/ICML/ICML-2011-7.pdf %*On Information-Maximization Clustering: Tuning Parameter Selection and Analytic Solution %@Masashi Sugiyama, Makoto Yamada, Manabu Kimura, Hirotaka Hachiya %t2011 %cICML %f/ICML/ICML-2011-8.pdf %*On tracking portfolios with certainty equivalents on a generalization of Markowitz model: the Fool, the Wise and the Adaptive %@Richard Nock, Brice Magdalou, Eric Briys, Frank Nielsen %t2011 %cICML %f/ICML/ICML-2011-9.pdf %*Multiple Instance Learning with Manifold Bags %@Boris Babenko, Nakul Verma, Piotr Dollar, Serge Belongie %t2011 %cICML %f/ICML/ICML-2011-10.pdf %*Eigenvalue Sensitive Feature Selection %@Yi Jiang, Jiangtao Ren %t2011 %cICML %f/ICML/ICML-2011-11.pdf %*Large Scale Text Classification using Semi-supervised Multinomial Naive Bayes %@Jiang Su, Jelber Sayyad Shirab, Stan Matwin %t2011 %cICML %f/ICML/ICML-2011-12.pdf %*Enhanced Gradient and Adaptive Learning Rate for Training Restricted Boltzmann Machines %@KyungHyun Cho, Tapani Raiko, Alexander Ilin %t2011 %cICML %f/ICML/ICML-2011-13.pdf %*Dynamic Tree Block Coordinate Ascent %@Daniel Tarlow, Dhruv Batra, Pushmeet Kohli, Vladimir Kolmogorov %t2011 %cICML %f/ICML/ICML-2011-14.pdf %*Implementing regularization implicitly via approximate eigenvector computation %@Michael Mahoney, Lorenzo Orecchia %t2011 %cICML %f/ICML/ICML-2011-15.pdf %*Parsing Natural Scenes and Natural Language with Recursive Neural Networks %@Richard Socher, Cliff Chiung-Yu Lin, Andrew Ng, Chris Manning %t2011 %cICML %f/ICML/ICML-2011-16.pdf %*Conjugate Markov Decision Processes %@Philip Thomas, Andrew Barto %t2011 %cICML %f/ICML/ICML-2011-17.pdf %*Learning Mallows Models with Pairwise Preferences %@Tyler Lu, Craig Boutilier %t2011 %cICML %f/ICML/ICML-2011-18.pdf %*Surrogate losses and regret bounds for cost-sensitive classification with example-dependent costs %@Clayton Scott %t2011 %cICML %f/ICML/ICML-2011-19.pdf %*Efficient Rule Ensemble Learning using Hierarchical Kernels %@Pratik Jawanpuria, Saketha Nath Jagarlapudi, Ganesh Ramakrishnan %t2011 %cICML %f/ICML/ICML-2011-20.pdf %*An Augmented Lagrangian Approach to Constrained MAP Inference %@Andre Martins, Mario Figueiredo, pedro Aguiar, Noah Smith, Eric Xing %t2011 %cICML %f/ICML/ICML-2011-21.pdf %*Mean-Variance Optimization in Markov Decision Processes %@Shie Mannor, John Tsitsiklis %t2011 %cICML %f/ICML/ICML-2011-22.pdf %*Time Series Clustering: Complex is Simpler! %@Lei Li, B. Aditya Prakash %t2011 %cICML %f/ICML/ICML-2011-23.pdf %*Max-margin Learning for Lower Linear Envelope Potentials in Binary Markov Random Fields %@Stephen Gould %t2011 %cICML %f/ICML/ICML-2011-24.pdf %*Inference of Inversion Transduction Grammars %@Alexander Clark %t2011 %cICML %f/ICML/ICML-2011-25.pdf %*BCDNPKL: Scalable Non-Parametric Kernel Learning Using Block Coordinate Descent %@En-Liang Hu, Bo Wang, SongCan Chen %t2011 %cICML %f/ICML/ICML-2011-26.pdf %*Learning Discriminative Fisher Kernels %@Laurens Van der Maaten %t2011 %cICML %f/ICML/ICML-2011-27.pdf %*Pruning nearest neighbor cluster trees %@Samory Kpotufe, Ulrike von Luxburg %t2011 %cICML %f/ICML/ICML-2011-28.pdf %*Online AUC Maximization %@Peilin Zhao, Steven Hoi, Rong Jin, Tianbao Yang %t2011 %cICML %f/ICML/ICML-2011-29.pdf %*Beat the Mean Bandit %@Yisong Yue, Thorsten Joachims %t2011 %cICML %f/ICML/ICML-2011-30.pdf %*Ultra-Fast Optimization Algorithm for Sparse Multi Kernel Learning %@Francesco Orabona, Luo Jie %t2011 %cICML %f/ICML/ICML-2011-31.pdf %*Estimating the Bayes Point Using Linear Knapsack Problems %@Brian Potetz %t2011 %cICML %f/ICML/ICML-2011-32.pdf %*On optimization methods for deep learning %@Quoc Le, Jiquan Ngiam, Adam Coates, Abhik Lahiri, Bobby Prochnow, Andrew Ng %t2011 %cICML %f/ICML/ICML-2011-33.pdf %*Multiclass Classification with Bandit Feedback using Adaptive Regularization %@Koby Crammer, Claudio Gentile %t2011 %cICML %f/ICML/ICML-2011-34.pdf %*On the Necessity of Irrelevant Variables %@Dave Helmbold, Phil Long %t2011 %cICML %f/ICML/ICML-2011-35.pdf %*ABC-EP: Expectation Propagation for Likelihood-free Bayesian Computation %@Simon Barthelmé, Nicolas Chopin %t2011 %cICML %f/ICML/ICML-2011-36.pdf %*A PAC-Bayes Sample-compression Approach to Kernel Methods %@Pascal Germain, Alexandre Lacoste, Francois Laviolette, Mario Marchand, Sara Shanian %t2011 %cICML %f/ICML/ICML-2011-37.pdf %*Integrating Partial Model Knowledge in Model Free RL Algorithms %@Aviv Tamar, Dotan Di Castro, Ron Meir %t2011 %cICML %f/ICML/ICML-2011-38.pdf %*Fast Newton-type Methods for Total Variation Regularization %@Álvaro Barbero, Suvrit Sra %t2011 %cICML %f/ICML/ICML-2011-39.pdf %*Parallel Coordinate Descent for L1-Regularized Loss Minimization %@Joseph Bradley, Aapo Kyrola, Daniel Bickson, Carlos Guestrin %t2011 %cICML %f/ICML/ICML-2011-40.pdf %*Large-Scale Convex Minimization with a Low-Rank Constraint %@Shai Shalev-Shwartz, Alon Gonen, Ohad Shamir %t2011 %cICML %f/ICML/ICML-2011-41.pdf %*Approximate Dynamic Programming for Storage Problems %@Lauren Hannah, David Dunson %t2011 %cICML %f/ICML/ICML-2011-42.pdf %*Online Submodular Minimization for Combinatorial Structures %@Stefanie Jegelka, Jeff Bilmes %t2011 %cICML %f/ICML/ICML-2011-43.pdf %*Minimal Loss Hashing for Compact Binary Codes %@Mohammad Norouzi, David Fleet %t2011 %cICML %f/ICML/ICML-2011-44.pdf %*The Hierarchical Beta Process for Convolutional Factor Analysis and Deep Learning %@Bo Chen, Gungor Polatkan, Guillermo Sapiro, David Dunson, Lawrence Carin %t2011 %cICML %f/ICML/ICML-2011-45.pdf %*Simultaneous Learning and Covering with Adversarial Noise %@Andrew Guillory, Jeff Bilmes %t2011 %cICML %f/ICML/ICML-2011-46.pdf %*Topic Modeling with Nonparametric Markov Tree %@Haojun Chen, David Dunson, Lawrence Carin %t2011 %cICML %f/ICML/ICML-2011-47.pdf %*Relational Active Learning for Joint Collective Classification Models %@Ankit Kuwadekar, Jennifer Neville %t2011 %cICML %f/ICML/ICML-2011-48.pdf %*A Co-training Approach for Multi-view Spectral Clustering %@Abhishek Kumar, Hal Daume III, University of Maryland %t2011 %cICML %f/ICML/ICML-2011-49.pdf %*Learning from Multiple Outlooks %@Maayan Harel, Shie Mannor %t2011 %cICML %f/ICML/ICML-2011-50.pdf %*Adaptive Kernel Approximation for Large-Scale Non-Linear SVM Prediction %@Michele Cossalter, Rong Yan, Lu Zheng %t2011 %cICML %f/ICML/ICML-2011-51.pdf %*Risk-Based Generalizations of f-divergences %@Darío García-García, Ulrike von Luxburg, Raúl Santos-Rodríguez %t2011 %cICML %f/ICML/ICML-2011-52.pdf %*Learning Multi-View Neighborhood Preserving Projections %@Novi Quadrianto, Christoph Lampert %t2011 %cICML %f/ICML/ICML-2011-53.pdf %*Better Algorithms for Selective Sampling %@Francesco Orabona, Nicolò Cesa-Bianchi %t2011 %cICML %f/ICML/ICML-2011-54.pdf %*Minimax Learning Rates for Bipartite Ranking and Plug-in Rules %@Sylvain Robbiano, Stéphan Clémençon %t2011 %cICML %f/ICML/ICML-2011-55.pdf %*Task Space Retrieval Using Inverse Feedback Control %@Nikolay Jetchev, Marc Toussaint %t2011 %cICML %f/ICML/ICML-2011-56.pdf %*Bayesian CCA via Group Sparsity %@Seppo Virtanen, Arto Klami, Samuel Kaski %t2011 %cICML %f/ICML/ICML-2011-57.pdf %*PILCO: A Model-Based and Data-Efficient Approach to Policy Search %@Marc Deisenroth, Carl Rasmussen %t2011 %cICML %f/ICML/ICML-2011-58.pdf %*Suboptimal Solution Path Algorithm for Support Vector Machine %@Masayuki Karasuyama, Ichiro Takeuchi %t2011 %cICML %f/ICML/ICML-2011-59.pdf %*Incremental Basis Construction from Temporal Difference Error %@Yi Sun, Faustino Gomez, Mark Ring, Jürgen Schmidhuber %t2011 %cICML %f/ICML/ICML-2011-60.pdf %*Predicting Legislative Roll Calls from Text %@Sean Gerrish, David Blei %t2011 %cICML %f/ICML/ICML-2011-61.pdf %*On Bayesian PCA: Automatic Dimensionality Selection and Analytic Solution %@Shinichi Nakajima, Masashi Sugiyama, Derin Babacan %t2011 %cICML %f/ICML/ICML-2011-62.pdf %*Learning Linear Functions with Quadratic and Linear Multiplicative Updates %@Tom Bylander %t2011 %cICML %f/ICML/ICML-2011-63.pdf %*Domain Adaptation for Large-Scale Sentiment Classification: A Deep Learning Approach %@Xavier Glorot, Antoine Bordes, Yoshua Bengio %t2011 %cICML %f/ICML/ICML-2011-64.pdf %*Learning with Whom to Share in Multi-task Feature Learning %@Zhuoliang Kang, Kristen Grauman, Fei Sha %t2011 %cICML %f/ICML/ICML-2011-65.pdf %*Boosting on a Budget: Sampling for Feature-Efficient Prediction %@Lev Reyzin %t2011 %cICML %f/ICML/ICML-2011-66.pdf %*Speeding-Up Hoeffding-Based Regression Trees With Options %@Elena Ikonomovska, João Gama, Bernard Zenko, Saso Dzeroski %t2011 %cICML %f/ICML/ICML-2011-67.pdf %*Linear Regression under Fixed-Rank Constraints: A Riemannian Approach %@Gilles Meyer, Silvère Bonnabel, Rodolphe Sepulchre, University of Liège %t2011 %cICML %f/ICML/ICML-2011-68.pdf %*Cauchy Graph Embedding %@Dijun Luo, Chris Ding, Feiping Nie, Heng Huang %t2011 %cICML %f/ICML/ICML-2011-69.pdf %*Uncovering the Temporal Dynamics of Diffusion Networks %@Manuel Gomez Rodriguez, David Balduzzi, Bernhard Schölkopf %t2011 %cICML %f/ICML/ICML-2011-70.pdf %*Multiclass Boosting with Hinge Loss based on Output Coding %@Tianshi Gao, Daphne Koller %t2011 %cICML %f/ICML/ICML-2011-71.pdf %*Approximation Bounds for Inference using Cooperative Cuts %@Stefanie Jegelka, Jeff Bilmes %t2011 %cICML %f/ICML/ICML-2011-72.pdf %*Brier Curves: a New Cost-Based Visualisation of Classifier Performance %@Jose Hernandez-Orallo, Peter Flach, Cèsar Ferri %t2011 %cICML %f/ICML/ICML-2011-73.pdf %*Semi-supervised Penalized Output Kernel Regression for Link Prediction %@Céline Brouard, Florence D'Alche-Buc, Marie Szafranski %t2011 %cICML %f/ICML/ICML-2011-74.pdf %*A New Bayesian Rating System for Team Competitions %@Sergey Nikolenko, Alexander Sirotkin %t2011 %cICML %f/ICML/ICML-2011-75.pdf %*OptiML: An Implicitly Parallel Domain-Specific Language for Machine Learning %@Arvind Sujeeth, HyoukJoong Lee, Kevin Brown, Tiark Rompf, Hassan Chafi, Michael Wu, Anand Atreya, Martin Odersky, Kunle Olukotun %t2011 %cICML %f/ICML/ICML-2011-76.pdf %*Infinite SVM: a Dirichlet Process Mixture of Large-margin Kernel Machines %@Jun Zhu, Ning Chen, Eric Xing %t2011 %cICML %f/ICML/ICML-2011-77.pdf %*On the Integration of Topic Modeling and Dictionary Learning %@Lingbo Li, Mingyuan Zhou, Guillermo Sapiro, Lawrence Carin %t2011 %cICML %f/ICML/ICML-2011-78.pdf %*Piecewise Bounds for Estimating Bernoulli-Logistic Latent Gaussian Models %@Benjamin Marlin, Mohammad Khan, Kevin Murphy %t2011 %cICML %f/ICML/ICML-2011-79.pdf %*Access to Unlabeled Data can Speed up Prediction Time %@Ruth Urner, Shai Shalev-Shwartz, Shai Ben-David %t2011 %cICML %f/ICML/ICML-2011-80.pdf %*From PAC-Bayes Bounds to Quadratic Programs for Majority Votes %@Jean-Francis Roy, Francois Laviolette, Mario Marchand %t2011 %cICML %f/ICML/ICML-2011-81.pdf %*A Coherent Interpretation of AUC as a Measure of Aggregated Classification Performance %@Peter Flach, Jose Hernandez-Orallo, Cèsar Ferri %t2011 %cICML %f/ICML/ICML-2011-82.pdf %*Support Vector Machines as Probabilistic Models %@Vojtech Franc, Alexander Zien, Bernhard Schölkopf %t2011 %cICML %f/ICML/ICML-2011-83.pdf %*Adaptively Learning the Crowd Kernel %@Omer Tamuz, Ce Liu, Serge Belongie, Ohad Shamir, Adam Kalai %t2011 %cICML %f/ICML/ICML-2011-84.pdf %*Bayesian Learning via Stochastic Gradient Langevin Dynamics %@Max Welling, Yee Whye Teh %t2011 %cICML %f/ICML/ICML-2011-85.pdf %*Multimodal Deep Learning %@Jiquan Ngiam, Aditya Khosla, Mingyu Kim, Juhan Nam, Honglak Lee, Andrew Ng %t2011 %cICML %f/ICML/ICML-2011-86.pdf %*On the Robustness of Kernel Density M-Estimators %@JooSeuk Kim, Clayton Scott %t2011 %cICML %f/ICML/ICML-2011-87.pdf %*Beam Search based MAP Estimates for the Indian Buffet Process %@Piyush Rai, Hal Daume III, University of Maryland %t2011 %cICML %f/ICML/ICML-2011-88.pdf %*Optimal Distributed Online Prediction %@Ofer Dekel, Ran Gilad-Bachrach, Ohad Shamir, Lin Xiao %t2011 %cICML %f/ICML/ICML-2011-89.pdf %*Message Passing Algorithms for the Dirichlet Diffusion Tree %@David Knowles, Jurgen Van Gael, Zoubin Ghahramani %t2011 %cICML %f/ICML/ICML-2011-90.pdf %*Convex Max-Product over Compact Sets for Protein Folding %@Jian Peng, Tamir Hazan, David McAllester, Raquel Urtasun %t2011 %cICML %f/ICML/ICML-2011-91.pdf %*Structure Learning in Ergodic Factored MDPs without Knowledge of the Transition Function's In-Degree %@Doran Chakraborty, Peter Stone %t2011 %cICML %f/ICML/ICML-2011-92.pdf %*Clusterpath: an Algorithm for Clustering using Convex Fusion Penalties %@Toby Hocking, Jean-Philippe Vert, Francis Bach, Armand Joulin %t2011 %cICML %f/ICML/ICML-2011-93.pdf %*Tree preserving embedding %@Albert Shieh, Tatsunori Hashimoto, Edo Airoldi %t2011 %cICML %f/ICML/ICML-2011-94.pdf %*Clustering by Left-Stochastic Matrix Factorization %@Raman Arora, Maya Gupta, Amol Kapila, Maryam Fazel %t2011 %cICML %f/ICML/ICML-2011-95.pdf %*The Infinite Regionalized Policy Representation %@Miao Liu, Xuejun Liao, Lawrence Carin %t2011 %cICML %f/ICML/ICML-2011-96.pdf %*SampleRank: Training Factor Graphs with Atomic Gradients %@Michael Wick, Khashayar Rohanimanesh, Kedar Bellare, Aron Culotta, Andrew McCallum %t2011 %cICML %f/ICML/ICML-2011-97.pdf %*Tree-Structured Infinite Sparse Factor Model %@XianXing Zhang, David Dunson, Lawrence Carin %t2011 %cICML %f/ICML/ICML-2011-98.pdf %*Preserving Personalized Pagerank in Subgraphs %@Andrea Vattani, Deepayan Chakrabarti, Maxim Gurevich %t2011 %cICML %f/ICML/ICML-2011-99.pdf %*Hierarchical Classification via Orthogonal Transfer %@Lin Xiao, Dengyong Zhou, Mingrui Wu %t2011 %cICML %f/ICML/ICML-2011-100.pdf %*A Three-Way Model for Collective Learning on Multi-Relational Data %@Maximilian Nickel, Volker Tresp, Hans-Peter Kriegel %t2011 %cICML %f/ICML/ICML-2011-101.pdf %*Variational Inference for Policy Search in changing situations %@Gerhard Neumann %t2011 %cICML %f/ICML/ICML-2011-102.pdf %*Learning Scoring Functions with Order-Preserving Losses and Standardized Supervision %@David Buffoni, Clément Calauzenes, Patrick Gallinari, Nicolas Usunier %t2011 %cICML %f/ICML/ICML-2011-103.pdf %*Contractive Auto-Encoders: Explicit Invariance During Feature Extraction %@Salah RIFAI, Pascal Vincent, Xavier Muller, Xavier Glorot, Yoshua Bengio %t2011 %cICML %f/ICML/ICML-2011-104.pdf %*Variational Heteroscedastic Gaussian Process Regression %@Miguel Lazaro-Gredilla, Michalis Titsias %t2011 %cICML %f/ICML/ICML-2011-105.pdf %*Bounding the Partition Function using Holder's Inequality %@Qiang Liu, Alexander Ihler, University of California %t2011 %cICML %f/ICML/ICML-2011-106.pdf %*Dynamic Egocentric Models for Citation Networks %@Duy Vu, Arthur Asuncion, David Hunter, Padhraic Smyth %t2011 %cICML %f/ICML/ICML-2011-107.pdf %*The Constrained Weight Space SVM: Learning with Ranked Features %@Kevin Small, Byron Wallace, Carla Brodley, Thomas Trikalinos %t2011 %cICML %f/ICML/ICML-2011-108.pdf %*Robust Matrix Completion and Corrupted Columns %@Yudong Chen, Huan Xu, Constantine Caramanis, Sujay Sanghavi, Dept. of Electrical and Computer Engineering %t2011 %cICML %f/ICML/ICML-2011-109.pdf %*Online Discovery of Feature Dependencies %@Alborz Geramifard, Finale Doshi, Joshua Redding, Nicholas Roy, Jonathan How %t2011 %cICML %f/ICML/ICML-2011-110.pdf %*Variational Inference for Stick-Breaking Beta Process Priors %@John Paisley, Lawrence Carin, David Blei %t2011 %cICML %f/ICML/ICML-2011-111.pdf %*Apprenticeship Learning About Multiple Intentions %@Monica Babes, Vukosi Marivate, Michael Littman, Kaushik Subramanian %t2011 %cICML %f/ICML/ICML-2011-112.pdf %*Minimum Probability Flow Learning %@Jascha Sohl-Dickstein, Peter Battaglino, Michael DeWeese %t2011 %cICML %f/ICML/ICML-2011-113.pdf %*Infinite Dynamic Bayesian Networks %@Finale Doshi, David Wingate, Josh Tenenbaum, Nicholas Roy %t2011 %cICML %f/ICML/ICML-2011-114.pdf %*The Importance of Encoding Versus Training with Sparse Coding and Vector Quantization %@Adam Coates, Andrew Ng %t2011 %cICML %f/ICML/ICML-2011-115.pdf %*Fast Global Alignment Kernels %@Marco Cuturi %t2011 %cICML %f/ICML/ICML-2011-116.pdf %*Learning attentional policies for tracking and recognition in video with deep networks %@Loris Bazzani, Nando Freitas, Hugo Larochelle, Vittorio Murino, Jo-Anne Ting %t2011 %cICML %f/ICML/ICML-2011-117.pdf %*Large-Scale Learning of Embeddings with Reconstruction Sampling %@Yann Dauphin, Xavier Glorot, Yoshua Bengio %t2011 %cICML %f/ICML/ICML-2011-118.pdf %*Automatic Feature Decomposition for Single View Co-training %@Minmin Chen, Kilian Weinberger, Yixin Chen %t2011 %cICML %f/ICML/ICML-2011-119.pdf %*Mapping kernels for trees %@Kilho Shin, Marco Cuturi, Tetsuji Kuboyama %t2011 %cICML %f/ICML/ICML-2011-120.pdf %*Stochastic Low-Rank Kernel Learning for Regression %@Pierre Machart, Thomas Peel, Sandrine Anthoine, Liva Ralaivola, Hervé Glotin %t2011 %cICML %f/ICML/ICML-2011-121.pdf %*Size-constrained Submodular Minimization through Minimum Norm Base %@Kiyohito Nagano, Yoshinobu Kawahara, Kazuyuki Aihara %t2011 %cICML %f/ICML/ICML-2011-122.pdf %*Locally Linear Support Vector Machines %@Lubor Ladicky, Philip Torr %t2011 %cICML %f/ICML/ICML-2011-123.pdf %*Functional Regularized Least Squares Classi cation with Operator-valued Kernels %@Hachem Kadri, Asma Rabaoui, philippe Preux, Emmanuel Duflos, Alain Rakotomamonjy %t2011 %cICML %f/ICML/ICML-2011-124.pdf %*Clustering Partially Observed Graphs via Convex Optimization %@Ali Jalali, Yudong Chen, Sujay Sanghavi, Huan Xu %t2011 %cICML %f/ICML/ICML-2011-125.pdf %*On the Use of Variational Inference for Learning Discrete Graphical Models %@Eunho Yang, Pradeep Ravikumar %t2011 %cICML %f/ICML/ICML-2011-126.pdf %*Generating Text with Recurrent Neural Networks %@Ilya Sutskever, James Martens, Geoffrey Hinton %t2011 %cICML %f/ICML/ICML-2011-127.pdf %*Probabilistic Matrix Addition %@Amrudin Agovic, Arindam Banerjee, Snigdhansu Chatterje %t2011 %cICML %f/ICML/ICML-2011-128.pdf %*Learning Recurrent Neural Networks with Hessian-Free Optimization %@James Martens, Ilya Sutskever %t2011 %cICML %f/ICML/ICML-2011-129.pdf %*Sparse Additive Generative Models of Text %@Jacob Eisenstein, Amr Ahmed, Eric Xing %t2011 %cICML %f/ICML/ICML-2011-130.pdf %*Classification-based Policy Iteration with a Critic %@Victor Gabillon, Alessandro Lazaric, Mohammad Ghavamzadeh, Bruno Scherrer %t2011 %cICML %f/ICML/ICML-2011-131.pdf %*Submodular meets Spectral: Greedy Algorithms for Subset Selection, Sparse Approximation and Dictionary Selection %@Abhimanyu Das, David Kempe %t2011 %cICML %f/ICML/ICML-2011-132.pdf %*A Spectral Algorithm for Latent Tree Graphical Models %@Ankur Parikh, Le Song, Eric Xing %t2011 %cICML %f/ICML/ICML-2011-133.pdf %*A Unified Probabilistic Model for Global and Local Unsupervised Feature Selection %@Yue Guan, Jennifer Dy, Michael Jordan %t2011 %cICML %f/ICML/ICML-2011-134.pdf %*Towards Making Unlabeled Data Never Hurt %@Yu-Feng Li, Zhi-Hua Zhou %t2011 %cICML %f/ICML/ICML-2011-135.pdf %*On Random Weights and Unsupervised Feature Learning %@Andrew Saxe, pang Wei Koh, Zhenghao Chen, Maneesh Bhand, Bipin Suresh, Andrew Ng %t2011 %cICML %f/ICML/ICML-2011-136.pdf %*Doubly Robust Policy Evaluation and Learning %@Miroslav Dudik, John Langford, Lihong Li %t2011 %cICML %f/ICML/ICML-2011-137.pdf %*Learning Deep Energy Models %@Jiquan Ngiam, Zhenghao Chen, pang Wei Koh, Andrew Ng %t2011 %cICML %f/ICML/ICML-2011-138.pdf %*Bipartite Ranking through Minimization of Univariate Loss %@Wojciech Kotlowski, Krzysztof Dembczynski, Eyke Huellermeier %t2011 %cICML %f/ICML/ICML-2011-139.pdf %*Manifold Identification of Dual Averaging Methods for Regularized Stochastic Online Learning %@Sangkyun Lee, Stephen Wright %t2011 %cICML %f/ICML/ICML-2011-140.pdf %*Noisy matrix decomposition via convex relaxation: Optimal rates in high dimensions %@Alekh Agarwal, Sahand Negahban, Martin Wainwright %t2011 %cICML %f/ICML/ICML-2011-141.pdf %*Bundle Selling by Online Estimation of Valuation Functions %@Daniel Vainsencher, Ofer Dekel, Shie Mannor %t2011 %cICML %f/ICML/ICML-2011-142.pdf %*Unsupervised Models of Images by Spike-and-Slab RBMs %@Aarron Courville, James Bergstra, Yoshua Bengio %t2011 %cICML %f/ICML/ICML-2011-143.pdf %*Approximating Correlated Equilibria using Relaxations on the Marginal Polytope %@Hetunandan Kamisetty, Eric Xing, Christopher Langmead %t2011 %cICML %f/ICML/ICML-2011-144.pdf %*Active Learning from Crowds %@Yan Yan, Romer Rosales, Glenn Fung, Jennifer Dy %t2011 %cICML %f/ICML/ICML-2011-145.pdf %*Computational Rationalization: The Inverse Equilibrium Problem %@Kevin Waugh, Brian Ziebart, Drew Bagnell %t2011 %cICML %f/ICML/ICML-2011-146.pdf %*Finite-Sample Analysis of Lasso-TD %@Mohammad Ghavamzadeh, Alessandro Lazaric, Remi Munos, Matthew Hoffman %t2011 %cICML %f/ICML/ICML-2011-147.pdf %*Generalized Value Functions for Large Action Sets %@Jason Pazis, Ron Parr %t2011 %cICML %f/ICML/ICML-2011-148.pdf %*k-DPPs: Fixed-Size Determinantal Point Processes %@Alex Kulesza, Ben Taskar %t2011 %cICML %f/ICML/ICML-2011-149.pdf %*On Autoencoders and Score Matching for Energy Based Models %@Kevin Swersky, Marc'Aurelio Ranzato, David Buchman, Benjamin Marlin, Nando Freitas %t2011 %cICML %f/ICML/ICML-2011-150.pdf %*Generalized Boosting Algorithms for Convex Optimization %@Alexander Grubb, Drew Bagnell %t2011 %cICML %f/ICML/ICML-2011-151.pdf %*Debt Collections Using Constrained Reinforcement Learning %@Naoki Abe, Prem Melville, Cezar Pendus, David L. Jensen, Chandan K. Reddy, Vince P. Thomas, James J. Bennett, Gary F. Anderson, Brent R. Cooley, Melissa Weatherwax, Timothy Gardinier, Gerard Miller %t2011 %cICML %f/ICML/ICML-2011-152.pdf %*Classifying Actions and Measuring Action Similarity by Modeling the Mutual Context of Objects and Human Poses %@Bangpeng Yao, Aditya Khosla, Li Fei-Fei %t2011 %cICML %f/ICML/ICML-2011-153.pdf %*Efficient Planning under Uncertainty for a Target-Tracking Micro-Aerial Vehicle in Urban Environments %@Abraham Bachrach, Ruijie He, Nicholas Roy %t2011 %cICML %f/ICML/ICML-2011-154.pdf %*Gesture-Based Human-Robot Jazz Improvisation %@Gil Weinberg %t2011 %cICML %f/ICML/ICML-2011-155.pdf %*High resolution models of transcription factor-DNA affinities improve in vitro and in vivo binding predictions %@Christina Leslie %t2011 %cICML %f/ICML/ICML-2011-156.pdf %*Suggesting Friends Using the Implicit Social Graph %@Maayan Roth, Tzvika Barenholz, Assaf Ben-David, David Deutscher, Guy Flysher, Avinatan Hassidim, Ilan Horn, Ari Leichtberg, Naty Leiser, Yossi Matias, Ron Merom %t2011 %cICML %f/ICML/ICML-2011-157.pdf %*Relevance and ranking in online dating systems %@Fernando Diaz, Donald Metzler, Sihem Amer-Yahia %t2011 %cICML %f/ICML/ICML-2011-158.pdf %*We Just Clicked - Conversational Features of Social Bonding in Speed Dates %@Rajesh Ranganath, Dan Jurafsky, Dan McFarland %t2011 %cICML %f/ICML/ICML-2011-159.pdf %*No Oops, You Won’t Do It Again: Mechanisms for Self-correction in Crowdsourcing %@Nihar Shah, Dengyong Zhou %t2012 %cICML %f/ICML/ICML-2012-160.pdf %*No Oops, You Won’t Do It Again: Mechanisms for Self-correction in Crowdsourcing %@Nihar Shah, Dengyong Zhou %t2012 %cICML %f/ICML/ICML-2012-161.pdf %*Stochastically Transitive Models for Pairwise Comparisons: Statistical and Computational Issues %@Nihar Shah, Sivaraman Balakrishnan, Aditya Guntuboyina, Martin Wainwright %t2012 %cICML %f/ICML/ICML-2012-162.pdf %*Stochastically Transitive Models for Pairwise Comparisons: Statistical and Computational Issues %@Nihar Shah, Sivaraman Balakrishnan, Aditya Guntuboyina, Martin Wainwright %t2012 %cICML %f/ICML/ICML-2012-163.pdf %*Uprooting and Rerooting Graphical Models %@Adrian Weller %t2012 %cICML %f/ICML/ICML-2012-164.pdf %*Uprooting and Rerooting Graphical Models %@Adrian Weller %t2012 %cICML %f/ICML/ICML-2012-165.pdf %*A Deep Learning Approach to Unsupervised Ensemble Learning %@Uri Shaham, Xiuyuan Cheng, Omer Dror, Ariel Jaffe, Boaz Nadler, Joseph Chang, Yuval Kluger %t2012 %cICML %f/ICML/ICML-2012-166.pdf %*A Deep Learning Approach to Unsupervised Ensemble Learning %@Uri Shaham, Xiuyuan Cheng, Omer Dror, Ariel Jaffe, Boaz Nadler, Joseph Chang, Yuval Kluger %t2012 %cICML %f/ICML/ICML-2012-167.pdf %*Revisiting Semi-Supervised Learning with Graph Embeddings %@Zhilin Yang, William Cohen, Ruslan Salakhudinov %t2012 %cICML %f/ICML/ICML-2012-168.pdf %*Guided Cost Learning: Deep Inverse Optimal Control via Policy Optimization %@Chelsea Finn, Sergey Levine, Pieter Abbeel %t2012 %cICML %f/ICML/ICML-2012-169.pdf %*Guided Cost Learning: Deep Inverse Optimal Control via Policy Optimization %@Chelsea Finn, Sergey Levine, Pieter Abbeel %t2012 %cICML %f/ICML/ICML-2012-170.pdf %*Diversity-Promoting Bayesian Learning of Latent Variable Models %@Pengtao Xie, Jun Zhu, Eric Xing %t2012 %cICML %f/ICML/ICML-2012-171.pdf %*Diversity-Promoting Bayesian Learning of Latent Variable Models %@Pengtao Xie, Jun Zhu, Eric Xing %t2012 %cICML %f/ICML/ICML-2012-172.pdf %*Additive Approximations in High Dimensional Nonparametric Regression via the SALSA %@Kirthevasan Kandasamy, Yaoliang Yu %t2012 %cICML %f/ICML/ICML-2012-173.pdf %*Hawkes Processes with Stochastic Excitations %@Young Lee, Kar Wai Lim, Cheng Soon Ong %t2012 %cICML %f/ICML/ICML-2012-174.pdf %*Hawkes Processes with Stochastic Excitations %@Young Lee, Kar Wai Lim, Cheng Soon Ong %t2012 %cICML %f/ICML/ICML-2012-175.pdf %*Data-driven Rank Breaking for Efficient Rank Aggregation %@Ashish Khetan, Sewoong Oh %t2012 %cICML %f/ICML/ICML-2012-176.pdf %*Dropout distillation %@Samuel Rota Bulò, Lorenzo Porzi, Peter Kontschieder %t2012 %cICML %f/ICML/ICML-2012-177.pdf %*Dropout distillation %@Samuel Rota Bulò, Lorenzo Porzi, Peter Kontschieder %t2012 %cICML %f/ICML/ICML-2012-178.pdf %*Metadata-conscious anonymous messaging %@Giulia Fanti, Peter Kairouz, Sewoong Oh, Kannan Ramchandran, Pramod Viswanath %t2012 %cICML %f/ICML/ICML-2012-179.pdf %*Metadata-conscious anonymous messaging %@Giulia Fanti, Peter Kairouz, Sewoong Oh, Kannan Ramchandran, Pramod Viswanath %t2012 %cICML %f/ICML/ICML-2012-180.pdf %*The Teaching Dimension of Linear Learners %@Ji Liu, Xiaojin Zhu, Hrag Ohannessian %t2012 %cICML %f/ICML/ICML-2012-181.pdf %*The Teaching Dimension of Linear Learners %@Ji Liu, Xiaojin Zhu, Hrag Ohannessian %t2012 %cICML %f/ICML/ICML-2012-182.pdf %*Truthful Univariate Estimators %@Ioannis Caragiannis, Ariel Procaccia, Nisarg Shah %t2012 %cICML %f/ICML/ICML-2012-183.pdf %*Truthful Univariate Estimators %@Ioannis Caragiannis, Ariel Procaccia, Nisarg Shah %t2012 %cICML %f/ICML/ICML-2012-184.pdf %*Why Regularized Auto-Encoders learn Sparse Representation? %@Devansh Arpit, Yingbo Zhou, Hung Ngo, Venu Govindaraju %t2012 %cICML %f/ICML/ICML-2012-185.pdf %*Why Regularized Auto-Encoders learn Sparse Representation? %@Devansh Arpit, Yingbo Zhou, Hung Ngo, Venu Govindaraju %t2012 %cICML %f/ICML/ICML-2012-186.pdf %*k-variates++: more pluses in the k-means++ %@Richard Nock, Raphael Canyasse, Roksana Boreli, Frank Nielsen %t2012 %cICML %f/ICML/ICML-2012-187.pdf %*k-variates++: more pluses in the k-means++ %@Richard Nock, Raphael Canyasse, Roksana Boreli, Frank Nielsen %t2012 %cICML %f/ICML/ICML-2012-188.pdf %*Multi-Player Bandits – a Musical Chairs Approach %@Jonathan Rosenski, Ohad Shamir, Liran Szlak %t2012 %cICML %f/ICML/ICML-2012-189.pdf %*Multi-Player Bandits – a Musical Chairs Approach %@Jonathan Rosenski, Ohad Shamir, Liran Szlak %t2012 %cICML %f/ICML/ICML-2012-190.pdf %*The Information Sieve %@Greg Ver Steeg, Aram Galstyan %t2012 %cICML %f/ICML/ICML-2012-191.pdf %*The Information Sieve %@Greg Ver Steeg, Aram Galstyan %t2012 %cICML %f/ICML/ICML-2012-192.pdf %*Deep Speech 2 : End-to-End Speech Recognition in English and Mandarin %@Dario Amodei, Rishita Anubhai, Eric Battenberg, Carl Case, Jared Casper, Bryan Catanzaro, JingDong Chen, Mike Chrzanowski, Adam Coates, Greg Diamos, Erich Elsen, Jesse Engel, Linxi Fan, Christopher Fougner, Awni Hannun, Billy Jun, Tony Han, Patrick LeGresley, Xiangang Li, Libby Lin, Sharan Narang, Andrew Ng, Sherjil Ozair, Ryan Prenger, Sheng Qian, Jonathan Raiman, Sanjeev Satheesh, David Seetapun, Shubho Sengupta, Chong Wang, Yi Wang, Zhiqian Wang, Bo Xiao, Yan Xie, Dani Yogatama, Jun Zhan, Zhenyao Zhu %t2012 %cICML %f/ICML/ICML-2012-193.pdf %*On the Consistency of Feature Selection With Lasso for Non-linear Targets %@Yue Zhang, Weihong Guo, Soumya Ray %t2012 %cICML %f/ICML/ICML-2012-194.pdf %*Minimum Regret Search for Single- and Multi-Task Optimization %@Jan Hendrik Metzen %t2012 %cICML %f/ICML/ICML-2012-195.pdf %*Minimum Regret Search for Single- and Multi-Task Optimization %@Jan Hendrik Metzen %t2012 %cICML %f/ICML/ICML-2012-196.pdf %*CryptoNets: Applying Neural Networks to Encrypted Data with High Throughput and Accuracy %@Ran Gilad-Bachrach, Nathan Dowlin, Kim Laine, Kristin Lauter, Michael Naehrig, John Wernsing %t2012 %cICML %f/ICML/ICML-2012-197.pdf %*The Variational Nystrom method for large-scale spectral problems %@Max Vladymyrov, Miguel Carreira-Perpinan %t2012 %cICML %f/ICML/ICML-2012-198.pdf %*The Variational Nystrom method for large-scale spectral problems %@Max Vladymyrov, Miguel Carreira-Perpinan %t2012 %cICML %f/ICML/ICML-2012-199.pdf %*Multi-Bias Non-linear Activation in Deep Neural Networks %@Hongyang Li, Wanli Ouyang, Xiaogang Wang %t2012 %cICML %f/ICML/ICML-2012-200.pdf %*Asymmetric Multi-task Learning Based on Task Relatedness and Loss %@Giwoong Lee, Eunho Yang, Sung ju Hwang %t2012 %cICML %f/ICML/ICML-2012-201.pdf %*Accurate Robust and Efficient Error Estimation for Decision Trees %@Lixin Fan %t2012 %cICML %f/ICML/ICML-2012-202.pdf %*Fast Stochastic Algorithms for SVD and PCA: Convergence Properties and Convexity %@Ohad Shamir %t2012 %cICML %f/ICML/ICML-2012-203.pdf %*Fast Stochastic Algorithms for SVD and PCA: Convergence Properties and Convexity %@Ohad Shamir %t2012 %cICML %f/ICML/ICML-2012-204.pdf %*Convergence of Stochastic Gradient Descent for PCA %@Ohad Shamir %t2012 %cICML %f/ICML/ICML-2012-205.pdf %*Convergence of Stochastic Gradient Descent for PCA %@Ohad Shamir %t2012 %cICML %f/ICML/ICML-2012-206.pdf %*Dealbreaker: A Nonlinear Latent Variable Model for Educational Data %@Andrew Lan, Tom Goldstein, Richard Baraniuk, Christoph Studer %t2012 %cICML %f/ICML/ICML-2012-207.pdf %*A Kernelized Stein Discrepancy for Goodness-of-fit Tests %@Qiang Liu, Jason Lee, Michael Jordan %t2012 %cICML %f/ICML/ICML-2012-208.pdf %*A Kernelized Stein Discrepancy for Goodness-of-fit Tests %@Qiang Liu, Jason Lee, Michael Jordan %t2012 %cICML %f/ICML/ICML-2012-209.pdf %*Variable Elimination in the Fourier Domain %@Yexiang Xue, Stefano Ermon, Ronan Le Bras, Carla, Bart Selman %t2012 %cICML %f/ICML/ICML-2012-210.pdf %*Variable Elimination in the Fourier Domain %@Yexiang Xue, Stefano Ermon, Ronan Le Bras, Carla, Bart Selman %t2012 %cICML %f/ICML/ICML-2012-211.pdf %*Low-Rank Matrix Approximation with Stability %@Dongsheng Li, Chao Chen, Qin Lv, Junchi Yan, Li Shang, Stephen Chu %t2012 %cICML %f/ICML/ICML-2012-212.pdf %*Linking losses for density ratio and class-probability estimation %@Aditya Menon, Cheng Soon Ong %t2012 %cICML %f/ICML/ICML-2012-213.pdf %*Linking losses for density ratio and class-probability estimation %@Aditya Menon, Cheng Soon Ong %t2012 %cICML %f/ICML/ICML-2012-214.pdf %*Stochastic Variance Reduction for Nonconvex Optimization %@Sashank J. Reddi, Ahmed Hefny, Suvrit Sra, Barnabas Poczos, Alex Smola %t2012 %cICML %f/ICML/ICML-2012-215.pdf %*Hierarchical Variational Models %@Rajesh Ranganath, Dustin Tran, David Blei %t2012 %cICML %f/ICML/ICML-2012-216.pdf %*Hierarchical Variational Models %@Rajesh Ranganath, Dustin Tran, David Blei %t2012 %cICML %f/ICML/ICML-2012-217.pdf %*Hierarchical Span-Based Conditional Random Fields for Labeling and Segmenting Events in Wearable Sensor Data Streams %@Roy Adams, Nazir Saleheen, Edison Thomaz, Abhinav Parate, Santosh Kumar, Benjamin Marlin %t2012 %cICML %f/ICML/ICML-2012-218.pdf %*Binary embeddings with structured hashed projections %@Anna Choromanska, Krzysztof Choromanski, Mariusz Bojarski, Tony Jebara, Sanjiv Kumar, Yann LeCun %t2012 %cICML %f/ICML/ICML-2012-219.pdf %*Binary embeddings with structured hashed projections %@Anna Choromanska, Krzysztof Choromanski, Mariusz Bojarski, Tony Jebara, Sanjiv Kumar, Yann LeCun %t2012 %cICML %f/ICML/ICML-2012-220.pdf %*A Variational Analysis of Stochastic Gradient Algorithms %@Stephan Mandt, Matthew Hoffman, David Blei %t2012 %cICML %f/ICML/ICML-2012-221.pdf %*A Variational Analysis of Stochastic Gradient Algorithms %@Stephan Mandt, Matthew Hoffman, David Blei %t2012 %cICML %f/ICML/ICML-2012-222.pdf %*Adaptive Sampling for SGD by Exploiting Side Information %@Siddharth Gopal %t2012 %cICML %f/ICML/ICML-2012-223.pdf %*Learning from Multiway Data: Simple and Efficient Tensor Regression %@Rose Yu, Yan Liu %t2012 %cICML %f/ICML/ICML-2012-224.pdf %*A Distributed Variational Inference Framework for Unifying Parallel Sparse Gaussian Process Regression Models %@Trong Nghia Hoang, Quang Minh Hoang, Bryan Kian Hsiang Low %t2012 %cICML %f/ICML/ICML-2012-225.pdf %*A Distributed Variational Inference Framework for Unifying Parallel Sparse Gaussian Process Regression Models %@Trong Nghia Hoang, Quang Minh Hoang, Bryan Kian Hsiang Low %t2012 %cICML %f/ICML/ICML-2012-226.pdf %*Online Stochastic Linear Optimization under One-bit Feedback %@Lijun Zhang, Tianbao Yang, Rong Jin, Yichi Xiao, Zhi-hua Zhou %t2012 %cICML %f/ICML/ICML-2012-227.pdf %*Online Stochastic Linear Optimization under One-bit Feedback %@Lijun Zhang, Tianbao Yang, Rong Jin, Yichi Xiao, Zhi-hua Zhou %t2012 %cICML %f/ICML/ICML-2012-228.pdf %*Adaptive Algorithms for Online Convex Optimization with Long-term Constraints %@Rodolphe Jenatton, Jim Huang, Cedric Archambeau %t2012 %cICML %f/ICML/ICML-2012-229.pdf %*Actively Learning Hemimetrics with Applications to Eliciting User Preferences %@Adish Singla, Sebastian Tschiatschek, Andreas Krause %t2012 %cICML %f/ICML/ICML-2012-230.pdf %*Learning Simple Algorithms from Examples %@Wojciech Zaremba, Tomas Mikolov, Armand Joulin, Rob Fergus %t2012 %cICML %f/ICML/ICML-2012-231.pdf %*Learning Physical Intuition of Block Towers by Example %@Adam Lerer, Sam Gross, Rob Fergus %t2012 %cICML %f/ICML/ICML-2012-232.pdf %*Structure Learning of Partitioned Markov Networks %@Song Liu, Taiji Suzuki, Masashi Sugiyama, Kenji Fukumizu %t2012 %cICML %f/ICML/ICML-2012-233.pdf %*Structure Learning of Partitioned Markov Networks %@Song Liu, Taiji Suzuki, Masashi Sugiyama, Kenji Fukumizu %t2012 %cICML %f/ICML/ICML-2012-234.pdf %*Tracking Slowly Moving Clairvoyant: Optimal Dynamic Regret of Online Learning with True and Noisy Gradient %@Tianbao Yang, Lijun Zhang, Rong Jin, Jinfeng Yi %t2012 %cICML %f/ICML/ICML-2012-235.pdf %*Tracking Slowly Moving Clairvoyant: Optimal Dynamic Regret of Online Learning with True and Noisy Gradient %@Tianbao Yang, Lijun Zhang, Rong Jin, Jinfeng Yi %t2012 %cICML %f/ICML/ICML-2012-236.pdf %*Beyond CCA: Moment Matching for Multi-View Models %@Anastasia Podosinnikova, Francis Bach, Simon Lacoste-Julien %t2012 %cICML %f/ICML/ICML-2012-237.pdf %*Beyond CCA: Moment Matching for Multi-View Models %@Anastasia Podosinnikova, Francis Bach, Simon Lacoste-Julien %t2012 %cICML %f/ICML/ICML-2012-238.pdf %*Fast methods for estimating the Numerical rank of large matrices %@Shashanka Ubaru, Yousef Saad %t2012 %cICML %f/ICML/ICML-2012-239.pdf %*Fast methods for estimating the Numerical rank of large matrices %@Shashanka Ubaru, Yousef Saad %t2012 %cICML %f/ICML/ICML-2012-240.pdf %*Unsupervised Deep Embedding for Clustering Analysis %@Junyuan Xie, Ross Girshick, Ali Farhadi %t2012 %cICML %f/ICML/ICML-2012-241.pdf %*Efficient Private Empirical Risk Minimization for High-dimensional Learning %@Shiva Prasad Kasiviswanathan, Hongxia Jin %t2012 %cICML %f/ICML/ICML-2012-242.pdf %*Efficient Private Empirical Risk Minimization for High-dimensional Learning %@Shiva Prasad Kasiviswanathan, Hongxia Jin %t2012 %cICML %f/ICML/ICML-2012-243.pdf %*Parameter Estimation for Generalized Thurstone Choice Models %@Milan Vojnovic, Seyoung Yun %t2012 %cICML %f/ICML/ICML-2012-244.pdf %*Parameter Estimation for Generalized Thurstone Choice Models %@Milan Vojnovic, Seyoung Yun %t2012 %cICML %f/ICML/ICML-2012-245.pdf %*Large-Margin Softmax Loss for Convolutional Neural Networks %@Weiyang Liu, Yandong Wen, Zhiding Yu, Meng Yang %t2012 %cICML %f/ICML/ICML-2012-246.pdf %*A Random Matrix Approach to Echo-State Neural Networks %@Romain Couillet, Gilles Wainrib, Hafiz Tiomoko Ali, Harry Sevi %t2012 %cICML %f/ICML/ICML-2012-247.pdf %*Supervised and Semi-Supervised Text Categorization using LSTM for Region Embeddings %@Rie Johnson, Tong Zhang %t2012 %cICML %f/ICML/ICML-2012-248.pdf %*Optimality of Belief Propagation for Crowdsourced Classification %@Jungseul Ok, Sewoong Oh, Jinwoo Shin, Yung Yi %t2012 %cICML %f/ICML/ICML-2012-249.pdf %*Optimality of Belief Propagation for Crowdsourced Classification %@Jungseul Ok, Sewoong Oh, Jinwoo Shin, Yung Yi %t2012 %cICML %f/ICML/ICML-2012-250.pdf %*Stability of Controllers for Gaussian Process Forward Models %@Julia Vinogradska, Bastian Bischoff, Duy Nguyen-Tuong, Anne Romer, Henner Schmidt, Jan Peters %t2012 %cICML %f/ICML/ICML-2012-251.pdf %*Learning privately from multiparty data %@Jihun Hamm, Yingjun Cao, Mikhail Belkin %t2012 %cICML %f/ICML/ICML-2012-252.pdf %*Learning privately from multiparty data %@Jihun Hamm, Yingjun Cao, Mikhail Belkin %t2012 %cICML %f/ICML/ICML-2012-253.pdf %*Network Morphism %@Tao Wei, Changhu Wang, Yong Rui, Chang Wen Chen %t2012 %cICML %f/ICML/ICML-2012-254.pdf %*A Kronecker-factored approximate Fisher matrix for convolution layers %@Roger Grosse, James Martens %t2012 %cICML %f/ICML/ICML-2012-255.pdf %*A Kronecker-factored approximate Fisher matrix for convolution layers %@Roger Grosse, James Martens %t2012 %cICML %f/ICML/ICML-2012-256.pdf %*Experimental Design on a Budget for Sparse Linear Models and Applications %@Sathya Narayanan Ravi, Vamsi Ithapu, Sterling Johnson, Vikas Singh %t2012 %cICML %f/ICML/ICML-2012-257.pdf %*Minding the Gaps for Block Frank-Wolfe Optimization of Structured SVMs %@Anton Osokin, Jean-Baptiste Alayrac, Isabella Lukasewitz, Puneet Dokania, Simon Lacoste-Julien %t2012 %cICML %f/ICML/ICML-2012-258.pdf %*Minding the Gaps for Block Frank-Wolfe Optimization of Structured SVMs %@Anton Osokin, Jean-Baptiste Alayrac, Isabella Lukasewitz, Puneet Dokania, Simon Lacoste-Julien %t2012 %cICML %f/ICML/ICML-2012-259.pdf %*Exact Exponent in Optimal Rates for Crowdsourcing %@Chao Gao, Yu Lu, Dengyong Zhou %t2012 %cICML %f/ICML/ICML-2012-260.pdf %*Exact Exponent in Optimal Rates for Crowdsourcing %@Chao Gao, Yu Lu, Dengyong Zhou %t2012 %cICML %f/ICML/ICML-2012-261.pdf %*Augmenting Supervised Neural Networks with Unsupervised Objectives for Large-scale Image Classification %@Yuting Zhang, Kibok Lee, Honglak Lee %t2012 %cICML %f/ICML/ICML-2012-262.pdf %*Augmenting Supervised Neural Networks with Unsupervised Objectives for Large-scale Image Classification %@Yuting Zhang, Kibok Lee, Honglak Lee %t2012 %cICML %f/ICML/ICML-2012-263.pdf %*Online Low-Rank Subspace Clustering by Basis Dictionary Pursuit %@Jie Shen, Ping Li, Huan Xu %t2012 %cICML %f/ICML/ICML-2012-264.pdf %*Online Low-Rank Subspace Clustering by Basis Dictionary Pursuit %@Jie Shen, Ping Li, Huan Xu %t2012 %cICML %f/ICML/ICML-2012-265.pdf %*A Self-Correcting Variable-Metric Algorithm for Stochastic Optimization %@Frank Curtis %t2012 %cICML %f/ICML/ICML-2012-266.pdf %*A Self-Correcting Variable-Metric Algorithm for Stochastic Optimization %@Frank Curtis %t2012 %cICML %f/ICML/ICML-2012-267.pdf %*Stochastic Quasi-Newton Langevin Monte Carlo %@Umut Simsekli, Roland Badeau, Taylan Cemgil, Gaël Richard %t2012 %cICML %f/ICML/ICML-2012-268.pdf %*Stochastic Quasi-Newton Langevin Monte Carlo %@Umut Simsekli, Roland Badeau, Taylan Cemgil, Gaël Richard %t2012 %cICML %f/ICML/ICML-2012-269.pdf %*Doubly Robust Off-policy Value Evaluation for Reinforcement Learning %@Nan Jiang, Lihong Li %t2012 %cICML %f/ICML/ICML-2012-270.pdf %*Doubly Robust Off-policy Value Evaluation for Reinforcement Learning %@Nan Jiang, Lihong Li %t2012 %cICML %f/ICML/ICML-2012-271.pdf %*Fast Rate Analysis of Some Stochastic Optimization Algorithms %@Chao Qu, Huan Xu, Chong jin Ong %t2012 %cICML %f/ICML/ICML-2012-272.pdf %*Fast Rate Analysis of Some Stochastic Optimization Algorithms %@Chao Qu, Huan Xu, Chong jin Ong %t2012 %cICML %f/ICML/ICML-2012-273.pdf %*Fast k-Nearest Neighbour Search via Dynamic Continuous Indexing %@Ke Li, Jitendra Malik %t2012 %cICML %f/ICML/ICML-2012-274.pdf %*Fast k-Nearest Neighbour Search via Dynamic Continuous Indexing %@Ke Li, Jitendra Malik %t2012 %cICML %f/ICML/ICML-2012-275.pdf %*Smooth Imitation Learning for Online Sequence Prediction %@Hoang Le, Andrew Kang, Yisong Yue, Peter Carr %t2012 %cICML %f/ICML/ICML-2012-276.pdf %*Smooth Imitation Learning for Online Sequence Prediction %@Hoang Le, Andrew Kang, Yisong Yue, Peter Carr %t2012 %cICML %f/ICML/ICML-2012-277.pdf %*Community Recovery in Graphs with Locality %@Yuxin Chen, Govinda Kamath, Changho Suh, David Tse %t2012 %cICML %f/ICML/ICML-2012-278.pdf %*Variance Reduction for Faster Non-Convex Optimization %@Zeyuan Allen-Zhu, Elad Hazan %t2012 %cICML %f/ICML/ICML-2012-279.pdf %*Loss factorization, weakly supervised learning and label noise robustness %@Giorgio Patrini, Frank Nielsen, Richard Nock, Marcello Carioni %t2012 %cICML %f/ICML/ICML-2012-280.pdf %*Loss factorization, weakly supervised learning and label noise robustness %@Giorgio Patrini, Frank Nielsen, Richard Nock, Marcello Carioni %t2012 %cICML %f/ICML/ICML-2012-281.pdf %*Analysis of Deep Neural Networks with Extended Data Jacobian Matrix %@Shengjie Wang, Abdel-rahman Mohamed, Rich Caruana, Jeff Bilmes, Matthai Plilipose, Matthew Richardson, Krzysztof Geras, Gregor Urban, Ozlem Aslan %t2012 %cICML %f/ICML/ICML-2012-282.pdf %*Doubly Decomposing Nonparametric Tensor Regression %@Masaaki Imaizumi, Kohei Hayashi %t2012 %cICML %f/ICML/ICML-2012-283.pdf %*Doubly Decomposing Nonparametric Tensor Regression %@Masaaki Imaizumi, Kohei Hayashi %t2012 %cICML %f/ICML/ICML-2012-284.pdf %*Hyperparameter optimization with approximate gradient %@Fabian Pedregosa %t2012 %cICML %f/ICML/ICML-2012-285.pdf %*SDCA without Duality, Regularization, and Individual Convexity %@Shai Shalev-Shwartz %t2012 %cICML %f/ICML/ICML-2012-286.pdf %*Heteroscedastic Sequences: Beyond Gaussianity %@Oren Anava, Shie Mannor %t2012 %cICML %f/ICML/ICML-2012-287.pdf %*Heteroscedastic Sequences: Beyond Gaussianity %@Oren Anava, Shie Mannor %t2012 %cICML %f/ICML/ICML-2012-288.pdf %*A Neural Autoregressive Approach to Collaborative Filtering %@Yin Zheng, Bangsheng Tang, Wenkui Ding, Hanning Zhou %t2012 %cICML %f/ICML/ICML-2012-289.pdf %*A Neural Autoregressive Approach to Collaborative Filtering %@Yin Zheng, Bangsheng Tang, Wenkui Ding, Hanning Zhou %t2012 %cICML %f/ICML/ICML-2012-290.pdf %*On the Quality of the Initial Basin in Overspecified Neural Networks %@Itay Safran, Ohad Shamir %t2012 %cICML %f/ICML/ICML-2012-291.pdf %*On the Quality of the Initial Basin in Overspecified Neural Networks %@Itay Safran, Ohad Shamir %t2012 %cICML %f/ICML/ICML-2012-292.pdf %*Primal-Dual Rates and Certificates %@Celestine Dünner, Simone Forte, Martin Takac, Martin Jaggi %t2012 %cICML %f/ICML/ICML-2012-293.pdf %*Primal-Dual Rates and Certificates %@Celestine Dünner, Simone Forte, Martin Takac, Martin Jaggi %t2012 %cICML %f/ICML/ICML-2012-294.pdf %*Minimizing the Maximal Loss: How and Why %@Shai Shalev-Shwartz, Yonatan Wexler %t2012 %cICML %f/ICML/ICML-2012-295.pdf %*Minimizing the Maximal Loss: How and Why %@Shai Shalev-Shwartz, Yonatan Wexler %t2012 %cICML %f/ICML/ICML-2012-296.pdf %*The Information-Theoretic Requirements of Subspace Clustering with Missing Data %@Daniel Pimentel-Alarcon, Robert Nowak %t2012 %cICML %f/ICML/ICML-2012-297.pdf %*Online Learning with Feedback Graphs Without the Graphs %@Alon Cohen, Tamir Hazan, Tomer Koren %t2012 %cICML %f/ICML/ICML-2012-298.pdf %*PAC learning of Probabilistic Automaton based on the Method of Moments %@Hadrien Glaude, Olivier Pietquin %t2012 %cICML %f/ICML/ICML-2012-299.pdf %*PAC learning of Probabilistic Automaton based on the Method of Moments %@Hadrien Glaude, Olivier Pietquin %t2012 %cICML %f/ICML/ICML-2012-300.pdf %*Estimating Structured Vector Autoregressive Models %@Igor Melnyk, Arindam Banerjee %t2012 %cICML %f/ICML/ICML-2012-301.pdf %*Estimating Structured Vector Autoregressive Models %@Igor Melnyk, Arindam Banerjee %t2012 %cICML %f/ICML/ICML-2012-302.pdf %*Mixing Rates for the Alternating Gibbs Sampler over Restricted Boltzmann Machines and Friends %@Christopher Tosh %t2012 %cICML %f/ICML/ICML-2012-303.pdf %*Mixing Rates for the Alternating Gibbs Sampler over Restricted Boltzmann Machines and Friends %@Christopher Tosh %t2012 %cICML %f/ICML/ICML-2012-304.pdf %*Polynomial Networks and Factorization Machines: New Insights and Efficient Training Algorithms %@Mathieu Blondel, Masakazu Ishihata, Akinori Fujino, Naonori Ueda %t2012 %cICML %f/ICML/ICML-2012-305.pdf %*Polynomial Networks and Factorization Machines: New Insights and Efficient Training Algorithms %@Mathieu Blondel, Masakazu Ishihata, Akinori Fujino, Naonori Ueda %t2012 %cICML %f/ICML/ICML-2012-306.pdf %*A New PAC-Bayesian Perspective on Domain Adaptation %@Pascal Germain, Amaury Habrard, François Laviolette, Emilie Morvant %t2012 %cICML %f/ICML/ICML-2012-307.pdf %*A New PAC-Bayesian Perspective on Domain Adaptation %@Pascal Germain, Amaury Habrard, François Laviolette, Emilie Morvant %t2012 %cICML %f/ICML/ICML-2012-308.pdf %*Correlation Clustering and Biclustering with Locally Bounded Errors %@Gregory Puleo, Olgica Milenkovic %t2012 %cICML %f/ICML/ICML-2012-309.pdf %*PAC Lower Bounds and Efficient Algorithms for The Max K-Armed Bandit Problem %@Yahel David, Nahum Shimkin %t2012 %cICML %f/ICML/ICML-2012-310.pdf %*PAC Lower Bounds and Efficient Algorithms for The Max K-Armed Bandit Problem %@Yahel David, Nahum Shimkin %t2012 %cICML %f/ICML/ICML-2012-311.pdf %*A Comparative Analysis and Study of Multiview CNN Models for Joint Object Categorization and Pose Estimation %@Mohamed Elhoseiny, Tarek El-Gaaly, Amr Bakry, Ahmed Elgammal %t2012 %cICML %f/ICML/ICML-2012-312.pdf %*A Comparative Analysis and Study of Multiview CNN Models for Joint Object Categorization and Pose Estimation %@Mohamed Elhoseiny, Tarek El-Gaaly, Amr Bakry, Ahmed Elgammal %t2012 %cICML %f/ICML/ICML-2012-313.pdf %*BASC: Applying Bayesian Optimization to the Search for Global Minima on Potential Energy Surfaces %@Shane Carr, Roman Garnett, Cynthia Lo %t2012 %cICML %f/ICML/ICML-2012-314.pdf %*On the Iteration Complexity of Oblivious First-Order Optimization Algorithms %@Yossi Arjevani, Ohad Shamir %t2012 %cICML %f/ICML/ICML-2012-315.pdf %*On the Iteration Complexity of Oblivious First-Order Optimization Algorithms %@Yossi Arjevani, Ohad Shamir %t2012 %cICML %f/ICML/ICML-2012-316.pdf %*Stochastic Variance Reduced Optimization for Nonconvex Sparse Learning %@Xingguo Li, Tuo Zhao, Raman Arora, Han Liu, Jarvis Haupt %t2012 %cICML %f/ICML/ICML-2012-317.pdf %*Stochastic Variance Reduced Optimization for Nonconvex Sparse Learning %@Xingguo Li, Tuo Zhao, Raman Arora, Han Liu, Jarvis Haupt %t2012 %cICML %f/ICML/ICML-2012-318.pdf %*Analysis of Variational Bayesian Factorizations for Sparse and Low-Rank Estimation %@David Wipf %t2012 %cICML %f/ICML/ICML-2012-319.pdf %*Fast k-means with accurate bounds %@James Newling, Francois Fleuret %t2012 %cICML %f/ICML/ICML-2012-320.pdf %*Fast k-means with accurate bounds %@James Newling, Francois Fleuret %t2012 %cICML %f/ICML/ICML-2012-321.pdf %*Boolean Matrix Factorization and Noisy Completion via Message Passing %@Siamak Ravanbakhsh, Barnabas Poczos, Russell Greiner %t2012 %cICML %f/ICML/ICML-2012-322.pdf %*Boolean Matrix Factorization and Noisy Completion via Message Passing %@Siamak Ravanbakhsh, Barnabas Poczos, Russell Greiner %t2012 %cICML %f/ICML/ICML-2012-323.pdf %*Convolutional Rectifier Networks as Generalized Tensor Decompositions %@Nadav Cohen, Amnon Shashua %t2012 %cICML %f/ICML/ICML-2012-324.pdf %*Convolutional Rectifier Networks as Generalized Tensor Decompositions %@Nadav Cohen, Amnon Shashua %t2012 %cICML %f/ICML/ICML-2012-325.pdf %*Low-rank Solutions of Linear Matrix Equations via Procrustes Flow %@Stephen Tu, Ross Boczar, Max Simchowitz, Mahdi Soltanolkotabi, Ben Recht %t2012 %cICML %f/ICML/ICML-2012-326.pdf %*Anytime Exploration for Multi-armed Bandits using Confidence Information %@Kwang-Sung Jun, Robert Nowak %t2012 %cICML %f/ICML/ICML-2012-327.pdf %*Anytime Exploration for Multi-armed Bandits using Confidence Information %@Kwang-Sung Jun, Robert Nowak %t2012 %cICML %f/ICML/ICML-2012-328.pdf %*Structured Prediction Energy Networks %@David Belanger, Andrew McCallum %t2012 %cICML %f/ICML/ICML-2012-329.pdf %*L1-regularized Neural Networks are Improperly Learnable in Polynomial Time %@Yuchen Zhang, Jason D. Lee, Michael I. Jordan %t2012 %cICML %f/ICML/ICML-2012-330.pdf %*Compressive Spectral Clustering %@Nicolas Tremblay, Gilles Puy, Remi Gribonval, Pierre Vandergheynst %t2012 %cICML %f/ICML/ICML-2012-331.pdf %*Compressive Spectral Clustering %@Nicolas Tremblay, Gilles Puy, Remi Gribonval, Pierre Vandergheynst %t2012 %cICML %f/ICML/ICML-2012-332.pdf %*Low-rank tensor completion: a Riemannian manifold preconditioning approach %@Hiroyuki Kasai, Bamdev Mishra %t2012 %cICML %f/ICML/ICML-2012-333.pdf %*Low-rank tensor completion: a Riemannian manifold preconditioning approach %@Hiroyuki Kasai, Bamdev Mishra %t2012 %cICML %f/ICML/ICML-2012-334.pdf %*Provable Non-convex Phase Retrieval with Outliers: Median TruncatedWirtinger Flow %@Huishuai Zhang, Yuejie Chi, Yingbin Liang %t2012 %cICML %f/ICML/ICML-2012-335.pdf %*Provable Non-convex Phase Retrieval with Outliers: Median TruncatedWirtinger Flow %@Huishuai Zhang, Yuejie Chi, Yingbin Liang %t2012 %cICML %f/ICML/ICML-2012-336.pdf %*Estimating Maximum Expected Value through Gaussian Approximation %@Carlo D’Eramo, Marcello Restelli, Alessandro Nuara %t2012 %cICML %f/ICML/ICML-2012-337.pdf %*Estimating Maximum Expected Value through Gaussian Approximation %@Carlo D’Eramo, Marcello Restelli, Alessandro Nuara %t2012 %cICML %f/ICML/ICML-2012-338.pdf %*Representational Similarity Learning with Application to Brain Networks %@Urvashi Oswal, Christopher Cox, Matthew Lambon-Ralph, Timothy Rogers, Robert Nowak %t2012 %cICML %f/ICML/ICML-2012-339.pdf %*Representational Similarity Learning with Application to Brain Networks %@Urvashi Oswal, Christopher Cox, Matthew Lambon-Ralph, Timothy Rogers, Robert Nowak %t2012 %cICML %f/ICML/ICML-2012-340.pdf %*Dropout as a Bayesian Approximation: Representing Model Uncertainty in Deep Learning %@Yarin Gal, Zoubin Ghahramani %t2012 %cICML %f/ICML/ICML-2012-341.pdf %*Dropout as a Bayesian Approximation: Representing Model Uncertainty in Deep Learning %@Yarin Gal, Zoubin Ghahramani %t2012 %cICML %f/ICML/ICML-2012-342.pdf %*Generative Adversarial Text to Image Synthesis %@Scott Reed, Zeynep Akata, Xinchen Yan, Lajanugen Logeswaran, Bernt Schiele, Honglak Lee %t2012 %cICML %f/ICML/ICML-2012-343.pdf %*Dirichlet Process Mixture Model for Correcting Technical Variation in Single-Cell Gene Expression Data %@Sandhya Prabhakaran, Elham Azizi, Ambrose Carr, Dana Pe’er %t2012 %cICML %f/ICML/ICML-2012-344.pdf %*Dirichlet Process Mixture Model for Correcting Technical Variation in Single-Cell Gene Expression Data %@Sandhya Prabhakaran, Elham Azizi, Ambrose Carr, Dana Pe’er %t2012 %cICML %f/ICML/ICML-2012-345.pdf %*Improved SVRG for Non-Strongly-Convex or Sum-of-Non-Convex Objectives %@Zeyuan Allen-Zhu, Yang Yuan %t2012 %cICML %f/ICML/ICML-2012-346.pdf %*Sparse Parameter Recovery from Aggregated Data %@Avradeep Bhowmik, Joydeep Ghosh, Oluwasanmi Koyejo %t2012 %cICML %f/ICML/ICML-2012-347.pdf %*Sparse Parameter Recovery from Aggregated Data %@Avradeep Bhowmik, Joydeep Ghosh, Oluwasanmi Koyejo %t2012 %cICML %f/ICML/ICML-2012-348.pdf %*Deep Structured Energy Based Models for Anomaly Detection %@Shuangfei Zhai, Yu Cheng, Weining Lu, Zhongfei Zhang %t2012 %cICML %f/ICML/ICML-2012-349.pdf %*Even Faster Accelerated Coordinate Descent Using Non-Uniform Sampling %@Zeyuan Allen-Zhu, Zheng Qu, Peter Richtarik, Yang Yuan %t2012 %cICML %f/ICML/ICML-2012-350.pdf %*Unitary Evolution Recurrent Neural Networks %@Martin Arjovsky, Amar Shah, Yoshua Bengio %t2012 %cICML %f/ICML/ICML-2012-351.pdf %*Markov Latent Feature Models %@Aonan Zhang, John Paisley %t2012 %cICML %f/ICML/ICML-2012-352.pdf %*The Knowledge Gradient for Sequential Decision Making with Stochastic Binary Feedbacks %@Yingfei Wang, Chu Wang, Warren Powell %t2012 %cICML %f/ICML/ICML-2012-353.pdf %*The Knowledge Gradient for Sequential Decision Making with Stochastic Binary Feedbacks %@Yingfei Wang, Chu Wang, Warren Powell %t2012 %cICML %f/ICML/ICML-2012-354.pdf %*A Simple and Provable Algorithm for Sparse Diagonal CCA %@Megasthenis Asteris, Anastasios Kyrillidis, Oluwasanmi Koyejo, Russell Poldrack %t2012 %cICML %f/ICML/ICML-2012-355.pdf %*Quadratic Optimization with Orthogonality Constraints: Explicit Lojasiewicz Exponent and Linear Convergence of Line-Search Methods %@Huikang Liu, Weijie Wu, Anthony Man-Cho So %t2012 %cICML %f/ICML/ICML-2012-356.pdf %*Quadratic Optimization with Orthogonality Constraints: Explicit Lojasiewicz Exponent and Linear Convergence of Line-Search Methods %@Huikang Liu, Weijie Wu, Anthony Man-Cho So %t2012 %cICML %f/ICML/ICML-2012-357.pdf %*Normalization Propagation: A Parametric Technique for Removing Internal Covariate Shift in Deep Networks %@Devansh Arpit, Yingbo Zhou, Bhargava Kota, Venu Govindaraju %t2012 %cICML %f/ICML/ICML-2012-358.pdf %*Normalization Propagation: A Parametric Technique for Removing Internal Covariate Shift in Deep Networks %@Devansh Arpit, Yingbo Zhou, Bhargava Kota, Venu Govindaraju %t2012 %cICML %f/ICML/ICML-2012-359.pdf %*Learning to Generate with Memory %@Chongxuan Li, Jun Zhu, Bo Zhang %t2012 %cICML %f/ICML/ICML-2012-360.pdf %*Learning to Generate with Memory %@Chongxuan Li, Jun Zhu, Bo Zhang %t2012 %cICML %f/ICML/ICML-2012-361.pdf %*Learning End-to-end Video Classification with Rank-Pooling %@Basura Fernando, Stephen Gould %t2012 %cICML %f/ICML/ICML-2012-362.pdf %*Learning to Filter with Predictive State Inference Machines %@Wen Sun, Arun Venkatraman, Byron Boots, J.Andrew Bagnell %t2012 %cICML %f/ICML/ICML-2012-363.pdf %*Learning to Filter with Predictive State Inference Machines %@Wen Sun, Arun Venkatraman, Byron Boots, J.Andrew Bagnell %t2012 %cICML %f/ICML/ICML-2012-364.pdf %*A Subspace Learning Approach for High Dimensional Matrix Decomposition with Efficient Column/Row Sampling %@Mostafa Rahmani, Geroge Atia %t2012 %cICML %f/ICML/ICML-2012-365.pdf %*DCM Bandits: Learning to Rank with Multiple Clicks %@Sumeet Katariya, Branislav Kveton, Csaba Szepesvari, Zheng Wen %t2012 %cICML %f/ICML/ICML-2012-366.pdf %*DCM Bandits: Learning to Rank with Multiple Clicks %@Sumeet Katariya, Branislav Kveton, Csaba Szepesvari, Zheng Wen %t2012 %cICML %f/ICML/ICML-2012-367.pdf %*Train faster, generalize better: Stability of stochastic gradient descent %@Moritz Hardt, Ben Recht, Yoram Singer %t2012 %cICML %f/ICML/ICML-2012-368.pdf %*Copeland Dueling Bandit Problem: Regret Lower Bound, Optimal Algorithm, and Computationally Efficient Algorithm %@Junpei Komiyama, Junya Honda, Hiroshi Nakagawa %t2012 %cICML %f/ICML/ICML-2012-369.pdf %*Copeland Dueling Bandit Problem: Regret Lower Bound, Optimal Algorithm, and Computationally Efficient Algorithm %@Junpei Komiyama, Junya Honda, Hiroshi Nakagawa %t2012 %cICML %f/ICML/ICML-2012-370.pdf %*Contextual Combinatorial Cascading Bandits %@Shuai Li, Baoxiang Wang, Shengyu Zhang, Wei Chen %t2012 %cICML %f/ICML/ICML-2012-371.pdf %*Contextual Combinatorial Cascading Bandits %@Shuai Li, Baoxiang Wang, Shengyu Zhang, Wei Chen %t2012 %cICML %f/ICML/ICML-2012-372.pdf %*Conservative Bandits %@Yifan Wu, Roshan Shariff, Tor Lattimore, Csaba Szepesvari %t2012 %cICML %f/ICML/ICML-2012-373.pdf %*Variance-Reduced and Projection-Free Stochastic Optimization %@Elad Hazan, Haipeng Luo %t2012 %cICML %f/ICML/ICML-2012-374.pdf %*Variance-Reduced and Projection-Free Stochastic Optimization %@Elad Hazan, Haipeng Luo %t2012 %cICML %f/ICML/ICML-2012-375.pdf %*Factored Temporal Sigmoid Belief Networks for Sequence Learning %@Jiaming Song, Zhe Gan, Lawrence Carin %t2012 %cICML %f/ICML/ICML-2012-376.pdf %*False Discovery Rate Control and Statistical Quality Assessment of Annotators in Crowdsourced Ranking %@QianQian Xu, Jiechao Xiong, Xiaochun Cao, Yuan Yao %t2012 %cICML %f/ICML/ICML-2012-377.pdf %*Strongly-Typed Recurrent Neural Networks %@David Balduzzi, Muhammad Ghifary %t2012 %cICML %f/ICML/ICML-2012-378.pdf %*Distributed Clustering of Linear Bandits in Peer to Peer Networks %@Nathan Korda, Balazs Szorenyi, Shuai Li %t2012 %cICML %f/ICML/ICML-2012-379.pdf %*Distributed Clustering of Linear Bandits in Peer to Peer Networks %@Nathan Korda, Balazs Szorenyi, Shuai Li %t2012 %cICML %f/ICML/ICML-2012-380.pdf %*Collapsed Variational Inference for Sum-Product Networks %@Han Zhao, Tameem Adel, Geoff Gordon, Brandon Amos %t2012 %cICML %f/ICML/ICML-2012-381.pdf %*Collapsed Variational Inference for Sum-Product Networks %@Han Zhao, Tameem Adel, Geoff Gordon, Brandon Amos %t2012 %cICML %f/ICML/ICML-2012-382.pdf %*On the Analysis of Complex Backup Strategies in Monte Carlo Tree Search %@Piyush Khandelwal, Elad Liebman, Scott, Peter Stone %t2012 %cICML %f/ICML/ICML-2012-383.pdf %*Benchmarking Deep Reinforcement Learning for Continuous Control %@Yan Duan, Xi Chen, Rein Houthooft, John Schulman, Pieter Abbeel %t2012 %cICML %f/ICML/ICML-2012-384.pdf %*Benchmarking Deep Reinforcement Learning for Continuous Control %@Yan Duan, Xi Chen, Rein Houthooft, John Schulman, Pieter Abbeel %t2012 %cICML %f/ICML/ICML-2012-385.pdf %*K-Means Clustering with Distributed Dimensions %@Hu Ding, Yu Liu, Lingxiao Huang, Jian Li %t2012 %cICML %f/ICML/ICML-2012-386.pdf %*K-Means Clustering with Distributed Dimensions %@Hu Ding, Yu Liu, Lingxiao Huang, Jian Li %t2012 %cICML %f/ICML/ICML-2012-387.pdf %*Texture Networks: Feed-forward Synthesis of Textures and Stylized Images %@Dmitry Ulyanov, Vadim Lebedev, Andrea, Victor Lempitsky %t2012 %cICML %f/ICML/ICML-2012-388.pdf %*Texture Networks: Feed-forward Synthesis of Textures and Stylized Images %@Dmitry Ulyanov, Vadim Lebedev, Andrea, Victor Lempitsky %t2012 %cICML %f/ICML/ICML-2012-389.pdf %*Fast Constrained Submodular Maximization: Personalized Data Summarization %@Baharan Mirzasoleiman, Ashwinkumar Badanidiyuru, Amin Karbasi %t2012 %cICML %f/ICML/ICML-2012-390.pdf %*Fast Constrained Submodular Maximization: Personalized Data Summarization %@Baharan Mirzasoleiman, Ashwinkumar Badanidiyuru, Amin Karbasi %t2012 %cICML %f/ICML/ICML-2012-391.pdf %*On the Statistical Limits of Convex Relaxations %@Zhaoran Wang, Quanquan Gu, Han Liu %t2012 %cICML %f/ICML/ICML-2012-392.pdf %*On the Statistical Limits of Convex Relaxations %@Zhaoran Wang, Quanquan Gu, Han Liu %t2012 %cICML %f/ICML/ICML-2012-393.pdf %*Ask Me Anything: Dynamic Memory Networks for Natural Language Processing %@Ankit Kumar, Ozan Irsoy, Peter Ondruska, Mohit Iyyer, James Bradbury, Ishaan Gulrajani, Victor Zhong, Romain Paulus, Richard Socher %t2012 %cICML %f/ICML/ICML-2012-394.pdf %*Ask Me Anything: Dynamic Memory Networks for Natural Language Processing %@Ankit Kumar, Ozan Irsoy, Peter Ondruska, Mohit Iyyer, James Bradbury, Ishaan Gulrajani, Victor Zhong, Romain Paulus, Richard Socher %t2012 %cICML %f/ICML/ICML-2012-395.pdf %*Gossip Dual Averaging for Decentralized Optimization of Pairwise Functions %@Igor Colin, Aurelien Bellet, Joseph Salmon, Stéphan Clémençon %t2012 %cICML %f/ICML/ICML-2012-396.pdf %*Gossip Dual Averaging for Decentralized Optimization of Pairwise Functions %@Igor Colin, Aurelien Bellet, Joseph Salmon, Stéphan Clémençon %t2012 %cICML %f/ICML/ICML-2012-397.pdf %*Solving Ridge Regression using Sketched Preconditioned SVRG %@Alon Gonen, Francesco Orabona, Shai Shalev-Shwartz %t2012 %cICML %f/ICML/ICML-2012-398.pdf %*Solving Ridge Regression using Sketched Preconditioned SVRG %@Alon Gonen, Francesco Orabona, Shai Shalev-Shwartz %t2012 %cICML %f/ICML/ICML-2012-399.pdf %*Cumulative Prospect Theory Meets Reinforcement Learning: Prediction and Control %@Prashanth L.A., Cheng Jie, Michael Fu, Steve Marcus, Csaba Szepesvari %t2012 %cICML %f/ICML/ICML-2012-400.pdf %*Estimating Accuracy from Unlabeled Data: A Bayesian Approach %@Emmanouil Antonios Platanios, Avinava Dubey, Tom Mitchell %t2012 %cICML %f/ICML/ICML-2012-401.pdf %*Estimating Accuracy from Unlabeled Data: A Bayesian Approach %@Emmanouil Antonios Platanios, Avinava Dubey, Tom Mitchell %t2012 %cICML %f/ICML/ICML-2012-402.pdf %*Non-negative Matrix Factorization under Heavy Noise %@Chiranjib Bhattacharya, Navin Goyal, Ravindran Kannan, Jagdeep Pani %t2012 %cICML %f/ICML/ICML-2012-403.pdf %*Non-negative Matrix Factorization under Heavy Noise %@Chiranjib Bhattacharya, Navin Goyal, Ravindran Kannan, Jagdeep Pani %t2012 %cICML %f/ICML/ICML-2012-404.pdf %*Extreme F-measure Maximization using Sparse Probability Estimates %@Kalina Jasinska, Krzysztof Dembczynski, Robert Busa-Fekete, Karlson Pfannschmidt, Timo Klerx, Eyke Hullermeier %t2012 %cICML %f/ICML/ICML-2012-405.pdf %*Extreme F-measure Maximization using Sparse Probability Estimates %@Kalina Jasinska, Krzysztof Dembczynski, Robert Busa-Fekete, Karlson Pfannschmidt, Timo Klerx, Eyke Hullermeier %t2012 %cICML %f/ICML/ICML-2012-406.pdf %*Auxiliary Deep Generative Models %@Lars Maaløe, Casper Kaae Sønderby, Søren Kaae Sønderby, Ole Winther %t2012 %cICML %f/ICML/ICML-2012-407.pdf %*Importance Sampling Tree for Large-scale Empirical Expectation %@Olivier Canevet, Cijo Jose, Francois Fleuret %t2012 %cICML %f/ICML/ICML-2012-408.pdf %*Importance Sampling Tree for Large-scale Empirical Expectation %@Olivier Canevet, Cijo Jose, Francois Fleuret %t2012 %cICML %f/ICML/ICML-2012-409.pdf %*Starting Small - Learning with Adaptive Sample Sizes %@Hadi Daneshmand, Aurelien Lucchi, Thomas Hofmann %t2012 %cICML %f/ICML/ICML-2012-410.pdf %*Starting Small - Learning with Adaptive Sample Sizes %@Hadi Daneshmand, Aurelien Lucchi, Thomas Hofmann %t2012 %cICML %f/ICML/ICML-2012-411.pdf %*Deep Gaussian Processes for Regression using Approximate Expectation Propagation %@Thang Bui, Daniel Hernandez-Lobato, Jose miguel Hernandez-Lobato, Yingzhen Li, Richard Turner %t2012 %cICML %f/ICML/ICML-2012-412.pdf %*Deep Gaussian Processes for Regression using Approximate Expectation Propagation %@Thang Bui, Daniel Hernandez-Lobato, Jose miguel Hernandez-Lobato, Yingzhen Li, Richard Turner %t2012 %cICML %f/ICML/ICML-2012-413.pdf %*DR-ABC: Approximate Bayesian Computation with Kernel-Based Distribution Regression %@Jovana Mitrovic, Dino Sejdinovic, Yee-Whye Teh %t2012 %cICML %f/ICML/ICML-2012-414.pdf %*Predictive Entropy Search for Multi-objective Bayesian Optimization %@Daniel Hernandez-Lobato, Jose miguel Hernandez-Lobato, Amar Shah, Ryan Adams %t2012 %cICML %f/ICML/ICML-2012-415.pdf %*Predictive Entropy Search for Multi-objective Bayesian Optimization %@Daniel Hernandez-Lobato, Jose miguel Hernandez-Lobato, Amar Shah, Ryan Adams %t2012 %cICML %f/ICML/ICML-2012-416.pdf %*Rich Component Analysis %@Rong Ge, James Zou %t2012 %cICML %f/ICML/ICML-2012-417.pdf %*Rich Component Analysis %@Rong Ge, James Zou %t2012 %cICML %f/ICML/ICML-2012-418.pdf %*Black-Box Alpha Divergence Minimization %@Jose miguel Hernandez-Lobato, Yingzhen Li, Mark Rowland, Thang Bui, Daniel Hernandez-Lobato, Richard Turner %t2012 %cICML %f/ICML/ICML-2012-419.pdf %*Black-Box Alpha Divergence Minimization %@Jose miguel Hernandez-Lobato, Yingzhen Li, Mark Rowland, Thang Bui, Daniel Hernandez-Lobato, Richard Turner %t2012 %cICML %f/ICML/ICML-2012-420.pdf %*One-Shot Generalization in Deep Generative Models %@Danilo Rezende, Shakir, Ivo Danihelka, Karol Gregor, Daan Wierstra %t2012 %cICML %f/ICML/ICML-2012-421.pdf %*Optimal Classification with Multivariate Losses %@Nagarajan Natarajan, Oluwasanmi Koyejo, Pradeep Ravikumar, Inderjit Dhillon %t2012 %cICML %f/ICML/ICML-2012-422.pdf %*Optimal Classification with Multivariate Losses %@Nagarajan Natarajan, Oluwasanmi Koyejo, Pradeep Ravikumar, Inderjit Dhillon %t2012 %cICML %f/ICML/ICML-2012-423.pdf %*A ranking approach to global optimization %@Cedric Malherbe, Emile Contal, Nicolas Vayatis %t2012 %cICML %f/ICML/ICML-2012-424.pdf %*A ranking approach to global optimization %@Cedric Malherbe, Emile Contal, Nicolas Vayatis %t2012 %cICML %f/ICML/ICML-2012-425.pdf %*Parallel and Distributed Block-Coordinate Frank-Wolfe Algorithms %@Yu-Xiang Wang, Veeranjaneyulu Sadhanala, Wei Dai, Willie Neiswanger, Suvrit Sra, Eric Xing %t2012 %cICML %f/ICML/ICML-2012-426.pdf %*Parallel and Distributed Block-Coordinate Frank-Wolfe Algorithms %@Yu-Xiang Wang, Veeranjaneyulu Sadhanala, Wei Dai, Willie Neiswanger, Suvrit Sra, Eric Xing %t2012 %cICML %f/ICML/ICML-2012-427.pdf %*Autoencoding beyond pixels using a learned similarity metric %@Anders Boesen Lindbo Larsen, Søren Kaae Sønderby, Hugo Larochelle, Ole Winther %t2012 %cICML %f/ICML/ICML-2012-428.pdf %*Ensuring Rapid Mixing and Low Bias for Asynchronous Gibbs Sampling %@Christopher De Sa, Chris Re, Kunle Olukotun %t2012 %cICML %f/ICML/ICML-2012-429.pdf %*Ensuring Rapid Mixing and Low Bias for Asynchronous Gibbs Sampling %@Christopher De Sa, Chris Re, Kunle Olukotun %t2012 %cICML %f/ICML/ICML-2012-430.pdf %*Simultaneous Safe Screening of Features and Samples in Doubly Sparse Modeling %@Atsushi Shibagaki, Masayuki Karasuyama, Kohei Hatano, Ichiro Takeuchi %t2012 %cICML %f/ICML/ICML-2012-431.pdf %*Anytime optimal algorithms in stochastic multi-armed bandits %@Rémy Degenne, Vianney Perchet %t2012 %cICML %f/ICML/ICML-2012-432.pdf %*Anytime optimal algorithms in stochastic multi-armed bandits %@Rémy Degenne, Vianney Perchet %t2012 %cICML %f/ICML/ICML-2012-433.pdf %*Bounded Off-Policy Evaluation with Missing Data for Course Recommendation and Curriculum Design %@William Hoiles, Mihaela van der Schaar %t2012 %cICML %f/ICML/ICML-2012-434.pdf %*Bounded Off-Policy Evaluation with Missing Data for Course Recommendation and Curriculum Design %@William Hoiles, Mihaela van der Schaar %t2012 %cICML %f/ICML/ICML-2012-435.pdf %*On collapsed representation of hierarchical Completely Random Measures %@Gaurav Pandey, Ambedkar Dukkipati %t2012 %cICML %f/ICML/ICML-2012-436.pdf %*On collapsed representation of hierarchical Completely Random Measures %@Gaurav Pandey, Ambedkar Dukkipati %t2012 %cICML %f/ICML/ICML-2012-437.pdf %*From Softmax to Sparsemax: A Sparse Model of Attention and Multi-Label Classification %@Andre Martins, Ramon Astudillo %t2012 %cICML %f/ICML/ICML-2012-438.pdf %*From Softmax to Sparsemax: A Sparse Model of Attention and Multi-Label Classification %@Andre Martins, Ramon Astudillo %t2012 %cICML %f/ICML/ICML-2012-439.pdf %*Black-box Optimization with a Politician %@Sebastien Bubeck, Yin Tat Lee %t2012 %cICML %f/ICML/ICML-2012-440.pdf %*Gaussian process nonparametric tensor estimator and its minimax optimality %@Heishiro Kanagawa, Taiji Suzuki, Hayato Kobayashi, Nobuyuki Shimizu, Yukihiro Tagami %t2012 %cICML %f/ICML/ICML-2012-441.pdf %*Gaussian process nonparametric tensor estimator and its minimax optimality %@Heishiro Kanagawa, Taiji Suzuki, Hayato Kobayashi, Nobuyuki Shimizu, Yukihiro Tagami %t2012 %cICML %f/ICML/ICML-2012-442.pdf %*No-Regret Algorithms for Heavy-Tailed Linear Bandits %@Andres Munoz Medina, Scott Yang %t2012 %cICML %f/ICML/ICML-2012-443.pdf %*Extended and Unscented Kitchen Sinks %@Edwin Bonilla, Daniel Steinberg, Alistair Reid %t2012 %cICML %f/ICML/ICML-2012-444.pdf %*Extended and Unscented Kitchen Sinks %@Edwin Bonilla, Daniel Steinberg, Alistair Reid %t2012 %cICML %f/ICML/ICML-2012-445.pdf %*Matrix Eigen-decomposition via Doubly Stochastic Riemannian Optimization %@Zhiqiang Xu, Peilin Zhao, Jianneng Cao, Xiaoli Li %t2012 %cICML %f/ICML/ICML-2012-446.pdf %*Matrix Eigen-decomposition via Doubly Stochastic Riemannian Optimization %@Zhiqiang Xu, Peilin Zhao, Jianneng Cao, Xiaoli Li %t2012 %cICML %f/ICML/ICML-2012-447.pdf %*Recommendations as Treatments: Debiasing Learning and Evaluation %@Tobias Schnabel, Adith Swaminathan, Ashudeep Singh, Navin Chandak, Thorsten Joachims %t2012 %cICML %f/ICML/ICML-2012-448.pdf %*Recommendations as Treatments: Debiasing Learning and Evaluation %@Tobias Schnabel, Adith Swaminathan, Ashudeep Singh, Navin Chandak, Thorsten Joachims %t2012 %cICML %f/ICML/ICML-2012-449.pdf %*ForecastICU: A Prognostic Decision Support System for Timely Prediction of Intensive Care Unit Admission %@Jinsung Yoon, Ahmed Alaa, Scott Hu, Mihaela van der Schaar %t2012 %cICML %f/ICML/ICML-2012-450.pdf %*ForecastICU: A Prognostic Decision Support System for Timely Prediction of Intensive Care Unit Admission %@Jinsung Yoon, Ahmed Alaa, Scott Hu, Mihaela van der Schaar %t2012 %cICML %f/ICML/ICML-2012-451.pdf %*An optimal algorithm for the Thresholding Bandit Problem %@Andrea Locatelli, Maurilio Gutzeit, Alexandra Carpentier %t2012 %cICML %f/ICML/ICML-2012-452.pdf %*An optimal algorithm for the Thresholding Bandit Problem %@Andrea Locatelli, Maurilio Gutzeit, Alexandra Carpentier %t2012 %cICML %f/ICML/ICML-2012-453.pdf %*Fast Parameter Inference in Nonlinear Dynamical Systems using Iterative Gradient Matching %@Mu Niu, Simon Rogers, Maurizio Filippone, Dirk Husmeier %t2012 %cICML %f/ICML/ICML-2012-454.pdf %*Structured and Efficient Variational Deep Learning with Matrix Gaussian Posteriors %@Christos Louizos, Max Welling %t2012 %cICML %f/ICML/ICML-2012-455.pdf %*Structured and Efficient Variational Deep Learning with Matrix Gaussian Posteriors %@Christos Louizos, Max Welling %t2012 %cICML %f/ICML/ICML-2012-456.pdf %*Learning Granger Causality for Hawkes Processes %@Hongteng Xu, Mehrdad Farajtabar, Hongyuan Zha %t2012 %cICML %f/ICML/ICML-2012-457.pdf %*Learning Granger Causality for Hawkes Processes %@Hongteng Xu, Mehrdad Farajtabar, Hongyuan Zha %t2012 %cICML %f/ICML/ICML-2012-458.pdf %*Neural Variational Inference for Text Processing %@Yishu Miao, Lei Yu, Phil Blunsom %t2012 %cICML %f/ICML/ICML-2012-459.pdf %*Neural Variational Inference for Text Processing %@Yishu Miao, Lei Yu, Phil Blunsom %t2012 %cICML %f/ICML/ICML-2012-460.pdf %*Dictionary Learning for Massive Matrix Factorization %@Arthur Mensch, Julien Mairal, Bertrand Thirion, Gael Varoquaux %t2012 %cICML %f/ICML/ICML-2012-461.pdf %*Pixel Recurrent Neural Networks %@Aaron Van den Oord, Nal Kalchbrenner, Koray Kavukcuoglu %t2012 %cICML %f/ICML/ICML-2012-462.pdf %*Why Most Decisions Are Easy in Tetris—And Perhaps in Other Sequential Decision Problems, As Well %@Ozgur Simsek, Simon Algorta, Amit Kothiyal %t2012 %cICML %f/ICML/ICML-2012-463.pdf %*Gaussian quadrature for matrix inverse forms with applications %@Chengtao Li, Suvrit Sra, Stefanie Jegelka %t2012 %cICML %f/ICML/ICML-2012-464.pdf %*Gaussian quadrature for matrix inverse forms with applications %@Chengtao Li, Suvrit Sra, Stefanie Jegelka %t2012 %cICML %f/ICML/ICML-2012-465.pdf %*Train and Test Tightness of LP Relaxations in Structured Prediction %@Ofer Meshi, Mehrdad Mahdavi, Adrian Weller, David Sontag %t2012 %cICML %f/ICML/ICML-2012-466.pdf %*Train and Test Tightness of LP Relaxations in Structured Prediction %@Ofer Meshi, Mehrdad Mahdavi, Adrian Weller, David Sontag %t2012 %cICML %f/ICML/ICML-2012-467.pdf %*Stochastic Optimization for Multiview Representation Learning using Partial Least Squares %@Raman Arora, Poorya Mianjy, Teodor Marinov %t2012 %cICML %f/ICML/ICML-2012-468.pdf %*Stochastic Optimization for Multiview Representation Learning using Partial Least Squares %@Raman Arora, Poorya Mianjy, Teodor Marinov %t2012 %cICML %f/ICML/ICML-2012-469.pdf %*Hierarchical Compound Poisson Factorization %@Mehmet Basbug, Barbara Engelhardt %t2012 %cICML %f/ICML/ICML-2012-470.pdf %*Hierarchical Compound Poisson Factorization %@Mehmet Basbug, Barbara Engelhardt %t2012 %cICML %f/ICML/ICML-2012-471.pdf %*Opponent Modeling in Deep Reinforcement Learning %@He He, Jordan Boyd-Graber, Kevin Kwok, Hal Daumé III %t2012 %cICML %f/ICML/ICML-2012-472.pdf %*No penalty no tears: Least squares in high-dimensional linear models %@Xiangyu Wang, David Dunson, Chenlei Leng %t2012 %cICML %f/ICML/ICML-2012-473.pdf %*No penalty no tears: Least squares in high-dimensional linear models %@Xiangyu Wang, David Dunson, Chenlei Leng %t2012 %cICML %f/ICML/ICML-2012-474.pdf %*SDNA: Stochastic Dual Newton Ascent for Empirical Risk Minimization %@Zheng Qu, Peter Richtarik, Martin Takac, Olivier Fercoq %t2012 %cICML %f/ICML/ICML-2012-475.pdf %*SDNA: Stochastic Dual Newton Ascent for Empirical Risk Minimization %@Zheng Qu, Peter Richtarik, Martin Takac, Olivier Fercoq %t2012 %cICML %f/ICML/ICML-2012-476.pdf %*On Graduated Optimization for Stochastic Non-Convex Problems %@Elad Hazan, Kfir Yehuda Levy, Shai Shalev-Shwartz %t2012 %cICML %f/ICML/ICML-2012-477.pdf %*On Graduated Optimization for Stochastic Non-Convex Problems %@Elad Hazan, Kfir Yehuda Levy, Shai Shalev-Shwartz %t2012 %cICML %f/ICML/ICML-2012-478.pdf %*Meta-Learning with Memory-Augmented Neural Networks %@Adam Santoro, Sergey Bartunov, Matthew Botvinick, Daan Wierstra, Timothy Lillicrap %t2012 %cICML %f/ICML/ICML-2012-479.pdf %*Meta-Learning with Memory-Augmented Neural Networks %@Adam Santoro, Sergey Bartunov, Matthew Botvinick, Daan Wierstra, Timothy Lillicrap %t2012 %cICML %f/ICML/ICML-2012-480.pdf %*The knockoff filter for FDR control in group-sparse and multitask regression %@Ran Dai, Rina Barber %t2012 %cICML %f/ICML/ICML-2012-481.pdf %*Softened Approximate Policy Iteration for Markov Games %@Julien Pérolat, Bilal Piot, Matthieu Geist, Bruno Scherrer, Olivier Pietquin %t2012 %cICML %f/ICML/ICML-2012-482.pdf %*Softened Approximate Policy Iteration for Markov Games %@Julien Pérolat, Bilal Piot, Matthieu Geist, Bruno Scherrer, Olivier Pietquin %t2012 %cICML %f/ICML/ICML-2012-483.pdf %*Stochastic Block BFGS: Squeezing More Curvature out of Data %@Robert Gower, Donald Goldfarb, Peter Richtarik %t2012 %cICML %f/ICML/ICML-2012-484.pdf %*Differential Geometric Regularization for Supervised Learning of Classifiers %@Qinxun Bai, Steven Rosenberg, Zheng Wu, Stan Sclaroff %t2012 %cICML %f/ICML/ICML-2012-485.pdf %*Differential Geometric Regularization for Supervised Learning of Classifiers %@Qinxun Bai, Steven Rosenberg, Zheng Wu, Stan Sclaroff %t2012 %cICML %f/ICML/ICML-2012-486.pdf %*Exploiting Cyclic Symmetry in Convolutional Neural Networks %@Sander Dieleman, Jeffrey De Fauw, Koray Kavukcuoglu %t2012 %cICML %f/ICML/ICML-2012-487.pdf %*Graying the black box: Understanding DQNs %@Tom Zahavy, Nir Ben-Zrihem, Shie Mannor %t2012 %cICML %f/ICML/ICML-2012-488.pdf %*Graying the black box: Understanding DQNs %@Tom Zahavy, Nir Ben-Zrihem, Shie Mannor %t2012 %cICML %f/ICML/ICML-2012-489.pdf %*The Sum-Product Theorem: A Foundation for Learning Tractable Models %@Abram Friesen, Pedro Domingos %t2012 %cICML %f/ICML/ICML-2012-490.pdf %*The Sum-Product Theorem: A Foundation for Learning Tractable Models %@Abram Friesen, Pedro Domingos %t2012 %cICML %f/ICML/ICML-2012-491.pdf %*Pareto Frontier Learning with Expensive Correlated Objectives %@Amar Shah, Zoubin Ghahramani %t2012 %cICML %f/ICML/ICML-2012-492.pdf %*Pareto Frontier Learning with Expensive Correlated Objectives %@Amar Shah, Zoubin Ghahramani %t2012 %cICML %f/ICML/ICML-2012-493.pdf %*Asynchronous Methods for Deep Reinforcement Learning %@Volodymyr Mnih, Adria Puigdomenech Badia, Mehdi Mirza, Alex Graves, Timothy Lillicrap, Tim Harley, David Silver, Koray Kavukcuoglu %t2012 %cICML %f/ICML/ICML-2012-494.pdf %*Asynchronous Methods for Deep Reinforcement Learning %@Volodymyr Mnih, Adria Puigdomenech Badia, Mehdi Mirza, Alex Graves, Timothy Lillicrap, Tim Harley, David Silver, Koray Kavukcuoglu %t2012 %cICML %f/ICML/ICML-2012-495.pdf %*A Simple and Strongly-Local Flow-Based Method for Cut Improvement %@Nate Veldt, David Gleich, Michael Mahoney %t2012 %cICML %f/ICML/ICML-2012-496.pdf %*A Simple and Strongly-Local Flow-Based Method for Cut Improvement %@Nate Veldt, David Gleich, Michael Mahoney %t2012 %cICML %f/ICML/ICML-2012-497.pdf %*Nonlinear Statistical Learning with Truncated Gaussian Graphical Models %@Qinliang Su, Xuejun Liao, Changyou Chen, Lawrence Carin %t2012 %cICML %f/ICML/ICML-2012-498.pdf %*Nonlinear Statistical Learning with Truncated Gaussian Graphical Models %@Qinliang Su, Xuejun Liao, Changyou Chen, Lawrence Carin %t2012 %cICML %f/ICML/ICML-2012-499.pdf %*Barron and Cover’s Theory in Supervised Learning and its Application to Lasso %@Masanori Kawakita, Jun’ichi Takeuchi %t2012 %cICML %f/ICML/ICML-2012-500.pdf %*Barron and Cover’s Theory in Supervised Learning and its Application to Lasso %@Masanori Kawakita, Jun’ichi Takeuchi %t2012 %cICML %f/ICML/ICML-2012-501.pdf %*Nonparametric Canonical Correlation Analysis %@Tomer Michaeli, Weiran Wang, Karen Livescu %t2012 %cICML %f/ICML/ICML-2012-502.pdf %*Nonparametric Canonical Correlation Analysis %@Tomer Michaeli, Weiran Wang, Karen Livescu %t2012 %cICML %f/ICML/ICML-2012-503.pdf %*BISTRO: An Efficient Relaxation-Based Method for Contextual Bandits %@Alexander Rakhlin, Karthik Sridharan %t2012 %cICML %f/ICML/ICML-2012-504.pdf %*BISTRO: An Efficient Relaxation-Based Method for Contextual Bandits %@Alexander Rakhlin, Karthik Sridharan %t2012 %cICML %f/ICML/ICML-2012-505.pdf %*Associative Long Short-Term Memory %@Ivo Danihelka, Greg Wayne, Benigno Uria, Nal Kalchbrenner, Alex Graves %t2012 %cICML %f/ICML/ICML-2012-506.pdf %*Associative Long Short-Term Memory %@Ivo Danihelka, Greg Wayne, Benigno Uria, Nal Kalchbrenner, Alex Graves %t2012 %cICML %f/ICML/ICML-2012-507.pdf %*Dueling Network Architectures for Deep Reinforcement Learning %@Ziyu Wang, Tom Schaul, Matteo Hessel, Hado van Hasselt, Marc Lanctot, Nando de Freitas %t2012 %cICML %f/ICML/ICML-2012-508.pdf %*Persistence weighted Gaussian kernel for topological data analysis %@Genki Kusano, Yasuaki Hiraoka, Kenji Fukumizu %t2012 %cICML %f/ICML/ICML-2012-509.pdf %*Learning Convolutional Neural Networks for Graphs %@Mathias Niepert, Mohamed Ahmed, Konstantin Kutzkov %t2012 %cICML %f/ICML/ICML-2012-510.pdf %*Persistent RNNs: Stashing Recurrent Weights On-Chip %@Greg Diamos, Shubho Sengupta, Bryan Catanzaro, Mike Chrzanowski, Adam Coates, Erich Elsen, Jesse Engel, Awni Hannun, Sanjeev Satheesh %t2012 %cICML %f/ICML/ICML-2012-511.pdf %*Recurrent Orthogonal Networks and Long-Memory Tasks %@Mikael Henaff, Arthur Szlam, Yann LeCun %t2012 %cICML %f/ICML/ICML-2012-512.pdf %*The Arrow of Time in Multivariate Time Series %@Stefan Bauer, Bernhard Schölkopf, Jonas Peters %t2012 %cICML %f/ICML/ICML-2012-513.pdf %*Mixture Proportion Estimation via Kernel Embeddings of Distributions %@Harish Ramaswamy, Clayton Scott, Ambuj Tewari %t2012 %cICML %f/ICML/ICML-2012-514.pdf %*Mixture Proportion Estimation via Kernel Embeddings of Distributions %@Harish Ramaswamy, Clayton Scott, Ambuj Tewari %t2012 %cICML %f/ICML/ICML-2012-515.pdf %*Fast DPP Sampling for Nystrom with Application to Kernel Methods %@Chengtao Li, Stefanie Jegelka, Suvrit Sra %t2012 %cICML %f/ICML/ICML-2012-516.pdf %*Fast DPP Sampling for Nystrom with Application to Kernel Methods %@Chengtao Li, Stefanie Jegelka, Suvrit Sra %t2012 %cICML %f/ICML/ICML-2012-517.pdf %*Complex Embeddings for Simple Link Prediction %@Théo Trouillon, Johannes Welbl, Sebastian Riedel, Eric Gaussier, Guillaume Bouchard %t2012 %cICML %f/ICML/ICML-2012-518.pdf %*Complex Embeddings for Simple Link Prediction %@Théo Trouillon, Johannes Welbl, Sebastian Riedel, Eric Gaussier, Guillaume Bouchard %t2012 %cICML %f/ICML/ICML-2012-519.pdf %*Interactive Bayesian Hierarchical Clustering %@Sharad Vikram, Sanjoy Dasgupta %t2012 %cICML %f/ICML/ICML-2012-520.pdf %*A Convolutional Attention Network for Extreme Summarization of Source Code %@Miltiadis Allamanis, Hao Peng, Charles Sutton %t2012 %cICML %f/ICML/ICML-2012-521.pdf %*How to Fake Multiply by a Gaussian Matrix %@Michael Kapralov, Vamsi Potluru, David Woodruff %t2012 %cICML %f/ICML/ICML-2012-522.pdf %*How to Fake Multiply by a Gaussian Matrix %@Michael Kapralov, Vamsi Potluru, David Woodruff %t2012 %cICML %f/ICML/ICML-2012-523.pdf %*Differentially Private Chi-Squared Hypothesis Testing: Goodness of Fit and Independence Testing %@Ryan Rogers, Salil Vadhan, Hyun Lim, Marco Gaboardi %t2012 %cICML %f/ICML/ICML-2012-524.pdf %*Differentially Private Chi-Squared Hypothesis Testing: Goodness of Fit and Independence Testing %@Ryan Rogers, Salil Vadhan, Hyun Lim, Marco Gaboardi %t2012 %cICML %f/ICML/ICML-2012-525.pdf %*Pliable Rejection Sampling %@Akram Erraqabi, Michal Valko, Alexandra Carpentier, Odalric Maillard %t2012 %cICML %f/ICML/ICML-2012-526.pdf %*Pliable Rejection Sampling %@Akram Erraqabi, Michal Valko, Alexandra Carpentier, Odalric Maillard %t2012 %cICML %f/ICML/ICML-2012-527.pdf %*Differentially Private Policy Evaluation %@Borja Balle, Maziar Gomrokchi, Doina Precup %t2012 %cICML %f/ICML/ICML-2012-528.pdf %*Differentially Private Policy Evaluation %@Borja Balle, Maziar Gomrokchi, Doina Precup %t2012 %cICML %f/ICML/ICML-2012-529.pdf %*Data-Efficient Off-Policy Policy Evaluation for Reinforcement Learning %@Philip Thomas, Emma Brunskill %t2012 %cICML %f/ICML/ICML-2012-530.pdf %*Discrete Deep Feature Extraction: A Theory and New Architectures %@Thomas Wiatowski, Michael Tschannen, Aleksandar Stanic, Philipp Grohs, Helmut Boelcskei %t2012 %cICML %f/ICML/ICML-2012-531.pdf %*Discrete Deep Feature Extraction: A Theory and New Architectures %@Thomas Wiatowski, Michael Tschannen, Aleksandar Stanic, Philipp Grohs, Helmut Boelcskei %t2012 %cICML %f/ICML/ICML-2012-532.pdf %*Efficient Algorithms for Adversarial Contextual Learning %@Vasilis Syrgkanis, Akshay Krishnamurthy, Robert Schapire %t2012 %cICML %f/ICML/ICML-2012-533.pdf %*Efficient Algorithms for Adversarial Contextual Learning %@Vasilis Syrgkanis, Akshay Krishnamurthy, Robert Schapire %t2012 %cICML %f/ICML/ICML-2012-534.pdf %*Training Deep Neural Networks via Direct Loss Minimization %@Yang Song, Alexander Schwing, Richard, Raquel Urtasun %t2012 %cICML %f/ICML/ICML-2012-535.pdf %*Training Deep Neural Networks via Direct Loss Minimization %@Yang Song, Alexander Schwing, Richard, Raquel Urtasun %t2012 %cICML %f/ICML/ICML-2012-536.pdf %*Sequence to Sequence Training of CTC-RNNs with Partial Windowing %@Kyuyeon Hwang, Wonyong Sung %t2012 %cICML %f/ICML/ICML-2012-537.pdf %*Sequence to Sequence Training of CTC-RNNs with Partial Windowing %@Kyuyeon Hwang, Wonyong Sung %t2012 %cICML %f/ICML/ICML-2012-538.pdf %*Variational Inference for Monte Carlo Objectives %@Andriy Mnih, Danilo Rezende %t2012 %cICML %f/ICML/ICML-2012-539.pdf %*Variational Inference for Monte Carlo Objectives %@Andriy Mnih, Danilo Rezende %t2012 %cICML %f/ICML/ICML-2012-540.pdf %*Hierarchical Decision Making In Electricity Grid Management %@Gal Dalal, Elad Gilboa, Shie Mannor %t2012 %cICML %f/ICML/ICML-2012-541.pdf %*Learning Sparse Combinatorial Representations via Two-stage Submodular Maximization %@Eric Balkanski, Baharan Mirzasoleiman, Andreas Krause, Yaron Singer %t2012 %cICML %f/ICML/ICML-2012-542.pdf %*Learning Sparse Combinatorial Representations via Two-stage Submodular Maximization %@Eric Balkanski, Baharan Mirzasoleiman, Andreas Krause, Yaron Singer %t2012 %cICML %f/ICML/ICML-2012-543.pdf %*Understanding and Improving Convolutional Neural Networks via Concatenated Rectified Linear Units %@Wenling Shang, Kihyuk Sohn, Diogo Almeida, Honglak Lee %t2012 %cICML %f/ICML/ICML-2012-544.pdf %*Isotonic Hawkes Processes %@Yichen Wang, Bo Xie, Nan Du, Le Song %t2012 %cICML %f/ICML/ICML-2012-545.pdf %*Isotonic Hawkes Processes %@Yichen Wang, Bo Xie, Nan Du, Le Song %t2012 %cICML %f/ICML/ICML-2012-546.pdf %*Cross-Graph Learning of Multi-Relational Associations %@Hanxiao Liu, Yiming Yang %t2012 %cICML %f/ICML/ICML-2012-547.pdf %*Markov-modulated Marked Poisson Processes for Check-in Data %@Jiangwei Pan, Vinayak Rao, Pankaj Agarwal, Alan Gelfand %t2012 %cICML %f/ICML/ICML-2012-548.pdf %*Beyond Parity Constraints: Fourier Analysis of Hash Functions for Inference %@Tudor Achim, Ashish Sabharwal, Stefano Ermon %t2012 %cICML %f/ICML/ICML-2012-549.pdf %*Beyond Parity Constraints: Fourier Analysis of Hash Functions for Inference %@Tudor Achim, Ashish Sabharwal, Stefano Ermon %t2012 %cICML %f/ICML/ICML-2012-550.pdf %*On the Power and Limits of Distance-Based Learning %@Periklis Papakonstantinou, Jia Xu, Guang Yang %t2012 %cICML %f/ICML/ICML-2012-551.pdf %*On the Power and Limits of Distance-Based Learning %@Periklis Papakonstantinou, Jia Xu, Guang Yang %t2012 %cICML %f/ICML/ICML-2012-552.pdf %*A Convex Atomic-Norm Approach to Multiple Sequence Alignment and Motif Discovery %@Ian En-Hsu Yen, Xin Lin, Jiong Zhang, Pradeep Ravikumar, Inderjit Dhillon %t2012 %cICML %f/ICML/ICML-2012-553.pdf %*A Convex Atomic-Norm Approach to Multiple Sequence Alignment and Motif Discovery %@Ian En-Hsu Yen, Xin Lin, Jiong Zhang, Pradeep Ravikumar, Inderjit Dhillon %t2012 %cICML %f/ICML/ICML-2012-554.pdf %*Generalized Direct Change Estimation in Ising Model Structure %@Farideh Fazayeli, Arindam Banerjee %t2012 %cICML %f/ICML/ICML-2012-555.pdf %*Robust Principal Component Analysis with Side Information %@Kai-Yang Chiang, Cho-Jui Hsieh, Inderjit Dhillon %t2012 %cICML %f/ICML/ICML-2012-556.pdf %*Robust Principal Component Analysis with Side Information %@Kai-Yang Chiang, Cho-Jui Hsieh, Inderjit Dhillon %t2012 %cICML %f/ICML/ICML-2012-557.pdf %*Towards Faster Rates and Oracle Property for Low-Rank Matrix Estimation %@Huan Gui, Jiawei Han, Quanquan Gu %t2012 %cICML %f/ICML/ICML-2012-558.pdf %*Towards Faster Rates and Oracle Property for Low-Rank Matrix Estimation %@Huan Gui, Jiawei Han, Quanquan Gu %t2012 %cICML %f/ICML/ICML-2012-559.pdf %*Early and Reliable Event Detection Using Proximity Space Representation %@Maxime Sangnier, Jerome Gauthier, Alain Rakotomamonjy %t2012 %cICML %f/ICML/ICML-2012-560.pdf %*Stratified Sampling Meets Machine Learning %@Edo Liberty, Kevin Lang, Konstantin Shmakov %t2012 %cICML %f/ICML/ICML-2012-561.pdf %*Efficient Multi-Instance Learning for Activity Recognition from Time Series Data Using an Auto-Regressive Hidden Markov Model %@Xinze Guan, Raviv Raich, Weng-Keen Wong %t2012 %cICML %f/ICML/ICML-2012-562.pdf %*Efficient Multi-Instance Learning for Activity Recognition from Time Series Data Using an Auto-Regressive Hidden Markov Model %@Xinze Guan, Raviv Raich, Weng-Keen Wong %t2012 %cICML %f/ICML/ICML-2012-563.pdf %*Generalization Properties and Implicit Regularization for Multiple Passes SGM %@Junhong Lin, Raffaello Camoriano, Lorenzo Rosasco %t2012 %cICML %f/ICML/ICML-2012-564.pdf %*Generalization Properties and Implicit Regularization for Multiple Passes SGM %@Junhong Lin, Raffaello Camoriano, Lorenzo Rosasco %t2012 %cICML %f/ICML/ICML-2012-565.pdf %*Principal Component Projection Without Principal Component Analysis %@Roy Frostig, Cameron Musco, Christopher Musco, Aaron Sidford %t2012 %cICML %f/ICML/ICML-2012-566.pdf %*Recovery guarantee of weighted low-rank approximation via alternating minimization %@Yuanzhi Li, Yingyu Liang, Andrej Risteski %t2012 %cICML %f/ICML/ICML-2012-567.pdf %*Recovery guarantee of weighted low-rank approximation via alternating minimization %@Yuanzhi Li, Yingyu Liang, Andrej Risteski %t2012 %cICML %f/ICML/ICML-2012-568.pdf %*Deconstructing the Ladder Network Architecture %@Mohammad Pezeshki, Linxi Fan, Philemon Brakel, Aaron Courville, Yoshua Bengio %t2012 %cICML %f/ICML/ICML-2012-569.pdf %*Deconstructing the Ladder Network Architecture %@Mohammad Pezeshki, Linxi Fan, Philemon Brakel, Aaron Courville, Yoshua Bengio %t2012 %cICML %f/ICML/ICML-2012-570.pdf %*Generalization and Exploration via Randomized Value Functions %@Ian Osband, Benjamin Van Roy, Zheng Wen %t2012 %cICML %f/ICML/ICML-2012-571.pdf %*Generalization and Exploration via Randomized Value Functions %@Ian Osband, Benjamin Van Roy, Zheng Wen %t2012 %cICML %f/ICML/ICML-2012-572.pdf %*Evasion and Hardening of Tree Ensemble Classifiers %@Alex Kantchelian, J. D. Tygar, Anthony Joseph %t2012 %cICML %f/ICML/ICML-2012-573.pdf %*Evasion and Hardening of Tree Ensemble Classifiers %@Alex Kantchelian, J. D. Tygar, Anthony Joseph %t2012 %cICML %f/ICML/ICML-2012-574.pdf %*Dynamic Memory Networks for Visual and Textual Question Answering %@Caiming Xiong, Stephen Merity, Richard Socher %t2012 %cICML %f/ICML/ICML-2012-575.pdf %*Estimating Cosmological Parameters from the Dark Matter Distribution %@Siamak Ravanbakhsh, Junier Oliva, Sebastian Fromenteau, Layne Price, Shirley Ho, Jeff Schneider, Barnabas Poczos %t2012 %cICML %f/ICML/ICML-2012-576.pdf %*Estimating Cosmological Parameters from the Dark Matter Distribution %@Siamak Ravanbakhsh, Junier Oliva, Sebastian Fromenteau, Layne Price, Shirley Ho, Jeff Schneider, Barnabas Poczos %t2012 %cICML %f/ICML/ICML-2012-577.pdf %*Learning Population-Level Diffusions with Generative RNNs %@Tatsunori Hashimoto, David Gifford, Tommi Jaakkola %t2012 %cICML %f/ICML/ICML-2012-578.pdf %*Expressiveness of Rectifier Networks %@Xingyuan Pan, Vivek Srikumar %t2012 %cICML %f/ICML/ICML-2012-579.pdf %*Expressiveness of Rectifier Networks %@Xingyuan Pan, Vivek Srikumar %t2012 %cICML %f/ICML/ICML-2012-580.pdf %*Discrete Distribution Estimation under Local Privacy %@Peter Kairouz, Keith Bonawitz, Daniel Ramage %t2012 %cICML %f/ICML/ICML-2012-581.pdf %*Discrete Distribution Estimation under Local Privacy %@Peter Kairouz, Keith Bonawitz, Daniel Ramage %t2012 %cICML %f/ICML/ICML-2012-582.pdf %*Square Root Graphical Models: Multivariate Generalizations of Univariate Exponential Families that Permit Positive Dependencies %@David Inouye, Pradeep Ravikumar, Inderjit Dhillon %t2012 %cICML %f/ICML/ICML-2012-583.pdf %*Square Root Graphical Models: Multivariate Generalizations of Univariate Exponential Families that Permit Positive Dependencies %@David Inouye, Pradeep Ravikumar, Inderjit Dhillon %t2012 %cICML %f/ICML/ICML-2012-584.pdf %*A Box-Constrained Approach for Hard Permutation Problems %@Cong Han Lim, Steve Wright %t2012 %cICML %f/ICML/ICML-2012-585.pdf %*A Box-Constrained Approach for Hard Permutation Problems %@Cong Han Lim, Steve Wright %t2012 %cICML %f/ICML/ICML-2012-586.pdf %*Geometric Mean Metric Learning %@Pourya Zadeh, Reshad Hosseini, Suvrit Sra %t2012 %cICML %f/ICML/ICML-2012-587.pdf %*Sparse Nonlinear Regression: Parameter Estimation under Nonconvexity %@Zhuoran Yang, Zhaoran Wang, Han Liu, Yonina Eldar, Tong Zhang %t2012 %cICML %f/ICML/ICML-2012-588.pdf %*Conditional Bernoulli Mixtures for Multi-label Classification %@Cheng Li, Bingyu Wang, Virgil Pavlu, Javed Aslam %t2012 %cICML %f/ICML/ICML-2012-589.pdf %*Conditional Bernoulli Mixtures for Multi-label Classification %@Cheng Li, Bingyu Wang, Virgil Pavlu, Javed Aslam %t2012 %cICML %f/ICML/ICML-2012-590.pdf %*Scalable Discrete Sampling as a Multi-Armed Bandit Problem %@Yutian Chen, Zoubin Ghahramani %t2012 %cICML %f/ICML/ICML-2012-591.pdf %*Scalable Discrete Sampling as a Multi-Armed Bandit Problem %@Yutian Chen, Zoubin Ghahramani %t2012 %cICML %f/ICML/ICML-2012-592.pdf %*Recycling Randomness with Structure for Sublinear time Kernel Expansions %@Krzysztof Choromanski, Vikas Sindhwani %t2012 %cICML %f/ICML/ICML-2012-593.pdf %*Recycling Randomness with Structure for Sublinear time Kernel Expansions %@Krzysztof Choromanski, Vikas Sindhwani %t2012 %cICML %f/ICML/ICML-2012-594.pdf %*Bidirectional Helmholtz Machines %@Jorg Bornschein, Samira Shabanian, Asja Fischer, Yoshua Bengio %t2012 %cICML %f/ICML/ICML-2012-595.pdf %*Faster Convex Optimization: Simulated Annealing with an Efficient Universal Barrier %@Jacob Abernethy, Elad Hazan %t2012 %cICML %f/ICML/ICML-2012-596.pdf %*Faster Convex Optimization: Simulated Annealing with an Efficient Universal Barrier %@Jacob Abernethy, Elad Hazan %t2012 %cICML %f/ICML/ICML-2012-597.pdf %*Preconditioning Kernel Matrices %@Kurt Cutajar, Michael Osborne, John Cunningham, Maurizio Filippone %t2012 %cICML %f/ICML/ICML-2012-598.pdf %*Preconditioning Kernel Matrices %@Kurt Cutajar, Michael Osborne, John Cunningham, Maurizio Filippone %t2012 %cICML %f/ICML/ICML-2012-599.pdf %*Greedy Column Subset Selection: New Bounds and Distributed Algorithms %@Jason Altschuler, Aditya Bhaskara, Gang Fu, Vahab Mirrokni, Afshin Rostamizadeh, Morteza Zadimoghaddam %t2012 %cICML %f/ICML/ICML-2012-600.pdf %*Greedy Column Subset Selection: New Bounds and Distributed Algorithms %@Jason Altschuler, Aditya Bhaskara, Gang Fu, Vahab Mirrokni, Afshin Rostamizadeh, Morteza Zadimoghaddam %t2012 %cICML %f/ICML/ICML-2012-601.pdf %*Dynamic Capacity Networks %@Amjad Almahairi, Nicolas Ballas, Tim Cooijmans, Yin Zheng, Hugo Larochelle, Aaron Courville %t2012 %cICML %f/ICML/ICML-2012-602.pdf %*Pricing a Low-regret Seller %@Hoda Heidari, Mohammad Mahdian, Umar Syed, Sergei Vassilvitskii, Sadra Yazdanbod %t2012 %cICML %f/ICML/ICML-2012-603.pdf %*Estimation from Indirect Supervision with Linear Moments %@Aditi Raghunathan, Roy Frostig, John Duchi, Percy Liang %t2012 %cICML %f/ICML/ICML-2012-604.pdf %*Estimation from Indirect Supervision with Linear Moments %@Aditi Raghunathan, Roy Frostig, John Duchi, Percy Liang %t2012 %cICML %f/ICML/ICML-2012-605.pdf %*Speeding up k-means by approximating Euclidean distances via block vectors %@Thomas Bottesch, Thomas Bühler, Markus Kächele %t2012 %cICML %f/ICML/ICML-2012-606.pdf %*Learning and Inference via Maximum Inner Product Search %@Stephen Mussmann, Stefano Ermon %t2012 %cICML %f/ICML/ICML-2012-607.pdf %*Learning and Inference via Maximum Inner Product Search %@Stephen Mussmann, Stefano Ermon %t2012 %cICML %f/ICML/ICML-2012-608.pdf %*A Superlinearly-Convergent Proximal Newton-type Method for the Optimization of Finite Sums %@Anton Rodomanov, Dmitry Kropotov %t2012 %cICML %f/ICML/ICML-2012-609.pdf %*A Superlinearly-Convergent Proximal Newton-type Method for the Optimization of Finite Sums %@Anton Rodomanov, Dmitry Kropotov %t2012 %cICML %f/ICML/ICML-2012-610.pdf %*A Kernel Test of Goodness of Fit %@Kacper Chwialkowski, Heiko Strathmann, Arthur Gretton %t2012 %cICML %f/ICML/ICML-2012-611.pdf %*A Kernel Test of Goodness of Fit %@Kacper Chwialkowski, Heiko Strathmann, Arthur Gretton %t2012 %cICML %f/ICML/ICML-2012-612.pdf %*Interacting Particle Markov Chain Monte Carlo %@Tom Rainforth, Christian Naesseth, Fredrik Lindsten, Brooks Paige, Jan-Willem Vandemeent, Arnaud Doucet, Frank Wood %t2012 %cICML %f/ICML/ICML-2012-613.pdf %*Interacting Particle Markov Chain Monte Carlo %@Tom Rainforth, Christian Naesseth, Fredrik Lindsten, Brooks Paige, Jan-Willem Vandemeent, Arnaud Doucet, Frank Wood %t2012 %cICML %f/ICML/ICML-2012-614.pdf %*Faster Eigenvector Computation via Shift-and-Invert Preconditioning %@Dan Garber, Elad Hazan, Chi Jin, Sham, Cameron Musco, Praneeth Netrapalli, Aaron Sidford %t2012 %cICML %f/ICML/ICML-2012-615.pdf %*A Theory of Generative ConvNet %@Jianwen Xie, Yang Lu, Song-Chun Zhu, Yingnian Wu %t2012 %cICML %f/ICML/ICML-2012-616.pdf %*Efficient Learning with a Family of Nonconvex Regularizers by Redistributing Nonconvexity %@Quanming Yao, James Kwok %t2012 %cICML %f/ICML/ICML-2012-617.pdf %*Computationally Efficient Nyström Approximation using Fast Transforms %@Si Si, Cho-Jui Hsieh, Inderjit Dhillon %t2012 %cICML %f/ICML/ICML-2012-618.pdf %*Computationally Efficient Nyström Approximation using Fast Transforms %@Si Si, Cho-Jui Hsieh, Inderjit Dhillon %t2012 %cICML %f/ICML/ICML-2012-619.pdf %*Gromov-Wasserstein Averaging of Kernel and Distance Matrices %@Gabriel Peyré, Marco Cuturi, Justin Solomon %t2012 %cICML %f/ICML/ICML-2012-620.pdf %*Robust Monte Carlo Sampling using Riemannian Nosé-Poincaré Hamiltonian Dynamics %@Anirban Roychowdhury, Brian Kulis, Srinivasan Parthasarathy %t2012 %cICML %f/ICML/ICML-2012-621.pdf %*Robust Monte Carlo Sampling using Riemannian Nosé-Poincaré Hamiltonian Dynamics %@Anirban Roychowdhury, Brian Kulis, Srinivasan Parthasarathy %t2012 %cICML %f/ICML/ICML-2012-622.pdf %*The Segmented iHMM: A Simple, Efficient Hierarchical Infinite HMM %@Ardavan Saeedi, Matthew Hoffman, Matthew Johnson, Ryan Adams %t2012 %cICML %f/ICML/ICML-2012-623.pdf %*The Segmented iHMM: A Simple, Efficient Hierarchical Infinite HMM %@Ardavan Saeedi, Matthew Hoffman, Matthew Johnson, Ryan Adams %t2012 %cICML %f/ICML/ICML-2012-624.pdf %*Meta–Gradient Boosted Decision Tree Model for Weight and Target Learning %@Yury Ustinovskiy, Valentina Fedorova, Gleb Gusev, Pavel Serdyukov %t2012 %cICML %f/ICML/ICML-2012-625.pdf %*Discriminative Embeddings of Latent Variable Models for Structured Data %@Hanjun Dai, Bo Dai, Le Song %t2012 %cICML %f/ICML/ICML-2012-626.pdf %*Discriminative Embeddings of Latent Variable Models for Structured Data %@Hanjun Dai, Bo Dai, Le Song %t2012 %cICML %f/ICML/ICML-2012-627.pdf %*Robust Random Cut Forest Based Anomaly Detection on Streams %@Sudipto Guha, Nina Mishra, Gourav Roy, Okke Schrijvers %t2012 %cICML %f/ICML/ICML-2012-628.pdf %*Robust Random Cut Forest Based Anomaly Detection on Streams %@Sudipto Guha, Nina Mishra, Gourav Roy, Okke Schrijvers %t2012 %cICML %f/ICML/ICML-2012-629.pdf %*Training Neural Networks Without Gradients: A Scalable ADMM Approach %@Gavin Taylor, Ryan Burmeister, Zheng Xu, Bharat Singh, Ankit Patel, Tom Goldstein %t2012 %cICML %f/ICML/ICML-2012-630.pdf %*Clustering High Dimensional Categorical Data via Topographical Features %@Chao Chen, Novi Quadrianto %t2012 %cICML %f/ICML/ICML-2012-631.pdf %*Efficient Algorithms for Large-scale Generalized Eigenvector Computation and Canonical Correlation Analysis %@Rong Ge, Chi Jin, Sham, Praneeth Netrapalli, Aaron Sidford %t2012 %cICML %f/ICML/ICML-2012-632.pdf %*Efficient Algorithms for Large-scale Generalized Eigenvector Computation and Canonical Correlation Analysis %@Rong Ge, Chi Jin, Sham, Praneeth Netrapalli, Aaron Sidford %t2012 %cICML %f/ICML/ICML-2012-633.pdf %*Algorithms for Optimizing the Ratio of Submodular Functions %@Wenruo Bai, Rishabh Iyer, Kai Wei, Jeff Bilmes %t2012 %cICML %f/ICML/ICML-2012-634.pdf %*Model-Free Imitation Learning with Policy Optimization %@Jonathan Ho, Jayesh Gupta, Stefano Ermon %t2012 %cICML %f/ICML/ICML-2012-635.pdf %*Model-Free Imitation Learning with Policy Optimization %@Jonathan Ho, Jayesh Gupta, Stefano Ermon %t2012 %cICML %f/ICML/ICML-2012-636.pdf %*ADIOS: Architectures Deep In Output Space %@Moustapha Cisse, Maruan Al-Shedivat, Samy Bengio %t2012 %cICML %f/ICML/ICML-2012-637.pdf %*Conditional Dependence via Shannon Capacity: Axioms, Estimators and Applications %@Weihao Gao, Sreeram Kannan, Sewoong Oh, Pramod Viswanath %t2012 %cICML %f/ICML/ICML-2012-638.pdf %*Control of Memory, Active Perception, and Action in Minecraft %@Junhyuk Oh, Valliappa Chockalingam, Satinder, Honglak Lee %t2012 %cICML %f/ICML/ICML-2012-639.pdf %*Control of Memory, Active Perception, and Action in Minecraft %@Junhyuk Oh, Valliappa Chockalingam, Satinder, Honglak Lee %t2012 %cICML %f/ICML/ICML-2012-640.pdf %*The Label Complexity of Mixed-Initiative Classifier Training %@Jina Suh, Xiaojin Zhu, Saleema Amershi %t2012 %cICML %f/ICML/ICML-2012-641.pdf %*Bayesian Poisson Tucker Decomposition for Learning the Structure of International Relations %@Aaron Schein, Mingyuan Zhou, David Blei, Hanna Wallach %t2012 %cICML %f/ICML/ICML-2012-642.pdf %*Bayesian Poisson Tucker Decomposition for Learning the Structure of International Relations %@Aaron Schein, Mingyuan Zhou, David Blei, Hanna Wallach %t2012 %cICML %f/ICML/ICML-2012-643.pdf %*Tensor Decomposition via Joint Matrix Schur Decomposition %@Nicolo Colombo, Nikos Vlassis %t2012 %cICML %f/ICML/ICML-2012-644.pdf %*Continuous Deep Q-Learning with Model-based Acceleration %@Shixiang Gu, Timothy Lillicrap, Ilya Sutskever, Sergey Levine %t2012 %cICML %f/ICML/ICML-2012-645.pdf %*Continuous Deep Q-Learning with Model-based Acceleration %@Shixiang Gu, Timothy Lillicrap, Ilya Sutskever, Sergey Levine %t2012 %cICML %f/ICML/ICML-2012-646.pdf %*Domain Adaptation with Conditional Transferable Components %@Mingming Gong, Kun Zhang, Tongliang Liu, Dacheng Tao, Clark Glymour, Bernhard Schölkopf %t2012 %cICML %f/ICML/ICML-2012-647.pdf %*Domain Adaptation with Conditional Transferable Components %@Mingming Gong, Kun Zhang, Tongliang Liu, Dacheng Tao, Clark Glymour, Bernhard Schölkopf %t2012 %cICML %f/ICML/ICML-2012-648.pdf %*Fixed Point Quantization of Deep Convolutional Networks %@Darryl Lin, Sachin Talathi, Sreekanth Annapureddy %t2012 %cICML %f/ICML/ICML-2012-649.pdf %*Provable Algorithms for Inference in Topic Models %@Sanjeev Arora, Rong Ge, Frederic Koehler, Tengyu Ma, Ankur Moitra %t2012 %cICML %f/ICML/ICML-2012-650.pdf %*Epigraph projections for fast general convex programming %@Po-Wei Wang, Matt Wytock, Zico Kolter %t2012 %cICML %f/ICML/ICML-2012-651.pdf %*Epigraph projections for fast general convex programming %@Po-Wei Wang, Matt Wytock, Zico Kolter %t2012 %cICML %f/ICML/ICML-2012-652.pdf %*Fast Algorithms for Segmented Regression %@Jayadev Acharya, Ilias Diakonikolas, Jerry Li, Ludwig Schmidt %t2012 %cICML %f/ICML/ICML-2012-653.pdf %*Fast Algorithms for Segmented Regression %@Jayadev Acharya, Ilias Diakonikolas, Jerry Li, Ludwig Schmidt %t2012 %cICML %f/ICML/ICML-2012-654.pdf %*Energetic Natural Gradient Descent %@Philip Thomas, Bruno Castro da Silva, Christoph Dann, Emma Brunskill %t2012 %cICML %f/ICML/ICML-2012-655.pdf %*Energetic Natural Gradient Descent %@Philip Thomas, Bruno Castro da Silva, Christoph Dann, Emma Brunskill %t2012 %cICML %f/ICML/ICML-2012-656.pdf %*Partition Functions from Rao-Blackwellized Tempered Sampling %@David Carlson, Patrick Stinson, Ari Pakman, Liam Paninski %t2012 %cICML %f/ICML/ICML-2012-657.pdf %*Partition Functions from Rao-Blackwellized Tempered Sampling %@David Carlson, Patrick Stinson, Ari Pakman, Liam Paninski %t2012 %cICML %f/ICML/ICML-2012-658.pdf %*Learning Mixtures of Plackett-Luce Models %@Zhibing Zhao, Peter Piech, Lirong Xia %t2012 %cICML %f/ICML/ICML-2012-659.pdf %*Learning Mixtures of Plackett-Luce Models %@Zhibing Zhao, Peter Piech, Lirong Xia %t2012 %cICML %f/ICML/ICML-2012-660.pdf %*Near Optimal Behavior via Approximate State Abstraction %@David Abel, David Hershkowitz, Michael Littman %t2012 %cICML %f/ICML/ICML-2012-661.pdf %*Power of Ordered Hypothesis Testing %@Lihua Lei, William Fithian %t2012 %cICML %f/ICML/ICML-2012-662.pdf %*Power of Ordered Hypothesis Testing %@Lihua Lei, William Fithian %t2012 %cICML %f/ICML/ICML-2012-663.pdf %*PHOG: Probabilistic Model for Code %@Pavol Bielik, Veselin Raychev, Martin Vechev %t2012 %cICML %f/ICML/ICML-2012-664.pdf %*PHOG: Probabilistic Model for Code %@Pavol Bielik, Veselin Raychev, Martin Vechev %t2012 %cICML %f/ICML/ICML-2012-665.pdf %*Shifting Regret, Mirror Descent, and Matrices %@Andras Gyorgy, Csaba Szepesvari %t2012 %cICML %f/ICML/ICML-2012-666.pdf %*Scalable Gradient-Based Tuning of Continuous Regularization Hyperparameters %@Jelena Luketina, Tapani Raiko, Mathias Berglund, Klaus Greff %t2012 %cICML %f/ICML/ICML-2012-667.pdf %*Model-Free Trajectory Optimization for Reinforcement Learning %@Riad Akrour, Gerhard Neumann, Hany Abdulsamad, Abbas Abdolmaleki %t2012 %cICML %f/ICML/ICML-2012-668.pdf %*Model-Free Trajectory Optimization for Reinforcement Learning %@Riad Akrour, Gerhard Neumann, Hany Abdulsamad, Abbas Abdolmaleki %t2012 %cICML %f/ICML/ICML-2012-669.pdf %*Controlling the distance to a Kemeny consensus without computing it %@Yunlong Jiao, Anna Korba, Eric Sibony %t2012 %cICML %f/ICML/ICML-2012-670.pdf %*Controlling the distance to a Kemeny consensus without computing it %@Yunlong Jiao, Anna Korba, Eric Sibony %t2012 %cICML %f/ICML/ICML-2012-671.pdf %*Horizontally Scalable Submodular Maximization %@Mario Lucic, Olivier Bachem, Morteza Zadimoghaddam, Andreas Krause %t2012 %cICML %f/ICML/ICML-2012-672.pdf %*Horizontally Scalable Submodular Maximization %@Mario Lucic, Olivier Bachem, Morteza Zadimoghaddam, Andreas Krause %t2012 %cICML %f/ICML/ICML-2012-673.pdf %*Group Equivariant Convolutional Networks %@Taco Cohen, Max Welling %t2012 %cICML %f/ICML/ICML-2012-674.pdf %*Group Equivariant Convolutional Networks %@Taco Cohen, Max Welling %t2012 %cICML %f/ICML/ICML-2012-675.pdf %*Stochastic Discrete Clenshaw-Curtis Quadrature %@Nico Piatkowski, Katharina Morik %t2012 %cICML %f/ICML/ICML-2012-676.pdf %*Correcting Forecasts with Multifactor Neural Attention %@Matthew Riemer, Aditya Vempaty, Flavio Calmon, Fenno Heath, Richard Hull, Elham Khabiri %t2012 %cICML %f/ICML/ICML-2012-677.pdf %*Learning Representations for Counterfactual Inference %@Fredrik Johansson, Uri Shalit, David Sontag %t2012 %cICML %f/ICML/ICML-2012-678.pdf %*Learning Representations for Counterfactual Inference %@Fredrik Johansson, Uri Shalit, David Sontag %t2012 %cICML %f/ICML/ICML-2012-679.pdf %*Automatic Construction of Nonparametric Relational Regression Models for Multiple Time Series %@Yunseong Hwang, Anh Tong, Jaesik Choi %t2012 %cICML %f/ICML/ICML-2012-680.pdf %*Automatic Construction of Nonparametric Relational Regression Models for Multiple Time Series %@Yunseong Hwang, Anh Tong, Jaesik Choi %t2012 %cICML %f/ICML/ICML-2012-681.pdf %*Inference Networks for Sequential Monte Carlo in Graphical Models %@Brooks Paige, Frank Wood %t2012 %cICML %f/ICML/ICML-2012-682.pdf %*Inference Networks for Sequential Monte Carlo in Graphical Models %@Brooks Paige, Frank Wood %t2012 %cICML %f/ICML/ICML-2012-683.pdf %*Slice Sampling on Hamiltonian Trajectories %@Benjamin Bloem-Reddy, John Cunningham %t2012 %cICML %f/ICML/ICML-2012-684.pdf %*Slice Sampling on Hamiltonian Trajectories %@Benjamin Bloem-Reddy, John Cunningham %t2012 %cICML %f/ICML/ICML-2012-685.pdf %*Noisy Activation Functions %@Caglar Gulcehre, Marcin Moczulski, Misha Denil, Yoshua Bengio %t2012 %cICML %f/ICML/ICML-2012-686.pdf %*PD-Sparse : A Primal and Dual Sparse Approach to Extreme Multiclass and Multilabel Classification %@Ian En-Hsu Yen, Xiangru Huang, Pradeep Ravikumar, Kai Zhong, Inderjit Dhillon %t2012 %cICML %f/ICML/ICML-2012-687.pdf %*PD-Sparse : A Primal and Dual Sparse Approach to Extreme Multiclass and Multilabel Classification %@Ian En-Hsu Yen, Xiangru Huang, Pradeep Ravikumar, Kai Zhong, Inderjit Dhillon %t2012 %cICML %f/ICML/ICML-2012-688.pdf %*An Optimal Policy for Target Localization with Application to Electron Microscopy %@Raphael Sznitman, Aurelien Lucchi, Peter Frazier, Bruno Jedynak, Pascal Fua %t2013 %cICML %f/ICML/ICML-2013-689.pdf %*Domain Generalization via Invariant Feature Representation %@Krikamol Muandet, David Balduzzi, Bernhard Schölkopf %t2013 %cICML %f/ICML/ICML-2013-690.pdf %*Domain Generalization via Invariant Feature Representation %@Krikamol Muandet, David Balduzzi, Bernhard Schölkopf %t2013 %cICML %f/ICML/ICML-2013-691.pdf %*A Spectral Learning Approach to Range-Only SLAM %@SLAM %t2013 %cICML %f/ICML/ICML-2013-692.pdf %*A Spectral Learning Approach to Range-Only SLAM %@SLAM %t2013 %cICML %f/ICML/ICML-2013-693.pdf %*Near-Optimal Bounds for Cross-Validation via Loss Stability %@Ravi Kumar, Daniel Lokshtanov, Sergei Vassilvitskii, Andrea Vattani %t2013 %cICML %f/ICML/ICML-2013-694.pdf %*Sparsity-Based Generalization Bounds for Predictive Sparse Coding %@Nishant Mehta, Alexander Gray %t2013 %cICML %f/ICML/ICML-2013-695.pdf %*Sparsity-Based Generalization Bounds for Predictive Sparse Coding %@Nishant Mehta, Alexander Gray %t2013 %cICML %f/ICML/ICML-2013-696.pdf %*Sparse Uncorrelated Linear Discriminant Analysis %@Xiaowei Zhang, Delin Chu %t2013 %cICML %f/ICML/ICML-2013-697.pdf %*Block-Coordinate Frank-Wolfe Optimization for Structural SVMs %@Frank-Wolfe %t2013 %cICML %f/ICML/ICML-2013-698.pdf %*Block-Coordinate Frank-Wolfe Optimization for Structural SVMs %@Frank-Wolfe %t2013 %cICML %f/ICML/ICML-2013-699.pdf %*Fast Probabilistic Optimization from Noisy Gradients %@Philipp Hennig %t2013 %cICML %f/ICML/ICML-2013-700.pdf %*Stochastic Gradient Descent for Non-smooth Optimization: Convergence Results and Optimal Averaging Schemes %@Ohad Shamir, Tong Zhang %t2013 %cICML %f/ICML/ICML-2013-701.pdf %*Stochastic Alternating Direction Method of Multipliers %@Hua Ouyang, Niao He, Long Tran, Alexander Gray %t2013 %cICML %f/ICML/ICML-2013-702.pdf %*Stochastic Alternating Direction Method of Multipliers %@Hua Ouyang, Niao He, Long Tran, Alexander Gray %t2013 %cICML %f/ICML/ICML-2013-703.pdf %*Noisy Sparse Subspace Clustering %@Yu-Xiang Wang, Huan Xu %t2013 %cICML %f/ICML/ICML-2013-704.pdf %*Noisy Sparse Subspace Clustering %@Yu-Xiang Wang, Huan Xu %t2013 %cICML %f/ICML/ICML-2013-705.pdf %*Parallel Markov Chain Monte Carlo for Nonparametric Mixture Models %@M %t2013 %cICML %f/ICML/ICML-2013-706.pdf %*Parallel Markov Chain Monte Carlo for Nonparametric Mixture Models %@M %t2013 %cICML %f/ICML/ICML-2013-707.pdf %*Risk Bounds and Learning Algorithms for the Regression Approach to Structured Output Prediction %@Sébastien Giguère, François Laviolette, Mario Marchand, Khadidja Sylla %t2013 %cICML %f/ICML/ICML-2013-708.pdf %*Risk Bounds and Learning Algorithms for the Regression Approach to Structured Output Prediction %@Sébastien Giguère, François Laviolette, Mario Marchand, Khadidja Sylla %t2013 %cICML %f/ICML/ICML-2013-709.pdf %*Making a Science of Model Search: Hyperparameter Optimization in Hundreds of Dimensions for Vision Architectures %@James Bergstra, Daniel Yamins, David Cox %t2013 %cICML %f/ICML/ICML-2013-710.pdf %*Gibbs Max-Margin Topic Models with Fast Sampling Algorithms %@G %t2013 %cICML %f/ICML/ICML-2013-711.pdf %*Cost-Sensitive Tree of Classifiers %@Zhixiang Xu, Matt Kusner, Kilian Weinberger, Minmin Chen %t2013 %cICML %f/ICML/ICML-2013-712.pdf %*Learning Hash Functions Using Column Generation %@Xi Li, Guosheng Lin, Chunhua Shen, Anton Van den Hengel, Anthony Dick %t2013 %cICML %f/ICML/ICML-2013-713.pdf %*Combinatorial Multi-Armed Bandit: General Framework and Applications %@Wei Chen, Yajun Wang, Yang Yuan %t2013 %cICML %f/ICML/ICML-2013-714.pdf %*Combinatorial Multi-Armed Bandit: General Framework and Applications %@Wei Chen, Yajun Wang, Yang Yuan %t2013 %cICML %f/ICML/ICML-2013-715.pdf %*Near-optimal Batch Mode Active Learning and Adaptive Submodular Optimization %@Yuxin Chen, Andreas Krause %t2013 %cICML %f/ICML/ICML-2013-716.pdf %*Near-optimal Batch Mode Active Learning and Adaptive Submodular Optimization %@Yuxin Chen, Andreas Krause %t2013 %cICML %f/ICML/ICML-2013-717.pdf %*Convex formulations of radius-margin based Support Vector Machines %@Huyen Do, Alexandros Kalousis %t2013 %cICML %f/ICML/ICML-2013-718.pdf %*Modelling Sparse Dynamical Systems with Compressed Predictive State Representations %@William L. Hamilton, Mahdi Milani Fard, Joelle Pineau %t2013 %cICML %f/ICML/ICML-2013-719.pdf %*A Machine Learning Framework for Programming by Example %@Aditya Menon, Omer Tamuz, Sumit Gulwani, Butler Lampson, Adam Kalai %t2013 %cICML %f/ICML/ICML-2013-720.pdf %*Discriminatively Activated Sparselets %@Ross Girshick, Hyun Oh Song, Trevor Darrell %t2013 %cICML %f/ICML/ICML-2013-721.pdf %*Discriminatively Activated Sparselets %@Ross Girshick, Hyun Oh Song, Trevor Darrell %t2013 %cICML %f/ICML/ICML-2013-722.pdf %*The Pairwise Piecewise-Linear Embedding for Efficient Non-Linear Classification %@Ofir Pele, Ben Taskar, Amir Globerson, Michael Werman %t2013 %cICML %f/ICML/ICML-2013-723.pdf %*Fixed-Point Model For Structured Labeling %@Quannan Li, Jingdong Wang, David Wipf, Zhuowen Tu %t2013 %cICML %f/ICML/ICML-2013-724.pdf %*Connecting the Dots with Landmarks: Discriminatively Learning Domain-Invariant Features for Unsupervised Domain Adaptation %@Boqing Gong, Kristen Grauman, Fei Sha %t2013 %cICML %f/ICML/ICML-2013-725.pdf %*Connecting the Dots with Landmarks: Discriminatively Learning Domain-Invariant Features for Unsupervised Domain Adaptation %@Boqing Gong, Kristen Grauman, Fei Sha %t2013 %cICML %f/ICML/ICML-2013-726.pdf %*Fast Conical Hull Algorithms for Near-separable Non-negative Matrix Factorization %@Abhishek Kumar, Vikas Sindhwani, Prabhanjan Kambadur %t2013 %cICML %f/ICML/ICML-2013-727.pdf %*Principal Component Analysis on non-Gaussian Dependent Data %@G %t2013 %cICML %f/ICML/ICML-2013-728.pdf %*Learning Linear Bayesian Networks with Latent Variables %@Animashree Anandkumar, Daniel Hsu, Adel Javanmard, Sham Kakade %t2013 %cICML %f/ICML/ICML-2013-729.pdf %*Multiple Identifications in Multi-Armed Bandits %@Séebastian Bubeck, Tengyao Wang, Nitin Viswanathan %t2013 %cICML %f/ICML/ICML-2013-730.pdf %*Learning Optimally Sparse Support Vector Machines %@Andrew Cotter, Shai Shalev-Shwartz, Nati Srebro %t2013 %cICML %f/ICML/ICML-2013-731.pdf %*Learning Optimally Sparse Support Vector Machines %@Andrew Cotter, Shai Shalev-Shwartz, Nati Srebro %t2013 %cICML %f/ICML/ICML-2013-732.pdf %*Dynamic Probabilistic Models for Latent Feature Propagation in Social Networks %@Creighton Heaukulani, Zoubin Ghahramani %t2013 %cICML %f/ICML/ICML-2013-733.pdf %*Efficient Sparse Group Feature Selection via Nonconvex Optimization %@Shuo Xiang, Xiaoshen Tong, Jieping Ye %t2013 %cICML %f/ICML/ICML-2013-734.pdf %*Efficient Sparse Group Feature Selection via Nonconvex Optimization %@Shuo Xiang, Xiaoshen Tong, Jieping Ye %t2013 %cICML %f/ICML/ICML-2013-735.pdf %*Domain Adaptation for Sequence Labeling Tasks with a Probabilistic Language Adaptation Model %@Min Xiao, Yuhong Guo %t2013 %cICML %f/ICML/ICML-2013-736.pdf %*Maximum Variance Correction with Application to A* Search %@Wenlin Chen, Kilian Weinberger, Yixin Chen %t2013 %cICML %f/ICML/ICML-2013-737.pdf %*Adaptive Sparsity in Gaussian Graphical Models %@G %t2013 %cICML %f/ICML/ICML-2013-738.pdf %*Average Reward Optimization Objective In Partially Observable Domains %@Yuri Grinberg, Doina Precup %t2013 %cICML %f/ICML/ICML-2013-739.pdf %*Average Reward Optimization Objective In Partially Observable Domains %@Yuri Grinberg, Doina Precup %t2013 %cICML %f/ICML/ICML-2013-740.pdf %*Feature Selection in High-Dimensional Classification %@Mladen Kolar, Han Liu %t2013 %cICML %f/ICML/ICML-2013-741.pdf %*Human Boosting %@Harsh Pareek, Pradeep Ravikumar %t2013 %cICML %f/ICML/ICML-2013-742.pdf %*Efficient Dimensionality Reduction for Canonical Correlation Analysis %@Haim Avron, Christos Boutsidis, Sivan Toledo, Anastasios Zouzias %t2013 %cICML %f/ICML/ICML-2013-743.pdf %*Parsing epileptic events using a Markov switching process model for correlated time series %@Drausin Wulsin, Emily Fox, Brian Litt %t2013 %cICML %f/ICML/ICML-2013-744.pdf %*Parsing epileptic events using a Markov switching process model for correlated time series %@Drausin Wulsin, Emily Fox, Brian Litt %t2013 %cICML %f/ICML/ICML-2013-745.pdf %*Optimal rates for stochastic convex optimization under Tsybakov noise condition %@Aaditya Ramdas, Aarti Singh %t2013 %cICML %f/ICML/ICML-2013-746.pdf %*Optimal rates for stochastic convex optimization under Tsybakov noise condition %@Aaditya Ramdas, Aarti Singh %t2013 %cICML %f/ICML/ICML-2013-747.pdf %*A Randomized Mirror Descent Algorithm for Large Scale Multiple Kernel Learning %@Arash Afkanpour, András György, Csaba Szepesvari, Michael Bowling %t2013 %cICML %f/ICML/ICML-2013-748.pdf %*Noisy and Missing Data Regression: Distribution-Oblivious Support Recovery %@Yudong Chen, Constantine Caramanis %t2013 %cICML %f/ICML/ICML-2013-749.pdf %*Noisy and Missing Data Regression: Distribution-Oblivious Support Recovery %@Yudong Chen, Constantine Caramanis %t2013 %cICML %f/ICML/ICML-2013-750.pdf %*Dual Averaging and Proximal Gradient Descent for Online Alternating Direction Multiplier Method %@Taiji Suzuki %t2013 %cICML %f/ICML/ICML-2013-751.pdf %*Dual Averaging and Proximal Gradient Descent for Online Alternating Direction Multiplier Method %@Taiji Suzuki %t2013 %cICML %f/ICML/ICML-2013-752.pdf %*A New Frontier of Kernel Design for Structured Data %@Kilho Shin %t2013 %cICML %f/ICML/ICML-2013-753.pdf %*Learning with Marginalized Corrupted Features %@Laurens Van der Maaten, Minmin Chen, Stephen Tyree, Kilian Weinberger %t2013 %cICML %f/ICML/ICML-2013-754.pdf %*Approximation properties of DBNs with binary hidden units and real-valued visible units %@DBNs %t2013 %cICML %f/ICML/ICML-2013-755.pdf %*Revisiting Frank-Wolfe: Projection-Free Sparse Convex Optimization %@Frank-Wolfe %t2013 %cICML %f/ICML/ICML-2013-756.pdf %*Revisiting Frank-Wolfe: Projection-Free Sparse Convex Optimization %@Frank-Wolfe %t2013 %cICML %f/ICML/ICML-2013-757.pdf %*General Functional Matrix Factorization Using Gradient Boosting %@Tianqi Chen, Hang Li, Qiang Yang, Yong Yu %t2013 %cICML %f/ICML/ICML-2013-758.pdf %*Iterative Learning and Denoising in Convolutional Neural Associative Memories %@Amin Karbasi, Amir Hesam Salavati, Amin Shokrollahi %t2013 %cICML %f/ICML/ICML-2013-759.pdf %*Iterative Learning and Denoising in Convolutional Neural Associative Memories %@Amin Karbasi, Amir Hesam Salavati, Amin Shokrollahi %t2013 %cICML %f/ICML/ICML-2013-760.pdf %*Scaling Multidimensional Gaussian Processes using Projected Additive Approximations %@G %t2013 %cICML %f/ICML/ICML-2013-761.pdf %*Scaling Multidimensional Gaussian Processes using Projected Additive Approximations %@G %t2013 %cICML %f/ICML/ICML-2013-762.pdf %*Active Learning for Multi-Objective Optimization %@Marcela Zuluaga, Guillaume Sergent, Andreas Krause, Markus Püschel %t2013 %cICML %f/ICML/ICML-2013-763.pdf %*Active Learning for Multi-Objective Optimization %@Marcela Zuluaga, Guillaume Sergent, Andreas Krause, Markus Püschel %t2013 %cICML %f/ICML/ICML-2013-764.pdf %*A Generalized Kernel Approach to Structured Output Learning %@Hachem Kadri, Mohammad Ghavamzadeh, Philippe Preux %t2013 %cICML %f/ICML/ICML-2013-765.pdf %*Efficient Active Learning of Halfspaces: an Aggressive Approach %@Alon Gonen, Sivan Sabato, Shai Shalev-Shwartz %t2013 %cICML %f/ICML/ICML-2013-766.pdf %*Enhanced statistical rankings via targeted data collection %@Braxton Osting, Christoph Brune, Stanley Osher %t2013 %cICML %f/ICML/ICML-2013-767.pdf %*Online Feature Selection for Model-based Reinforcement Learning %@Trung Nguyen, Zhuoru Li, Tomi Silander, Tze Yun Leong %t2013 %cICML %f/ICML/ICML-2013-768.pdf %*Online Feature Selection for Model-based Reinforcement Learning %@Trung Nguyen, Zhuoru Li, Tomi Silander, Tze Yun Leong %t2013 %cICML %f/ICML/ICML-2013-769.pdf %*ELLA: An Efficient Lifelong Learning Algorithm %@ELLA %t2013 %cICML %f/ICML/ICML-2013-770.pdf %*ELLA: An Efficient Lifelong Learning Algorithm %@ELLA %t2013 %cICML %f/ICML/ICML-2013-771.pdf %*A Structural SVM Based Approach for Optimizing Partial AUC %@SVM %t2013 %cICML %f/ICML/ICML-2013-772.pdf %*A Structural SVM Based Approach for Optimizing Partial AUC %@SVM %t2013 %cICML %f/ICML/ICML-2013-773.pdf %*Convex Relaxations for Learning Bounded-Treewidth Decomposable Graphs %@K. S. Sesh Kumar, Francis Bach %t2013 %cICML %f/ICML/ICML-2013-774.pdf %*Convex Relaxations for Learning Bounded-Treewidth Decomposable Graphs %@K. S. Sesh Kumar, Francis Bach %t2013 %cICML %f/ICML/ICML-2013-775.pdf %*Adaptive Task Assignment for Crowdsourced Classification %@Chien-Ju Ho, Shahin Jabbari, Jennifer Wortman Vaughan %t2013 %cICML %f/ICML/ICML-2013-776.pdf %*Optimal Regret Bounds for Selecting the State Representation in Reinforcement Learning %@Odalric-Ambrym Maillard, Phuong Nguyen, Ronald Ortner, Daniil Ryabko %t2013 %cICML %f/ICML/ICML-2013-777.pdf %*Better Mixing via Deep Representations %@Yoshua Bengio, Gregoire Mesnil, Yann Dauphin, Salah Rifai %t2013 %cICML %f/ICML/ICML-2013-778.pdf %*Online Latent Dirichlet Allocation with Infinite Vocabulary %@D %t2013 %cICML %f/ICML/ICML-2013-779.pdf %*Characterizing the Representer Theorem %@Yaoliang Yu, Hao Cheng, Dale Schuurmans, Csaba Szepesvari %t2013 %cICML %f/ICML/ICML-2013-780.pdf %*Dynamical Models and tracking regret in online convex programming %@Eric Hall, Rebecca Willett %t2013 %cICML %f/ICML/ICML-2013-781.pdf %*Large-Scale Bandit Problems and KWIK Learning %@KWIK %t2013 %cICML %f/ICML/ICML-2013-782.pdf %*Large-Scale Bandit Problems and KWIK Learning %@KWIK %t2013 %cICML %f/ICML/ICML-2013-783.pdf %*Vanishing Component Analysis %@Roi Livni, David Lehavi, Sagi Schein, Hila Nachliely, Shai Shalev-Shwartz, Amir Globerson %t2013 %cICML %f/ICML/ICML-2013-784.pdf %*Learning an Internal Dynamics Model from Control Demonstration %@Matthew Golub, Steven Chase, Byron Yu %t2013 %cICML %f/ICML/ICML-2013-785.pdf %*Robust Structural Metric Learning %@Daryl Lim, Gert Lanckriet, Brian McFee %t2013 %cICML %f/ICML/ICML-2013-786.pdf %*Constrained fractional set programs and their application in local clustering and community detection %@Thomas Bühler, Shyam Sundar Rangapuram, Simon Setzer, Matthias Hein %t2013 %cICML %f/ICML/ICML-2013-787.pdf %*Constrained fractional set programs and their application in local clustering and community detection %@Thomas Bühler, Shyam Sundar Rangapuram, Simon Setzer, Matthias Hein %t2013 %cICML %f/ICML/ICML-2013-788.pdf %*Efficient Semi-supervised and Active Learning of Disjunctions %@Nina Balcan, Christopher Berlind, Steven Ehrlich, Yingyu Liang %t2013 %cICML %f/ICML/ICML-2013-789.pdf %*Efficient Semi-supervised and Active Learning of Disjunctions %@Nina Balcan, Christopher Berlind, Steven Ehrlich, Yingyu Liang %t2013 %cICML %f/ICML/ICML-2013-790.pdf %*Convex Adversarial Collective Classification %@MohamadAli Torkamani, Daniel Lowd %t2013 %cICML %f/ICML/ICML-2013-791.pdf %*Convex Adversarial Collective Classification %@MohamadAli Torkamani, Daniel Lowd %t2013 %cICML %f/ICML/ICML-2013-792.pdf %*Rounding Methods for Discrete Linear Classification %@Yann Chevaleyre, Frédéerick Koriche, Jean-daniel Zucker %t2013 %cICML %f/ICML/ICML-2013-793.pdf %*Rounding Methods for Discrete Linear Classification %@Yann Chevaleyre, Frédéerick Koriche, Jean-daniel Zucker %t2013 %cICML %f/ICML/ICML-2013-794.pdf %*Mixture of Mutually Exciting Processes for Viral Diffusion %@Shuang-Hong Yang, Hongyuan Zha %t2013 %cICML %f/ICML/ICML-2013-795.pdf %*Mixture of Mutually Exciting Processes for Viral Diffusion %@Shuang-Hong Yang, Hongyuan Zha %t2013 %cICML %f/ICML/ICML-2013-796.pdf %*Gaussian Process Vine Copulas for Multivariate Dependence %@David Lopez-Paz, Jose Miguel Hernández-Lobato, Ghahramani Zoubin %t2013 %cICML %f/ICML/ICML-2013-797.pdf %*Stochastic Simultaneous Optimistic Optimization %@Michal Valko, Alexandra Carpentier, Rémi Munos %t2013 %cICML %f/ICML/ICML-2013-798.pdf %*Toward Optimal Stratification for Stratified Monte-Carlo Integration %@Alexandra Carpentier, Rémi Munos %t2013 %cICML %f/ICML/ICML-2013-799.pdf %*A General Iterative Shrinkage and Thresholding Algorithm for Non-convex Regularized Optimization Problems %@Pinghua Gong, Changshui Zhang, Zhaosong Lu, Jianhua Huang, Jieping Ye %t2013 %cICML %f/ICML/ICML-2013-800.pdf %*Thurstonian Boltzmann Machines: Learning from Multiple Inequalities %@B %t2013 %cICML %f/ICML/ICML-2013-801.pdf %*Thurstonian Boltzmann Machines: Learning from Multiple Inequalities %@B %t2013 %cICML %f/ICML/ICML-2013-802.pdf %*A Variational Approximation for Topic Modeling of Hierarchical Corpora %@Do-kyum Kim, Geoffrey Voelker, Lawrence Saul %t2013 %cICML %f/ICML/ICML-2013-803.pdf %*A Variational Approximation for Topic Modeling of Hierarchical Corpora %@Do-kyum Kim, Geoffrey Voelker, Lawrence Saul %t2013 %cICML %f/ICML/ICML-2013-804.pdf %*Forecastable Component Analysis %@Georg Goerg %t2013 %cICML %f/ICML/ICML-2013-805.pdf %*Forecastable Component Analysis %@Georg Goerg %t2013 %cICML %f/ICML/ICML-2013-806.pdf %*Ellipsoidal Multiple Instance Learning %@Gabriel Krummenacher, Cheng Soon Ong, Joachim Buhmann %t2013 %cICML %f/ICML/ICML-2013-807.pdf %*Ellipsoidal Multiple Instance Learning %@Gabriel Krummenacher, Cheng Soon Ong, Joachim Buhmann %t2013 %cICML %f/ICML/ICML-2013-808.pdf %*Local Low-Rank Matrix Approximation %@Joonseok Lee, Seungyeon Kim, Guy Lebanon, Yoram Singer %t2013 %cICML %f/ICML/ICML-2013-809.pdf %*Generic Exploration and K-armed Voting Bandits %@K %t2013 %cICML %f/ICML/ICML-2013-810.pdf %*Generic Exploration and K-armed Voting Bandits %@K %t2013 %cICML %f/ICML/ICML-2013-811.pdf %*A unifying framework for vector-valued manifold regularization and multi-view learning %@Minh Hà Quang, Loris Bazzani, Vittorio Murino %t2013 %cICML %f/ICML/ICML-2013-812.pdf %*A unifying framework for vector-valued manifold regularization and multi-view learning %@Minh Hà Quang, Loris Bazzani, Vittorio Murino %t2013 %cICML %f/ICML/ICML-2013-813.pdf %*Learning Connections in Financial Time Series %@Gartheeban Ganeshapillai, John Guttag, Andrew Lo %t2013 %cICML %f/ICML/ICML-2013-814.pdf %*Fast dropout training %@Sida Wang, Christopher Manning %t2013 %cICML %f/ICML/ICML-2013-815.pdf %*Scalable Optimization of Neighbor Embedding for Visualization %@Zhirong Yang, Jaakko Peltonen, Samuel Kaski %t2013 %cICML %f/ICML/ICML-2013-816.pdf %*Scalable Optimization of Neighbor Embedding for Visualization %@Zhirong Yang, Jaakko Peltonen, Samuel Kaski %t2013 %cICML %f/ICML/ICML-2013-817.pdf %*Precision-recall space to correct external indices for biclustering %@Blaise Hanczar, Mohamed Nadif %t2013 %cICML %f/ICML/ICML-2013-818.pdf %*Monochromatic Bi-Clustering %@Sharon Wulff, Ruth Urner, Shai Ben-David %t2013 %cICML %f/ICML/ICML-2013-819.pdf %*Monochromatic Bi-Clustering %@Sharon Wulff, Ruth Urner, Shai Ben-David %t2013 %cICML %f/ICML/ICML-2013-820.pdf %*Gated Autoencoders with Tied Input Weights %@Droniou Alain, Sigaud Olivier %t2013 %cICML %f/ICML/ICML-2013-821.pdf %*Strict Monotonicity of Sum of Squares Error and Normalized Cut in the Lattice of Clusterings %@Nicola Rebagliati %t2013 %cICML %f/ICML/ICML-2013-822.pdf %*Transition Matrix Estimation in High Dimensional Time Series %@Fang Han, Han Liu %t2013 %cICML %f/ICML/ICML-2013-823.pdf %*Label Partitioning For Sublinear Ranking %@Jason Weston, Ameesh Makadia, Hector Yee %t2013 %cICML %f/ICML/ICML-2013-824.pdf %*Subproblem-Tree Calibration: A Unified Approach to Max-Product Message Passing %@Huayan Wang, Koller Daphne %t2013 %cICML %f/ICML/ICML-2013-825.pdf %*Subproblem-Tree Calibration: A Unified Approach to Max-Product Message Passing %@Huayan Wang, Koller Daphne %t2013 %cICML %f/ICML/ICML-2013-826.pdf %*Collaborative hyperparameter tuning %@Rémi Bardenet, Mátyás Brendel, Balázs Kégl, Michèle Sebag %t2013 %cICML %f/ICML/ICML-2013-827.pdf %*Collaborative hyperparameter tuning %@Rémi Bardenet, Mátyás Brendel, Balázs Kégl, Michèle Sebag %t2013 %cICML %f/ICML/ICML-2013-828.pdf %*SADA: A General Framework to Support Robust Causation Discovery %@Ruichu Cai, Zhenjie Zhang, Zhifeng Hao %t2013 %cICML %f/ICML/ICML-2013-829.pdf %*Learning and Selecting Features Jointly with Point-wise Gated Boltzmann Machines %@B %t2013 %cICML %f/ICML/ICML-2013-830.pdf %*Sequential Bayesian Search %@B %t2013 %cICML %f/ICML/ICML-2013-831.pdf %*Sequential Bayesian Search %@B %t2013 %cICML %f/ICML/ICML-2013-832.pdf %*Sparse projections onto the simplex %@Anastasios Kyrillidis, Stephen Becker, Volkan Cevher, Christoph Koch %t2013 %cICML %f/ICML/ICML-2013-833.pdf %*Modeling Musical Influence with Topic Models %@Uri Shalit, Daphna Weinshall, Gal Chechik %t2013 %cICML %f/ICML/ICML-2013-834.pdf %*Modeling Musical Influence with Topic Models %@Uri Shalit, Daphna Weinshall, Gal Chechik %t2013 %cICML %f/ICML/ICML-2013-835.pdf %*Subtle Topic Models and Discovering Subtly Manifested Software Concerns Automatically %@Mrinal Das, Suparna Bhattacharya, Chiranjib Bhattacharyya, Gopinath Kanchi %t2013 %cICML %f/ICML/ICML-2013-836.pdf %*Subtle Topic Models and Discovering Subtly Manifested Software Concerns Automatically %@Mrinal Das, Suparna Bhattacharya, Chiranjib Bhattacharyya, Gopinath Kanchi %t2013 %cICML %f/ICML/ICML-2013-837.pdf %*Exploring the Mind: Integrating Questionnaires and fMRI %@Esther Salazar, Ryan Bogdan, Adam Gorka, Ahmad Hariri, Lawrence Carin %t2013 %cICML %f/ICML/ICML-2013-838.pdf %*A proximal Newton framework for composite minimization: Graph learning without Cholesky decompositions and matrix inversions %@N %t2013 %cICML %f/ICML/ICML-2013-839.pdf %*A proximal Newton framework for composite minimization: Graph learning without Cholesky decompositions and matrix inversions %@N %t2013 %cICML %f/ICML/ICML-2013-840.pdf %*A Practical Algorithm for Topic Modeling with Provable Guarantees %@Sanjeev Arora, Rong Ge, Yonatan Halpern, David Mimno, Ankur Moitra, David Sontag, Yichen Wu, Michael Zhu %t2013 %cICML %f/ICML/ICML-2013-841.pdf %*A Practical Algorithm for Topic Modeling with Provable Guarantees %@Sanjeev Arora, Rong Ge, Yonatan Halpern, David Mimno, Ankur Moitra, David Sontag, Yichen Wu, Michael Zhu %t2013 %cICML %f/ICML/ICML-2013-842.pdf %*Distributed training of Large-scale Logistic models %@Siddharth Gopal, Yiming Yang %t2013 %cICML %f/ICML/ICML-2013-843.pdf %*An Adaptive Learning Rate for Stochastic Variational Inference %@Rajesh Ranganath, Chong Wang, Blei David, Eric Xing %t2013 %cICML %f/ICML/ICML-2013-844.pdf %*An Adaptive Learning Rate for Stochastic Variational Inference %@Rajesh Ranganath, Chong Wang, Blei David, Eric Xing %t2013 %cICML %f/ICML/ICML-2013-845.pdf %*Margins, Shrinkage, and Boosting %@Matus Telgarsky %t2013 %cICML %f/ICML/ICML-2013-846.pdf %*Margins, Shrinkage, and Boosting %@Matus Telgarsky %t2013 %cICML %f/ICML/ICML-2013-847.pdf %*Canonical Correlation Analysis based on Hilbert-Schmidt Independence Criterion and Centered Kernel Target Alignment %@Billy Chang, Uwe Kruger, Rafal Kustra, Junping Zhang %t2013 %cICML %f/ICML/ICML-2013-848.pdf %*Canonical Correlation Analysis based on Hilbert-Schmidt Independence Criterion and Centered Kernel Target Alignment %@Billy Chang, Uwe Kruger, Rafal Kustra, Junping Zhang %t2013 %cICML %f/ICML/ICML-2013-849.pdf %*Large-Scale Learning with Less RAM via Randomization %@Daniel Golovin, D. Sculley, Brendan McMahan, Michael Young %t2013 %cICML %f/ICML/ICML-2013-850.pdf %*Taming the Curse of Dimensionality: Discrete Integration by Hashing and Optimization %@Stefano Ermon, Carla Gomes, Ashish Sabharwal, Bart Selman %t2013 %cICML %f/ICML/ICML-2013-851.pdf %*Taming the Curse of Dimensionality: Discrete Integration by Hashing and Optimization %@Stefano Ermon, Carla Gomes, Ashish Sabharwal, Bart Selman %t2013 %cICML %f/ICML/ICML-2013-852.pdf %*Sparse coding for multitask and transfer learning %@Andreas Maurer, Massi Pontil, Bernardino Romera-Paredes %t2013 %cICML %f/ICML/ICML-2013-853.pdf %*Sparse coding for multitask and transfer learning %@Andreas Maurer, Massi Pontil, Bernardino Romera-Paredes %t2013 %cICML %f/ICML/ICML-2013-854.pdf %*Direct Modeling of Complex Invariances for Visual Object Features %@Ka Yu Hui %t2013 %cICML %f/ICML/ICML-2013-855.pdf %*Hierarchically-coupled hidden Markov models for learning kinetic rates from single-molecule data %@M %t2013 %cICML %f/ICML/ICML-2013-856.pdf %*Activized Learning with Uniform Classification Noise %@Liu Yang, Steve Hanneke %t2013 %cICML %f/ICML/ICML-2013-857.pdf %*Guided Policy Search %@Sergey Levine, Vladlen Koltun %t2013 %cICML %f/ICML/ICML-2013-858.pdf %*Guided Policy Search %@Sergey Levine, Vladlen Koltun %t2013 %cICML %f/ICML/ICML-2013-859.pdf %*Squared-loss Mutual Information Regularization: A Novel Information-theoretic Approach to Semi-supervised Learning %@Gang Niu, Wittawat Jitkrittum, Bo Dai, Hirotaka Hachiya, Masashi Sugiyama %t2013 %cICML %f/ICML/ICML-2013-860.pdf %*Squared-loss Mutual Information Regularization: A Novel Information-theoretic Approach to Semi-supervised Learning %@Gang Niu, Wittawat Jitkrittum, Bo Dai, Hirotaka Hachiya, Masashi Sugiyama %t2013 %cICML %f/ICML/ICML-2013-861.pdf %*Gossip-based distributed stochastic bandit algorithms %@Balazs Szorenyi, Robert Busa-Fekete, Istvan Hegedus, Robert Ormandi, Mark Jelasity, Balazs Kegl %t2013 %cICML %f/ICML/ICML-2013-862.pdf %*Gossip-based distributed stochastic bandit algorithms %@Balazs Szorenyi, Robert Busa-Fekete, Istvan Hegedus, Robert Ormandi, Mark Jelasity, Balazs Kegl %t2013 %cICML %f/ICML/ICML-2013-863.pdf %*The Sample-Complexity of General Reinforcement Learning %@Tor Lattimore, Marcus Hutter, Peter Sunehag %t2013 %cICML %f/ICML/ICML-2013-864.pdf %*Hierarchical Regularization Cascade for Joint Learning %@Alon Zweig, Daphna Weinshall %t2013 %cICML %f/ICML/ICML-2013-865.pdf %*Hierarchical Regularization Cascade for Joint Learning %@Alon Zweig, Daphna Weinshall %t2013 %cICML %f/ICML/ICML-2013-866.pdf %*Multi-Class Classification with Maximum Margin Multiple Kernel %@Corinna Cortes, Mehryar Mohri, Afshin Rostamizadeh %t2013 %cICML %f/ICML/ICML-2013-867.pdf %*Multi-Class Classification with Maximum Margin Multiple Kernel %@Corinna Cortes, Mehryar Mohri, Afshin Rostamizadeh %t2013 %cICML %f/ICML/ICML-2013-868.pdf %*Bayesian Games for Adversarial Regression Problems %@Michael Großhans, Christoph Sawade, Michael Brückner, Tobias Scheffer %t2013 %cICML %f/ICML/ICML-2013-869.pdf %*Bayesian Games for Adversarial Regression Problems %@Michael Großhans, Christoph Sawade, Michael Brückner, Tobias Scheffer %t2013 %cICML %f/ICML/ICML-2013-870.pdf %*Optimistic Knowledge Gradient Policy for Optimal Budget Allocation in Crowdsourcing %@Xi Chen, Qihang Lin, Dengyong Zhou %t2013 %cICML %f/ICML/ICML-2013-871.pdf %*Optimistic Knowledge Gradient Policy for Optimal Budget Allocation in Crowdsourcing %@Xi Chen, Qihang Lin, Dengyong Zhou %t2013 %cICML %f/ICML/ICML-2013-872.pdf %*Markov Network Estimation From Multi-attribute Data %@Mladen Kolar, Han Liu, Eric Xing %t2013 %cICML %f/ICML/ICML-2013-873.pdf %*MILEAGE: Multiple Instance LEArning with Global Embedding %@Dan Zhang, Jingrui He, Luo Si, Richard Lawrence %t2013 %cICML %f/ICML/ICML-2013-874.pdf %*MILEAGE: Multiple Instance LEArning with Global Embedding %@Dan Zhang, Jingrui He, Luo Si, Richard Lawrence %t2013 %cICML %f/ICML/ICML-2013-875.pdf %*Guaranteed Sparse Recovery under Linear Transformation %@Ji Liu, Lei Yuan, Jieping Ye %t2013 %cICML %f/ICML/ICML-2013-876.pdf %*Learning invariant features by harnessing the aperture problem %@Roland Memisevic, Georgios Exarchakis %t2013 %cICML %f/ICML/ICML-2013-877.pdf %*Efficient Ranking from Pairwise Comparisons %@Fabian Wauthier, Michael Jordan, Nebojsa Jojic %t2013 %cICML %f/ICML/ICML-2013-878.pdf %*Efficient Ranking from Pairwise Comparisons %@Fabian Wauthier, Michael Jordan, Nebojsa Jojic %t2013 %cICML %f/ICML/ICML-2013-879.pdf %*Differentially Private Learning with Kernels %@Prateek Jain, Abhradeep Thakurta %t2013 %cICML %f/ICML/ICML-2013-880.pdf %*Differentially Private Learning with Kernels %@Prateek Jain, Abhradeep Thakurta %t2013 %cICML %f/ICML/ICML-2013-881.pdf %*Thompson Sampling for Contextual Bandits with Linear Payoffs %@Shipra Agrawal, Navin Goyal %t2013 %cICML %f/ICML/ICML-2013-882.pdf %*Thompson Sampling for Contextual Bandits with Linear Payoffs %@Shipra Agrawal, Navin Goyal %t2013 %cICML %f/ICML/ICML-2013-883.pdf %*Learning Multiple Behaviors from Unlabeled Demonstrations in a Latent Controller Space %@Javier Almingol, Lui Montesano, Manuel Lopes %t2013 %cICML %f/ICML/ICML-2013-884.pdf %*Learning Multiple Behaviors from Unlabeled Demonstrations in a Latent Controller Space %@Javier Almingol, Lui Montesano, Manuel Lopes %t2013 %cICML %f/ICML/ICML-2013-885.pdf %*Inference algorithms for pattern-based CRFs on sequence data %@Rustem Takhanov, Vladimir Kolmogorov %t2013 %cICML %f/ICML/ICML-2013-886.pdf %*One-Bit Compressed Sensing: Provable Support and Vector Recovery %@Sivakant Gopi, Praneeth Netrapalli, Prateek Jain, Aditya Nori %t2013 %cICML %f/ICML/ICML-2013-887.pdf %*One-Bit Compressed Sensing: Provable Support and Vector Recovery %@Sivakant Gopi, Praneeth Netrapalli, Prateek Jain, Aditya Nori %t2013 %cICML %f/ICML/ICML-2013-888.pdf %*Tensor Analyzers %@Yichuan Tang, Ruslan Salakhutdinov, Geoffrey Hinton %t2013 %cICML %f/ICML/ICML-2013-889.pdf %*Tensor Analyzers %@Yichuan Tang, Ruslan Salakhutdinov, Geoffrey Hinton %t2013 %cICML %f/ICML/ICML-2013-890.pdf %*Learning Sparse Penalties for Change-point Detection using Max Margin Interval Regression %@Toby Hocking, Guillem Rigaill, Jean-Philippe Vert, Francis Bach %t2013 %cICML %f/ICML/ICML-2013-891.pdf %*Learning from Human-Generated Lists %@Kwang-Sung Jun, Jerry Zhu, Burr Settles, Timothy Rogers %t2013 %cICML %f/ICML/ICML-2013-892.pdf %*A Fast and Exact Energy Minimization Algorithm for Cycle MRFs %@Huayan Wang, Koller Daphne %t2013 %cICML %f/ICML/ICML-2013-893.pdf %*A Fast and Exact Energy Minimization Algorithm for Cycle MRFs %@Huayan Wang, Koller Daphne %t2013 %cICML %f/ICML/ICML-2013-894.pdf %*Stochastic k-Neighborhood Selection for Supervised and Unsupervised Learning %@Daniel Tarlow, Kevin Swersky, Laurent Charlin, Ilya Sutskever, Rich Zemel %t2013 %cICML %f/ICML/ICML-2013-895.pdf %*Stochastic k-Neighborhood Selection for Supervised and Unsupervised Learning %@Daniel Tarlow, Kevin Swersky, Laurent Charlin, Ilya Sutskever, Rich Zemel %t2013 %cICML %f/ICML/ICML-2013-896.pdf %*An Efficient Posterior Regularized Latent Variable Model for Interactive Sound Source Separation %@Nicholas Bryan, Gautham Mysore %t2013 %cICML %f/ICML/ICML-2013-897.pdf %*Estimating Unknown Sparsity in Compressed Sensing %@Miles Lopes %t2013 %cICML %f/ICML/ICML-2013-898.pdf %*Estimating Unknown Sparsity in Compressed Sensing %@Miles Lopes %t2013 %cICML %f/ICML/ICML-2013-899.pdf %*MAD-Bayes: MAP-based Asymptotic Derivations from Bayes %@Tamara Broderick, Brian Kulis, Michael Jordan %t2013 %cICML %f/ICML/ICML-2013-900.pdf %*MAD-Bayes: MAP-based Asymptotic Derivations from Bayes %@Tamara Broderick, Brian Kulis, Michael Jordan %t2013 %cICML %f/ICML/ICML-2013-901.pdf %*The Most Generative Maximum Margin Bayesian Networks %@Robert Peharz, Sebastian Tschiatschek, Franz Pernkopf %t2013 %cICML %f/ICML/ICML-2013-902.pdf %*The Most Generative Maximum Margin Bayesian Networks %@Robert Peharz, Sebastian Tschiatschek, Franz Pernkopf %t2013 %cICML %f/ICML/ICML-2013-903.pdf %*Fastfood - Computing Hilbert Space Expansions in loglinear time %@Quoc Le, Tamas Sarlos, Alexander Smola %t2013 %cICML %f/ICML/ICML-2013-904.pdf %*Fastfood - Computing Hilbert Space Expansions in loglinear time %@Quoc Le, Tamas Sarlos, Alexander Smola %t2013 %cICML %f/ICML/ICML-2013-905.pdf %*Joint Transfer and Batch-mode Active Learning %@Rita Chattopadhyay, Wei Fan, Ian Davidson, Sethuraman Panchanathan, Jieping Ye %t2013 %cICML %f/ICML/ICML-2013-906.pdf %*Joint Transfer and Batch-mode Active Learning %@Rita Chattopadhyay, Wei Fan, Ian Davidson, Sethuraman Panchanathan, Jieping Ye %t2013 %cICML %f/ICML/ICML-2013-907.pdf %*Message passing with l1 penalized KL minimization %@Yuan Qi, Yandong Guo %t2013 %cICML %f/ICML/ICML-2013-908.pdf %*Message passing with l1 penalized KL minimization %@Yuan Qi, Yandong Guo %t2013 %cICML %f/ICML/ICML-2013-909.pdf %*Mean Reversion with a Variance Threshold %@Marco Cuturi, Alexandre D’Aspremont %t2013 %cICML %f/ICML/ICML-2013-910.pdf %*Top-down particle filtering for Bayesian decision trees %@Balaji Lakshminarayanan, Daniel Roy, Yee Whye Teh %t2013 %cICML %f/ICML/ICML-2013-911.pdf %*Top-down particle filtering for Bayesian decision trees %@Balaji Lakshminarayanan, Daniel Roy, Yee Whye Teh %t2013 %cICML %f/ICML/ICML-2013-912.pdf %*Smooth Sparse Coding via Marginal Regression for Learning Sparse Representations %@Krishnakumar Balasubramanian, Kai Yu, Guy Lebanon %t2013 %cICML %f/ICML/ICML-2013-913.pdf %*Smooth Sparse Coding via Marginal Regression for Learning Sparse Representations %@Krishnakumar Balasubramanian, Kai Yu, Guy Lebanon %t2013 %cICML %f/ICML/ICML-2013-914.pdf %*Robust and Discriminative Self-Taught Learning %@Hua Wang, Feiping Nie, Heng Huang %t2013 %cICML %f/ICML/ICML-2013-915.pdf %*Robust and Discriminative Self-Taught Learning %@Hua Wang, Feiping Nie, Heng Huang %t2013 %cICML %f/ICML/ICML-2013-916.pdf %*Safe Policy Iteration %@Matteo Pirotta, Marcello Restelli, Alessio Pecorino, Daniele Calandriello %t2013 %cICML %f/ICML/ICML-2013-917.pdf %*Safe Policy Iteration %@Matteo Pirotta, Marcello Restelli, Alessio Pecorino, Daniele Calandriello %t2013 %cICML %f/ICML/ICML-2013-918.pdf %*Unfolding Latent Tree Structures using 4th Order Tensors %@Mariya Ishteva, Haesun Park, Le Song %t2013 %cICML %f/ICML/ICML-2013-919.pdf %*Unfolding Latent Tree Structures using 4th Order Tensors %@Mariya Ishteva, Haesun Park, Le Song %t2013 %cICML %f/ICML/ICML-2013-920.pdf %*Learning Fair Representations %@Rich Zemel, Yu Wu, Kevin Swersky, Toni Pitassi, Cynthia Dwork %t2013 %cICML %f/ICML/ICML-2013-921.pdf %*Learning Fair Representations %@Rich Zemel, Yu Wu, Kevin Swersky, Toni Pitassi, Cynthia Dwork %t2013 %cICML %f/ICML/ICML-2013-922.pdf %*Hierarchical Tensor Decomposition of Latent Tree Graphical Models %@Le Song, Mariya Ishteva, Ankur Parikh, Eric Xing, Haesun Park %t2013 %cICML %f/ICML/ICML-2013-923.pdf %*No more pesky learning rates %@Tom Schaul, Sixin Zhang, Yann LeCun %t2013 %cICML %f/ICML/ICML-2013-924.pdf %*No more pesky learning rates %@Tom Schaul, Sixin Zhang, Yann LeCun %t2013 %cICML %f/ICML/ICML-2013-925.pdf %*Multi-View Clustering and Feature Learning via Structured Sparsity %@Hua Wang, Feiping Nie, Heng Huang %t2013 %cICML %f/ICML/ICML-2013-926.pdf %*Planning by Prioritized Sweeping with Small Backups %@Harm Van Seijen, Rich Sutton %t2013 %cICML %f/ICML/ICML-2013-927.pdf %*Solving Continuous POMDPs: Value Iteration with Incremental Learning of an Efficient Space Representation %@Sebastian Brechtel, Tobias Gindele, Rdiger Dillmann %t2013 %cICML %f/ICML/ICML-2013-928.pdf %*Learning Heteroscedastic Models by Convex Programming under Group Sparsity %@Arnak Dalalyan, Mohamed Hebiri, Katia Meziani, Joseph Salmon %t2013 %cICML %f/ICML/ICML-2013-929.pdf %*Learning Heteroscedastic Models by Convex Programming under Group Sparsity %@Arnak Dalalyan, Mohamed Hebiri, Katia Meziani, Joseph Salmon %t2013 %cICML %f/ICML/ICML-2013-930.pdf %*Covariate Shift in Hilbert Space: A Solution via Sorrogate Kernels %@Kai Zhang, Vincent Zheng, Qiaojun Wang, James Kwok, Qiang Yang, Ivan Marsic %t2013 %cICML %f/ICML/ICML-2013-931.pdf %*A Local Algorithm for Finding Well-Connected Clusters %@Zeyuan Allen Zhu, Silvio Lattanzi, Vahab Mirrokni %t2013 %cICML %f/ICML/ICML-2013-932.pdf %*A Local Algorithm for Finding Well-Connected Clusters %@Zeyuan Allen Zhu, Silvio Lattanzi, Vahab Mirrokni %t2013 %cICML %f/ICML/ICML-2013-933.pdf %*Efficient Multi-label Classification with Many Labels %@Wei Bi, James Kwok %t2013 %cICML %f/ICML/ICML-2013-934.pdf %*Spectral Compressed Sensing via Structured Matrix Completion %@Yuxin Chen, Yuejie Chi %t2013 %cICML %f/ICML/ICML-2013-935.pdf %*Spectral Compressed Sensing via Structured Matrix Completion %@Yuxin Chen, Yuejie Chi %t2013 %cICML %f/ICML/ICML-2013-936.pdf %*Multi-Task Learning with Gaussian Matrix Generalized Inverse Gaussian Model %@Ming Yang, Yingming Li, Zhongfei Zhang (Zhejiang University) %t2013 %cICML %f/ICML/ICML-2013-937.pdf %*Simple Sparsification Improves Sparse Denoising Autoencoders in Denoising Highly Corrupted Images %@Kyunghyun Cho %t2013 %cICML %f/ICML/ICML-2013-938.pdf %*On the Generalization Ability of Online Learning Algorithms for Pairwise Loss Functions %@Purushottam Kar, Bharath Sriperumbudur, Prateek Jain, Harish Karnick %t2013 %cICML %f/ICML/ICML-2013-939.pdf %*On the Generalization Ability of Online Learning Algorithms for Pairwise Loss Functions %@Purushottam Kar, Bharath Sriperumbudur, Prateek Jain, Harish Karnick %t2013 %cICML %f/ICML/ICML-2013-940.pdf %*Non-Linear Stationary Subspace Analysis with Application to Video Classification %@Mahsa Baktashmotlagh, Mehrtash Harandi, Abbas Bigdeli, Brian Lovell, Mathieu Salzmann %t2013 %cICML %f/ICML/ICML-2013-941.pdf %*Non-Linear Stationary Subspace Analysis with Application to Video Classification %@Mahsa Baktashmotlagh, Mehrtash Harandi, Abbas Bigdeli, Brian Lovell, Mathieu Salzmann %t2013 %cICML %f/ICML/ICML-2013-942.pdf %*Two-Sided Exponential Concentration Bounds for Bayes Error Rate and Shannon Entropy %@Jean Honorio, Jaakkola Tommi %t2013 %cICML %f/ICML/ICML-2013-943.pdf %*That was fast! Speeding up NN search of high dimensional distributions. %@Emanuele Coviello, Adeel Mumtaz, Antoni Chan, Gert Lanckriet %t2013 %cICML %f/ICML/ICML-2013-944.pdf %*That was fast! Speeding up NN search of high dimensional distributions. %@Emanuele Coviello, Adeel Mumtaz, Antoni Chan, Gert Lanckriet %t2013 %cICML %f/ICML/ICML-2013-945.pdf %*Entropic Affinities: Properties and Efficient Numerical Computation %@Max Vladymyrov, Miguel Carreira-Perpinan %t2013 %cICML %f/ICML/ICML-2013-946.pdf %*Local Deep Kernel Learning for Efficient Non-linear SVM Prediction %@Cijo Jose, Prasoon Goyal, Parv Aggrwal, Manik Varma %t2013 %cICML %f/ICML/ICML-2013-947.pdf %*Temporal Difference Methods for the Variance of the Reward To Go %@Aviv Tamar, Dotan Di Castro, Shie Mannor %t2013 %cICML %f/ICML/ICML-2013-948.pdf %*Temporal Difference Methods for the Variance of the Reward To Go %@Aviv Tamar, Dotan Di Castro, Shie Mannor %t2013 %cICML %f/ICML/ICML-2013-949.pdf %*Parameter Learning and Convergent Inference for Dense Random Fields %@Philipp Kraehenbuehl, Vladlen Koltun %t2013 %cICML %f/ICML/ICML-2013-950.pdf %*Loss-Proportional Subsampling for Subsequent ERM %@Paul Mineiro, Nikos Karampatziakis %t2013 %cICML %f/ICML/ICML-2013-951.pdf %*Scalable Simple Random Sampling and Stratified Sampling %@Xiangrui Meng %t2013 %cICML %f/ICML/ICML-2013-952.pdf %*Riemannian Similarity Learning %@Li Cheng %t2013 %cICML %f/ICML/ICML-2013-953.pdf %*On Compact Codes for Spatially Pooled Features %@Yangqing Jia, Oriol Vinyals, Trevor Darrell %t2013 %cICML %f/ICML/ICML-2013-954.pdf %*On Compact Codes for Spatially Pooled Features %@Yangqing Jia, Oriol Vinyals, Trevor Darrell %t2013 %cICML %f/ICML/ICML-2013-955.pdf %*Dynamic Covariance Models for Multivariate Financial Time Series %@Yue Wu, Jose Miguel Hernandez-Lobato, Ghahramani Zoubin %t2013 %cICML %f/ICML/ICML-2013-956.pdf %*Revisiting the Nystrom method for improved large-scale machine learning %@Alex Gittens, Michael Mahoney %t2013 %cICML %f/ICML/ICML-2013-957.pdf %*Infinite Positive Semidefinite Tensor Factorization for Source Separation of Mixture Signals %@Kazuyoshi Yoshii, Ryota Tomioka, Daichi Mochihashi, Masataka Goto %t2013 %cICML %f/ICML/ICML-2013-958.pdf %*Infinite Positive Semidefinite Tensor Factorization for Source Separation of Mixture Signals %@Kazuyoshi Yoshii, Ryota Tomioka, Daichi Mochihashi, Masataka Goto %t2013 %cICML %f/ICML/ICML-2013-959.pdf %*A Unified Robust Regression Model for Lasso-like Algorithms %@Wenzhuo Yang, Huan Xu %t2013 %cICML %f/ICML/ICML-2013-960.pdf %*A Unified Robust Regression Model for Lasso-like Algorithms %@Wenzhuo Yang, Huan Xu %t2013 %cICML %f/ICML/ICML-2013-961.pdf %*Quickly Boosting Decision Trees – Pruning Underachieving Features Early %@Ron Appel, Thomas Fuchs, Piotr Dollar, Pietro Perona %t2013 %cICML %f/ICML/ICML-2013-962.pdf %*Quickly Boosting Decision Trees – Pruning Underachieving Features Early %@Ron Appel, Thomas Fuchs, Piotr Dollar, Pietro Perona %t2013 %cICML %f/ICML/ICML-2013-963.pdf %*On the Statistical Consistency of Algorithms for Binary Classification under Class Imbalance %@Aditya Menon, Harikrishna Narasimhan, Shivani Agarwal, Sanjay Chawla %t2013 %cICML %f/ICML/ICML-2013-964.pdf %*On the Statistical Consistency of Algorithms for Binary Classification under Class Imbalance %@Aditya Menon, Harikrishna Narasimhan, Shivani Agarwal, Sanjay Chawla %t2013 %cICML %f/ICML/ICML-2013-965.pdf %*Topic Model Diagnostics: Assessing Domain Relevance via Topical Alignment %@Jason Chuang, Sonal Gupta, Christopher Manning, Jeffrey Heer %t2013 %cICML %f/ICML/ICML-2013-966.pdf %*Topic Model Diagnostics: Assessing Domain Relevance via Topical Alignment %@Jason Chuang, Sonal Gupta, Christopher Manning, Jeffrey Heer %t2013 %cICML %f/ICML/ICML-2013-967.pdf %*Online Kernel Learning with a Near Optimal Sparsity Bound %@Lijun Zhang, Jinfeng Yi, Rong Jin, Ming Lin, Xiaofei He %t2013 %cICML %f/ICML/ICML-2013-968.pdf %*Online Kernel Learning with a Near Optimal Sparsity Bound %@Lijun Zhang, Jinfeng Yi, Rong Jin, Ming Lin, Xiaofei He %t2013 %cICML %f/ICML/ICML-2013-969.pdf %*Spectral Learning of Hidden Markov Models from Dynamic and Static Data %@Tzu-Kuo Huang, Jeff Schneider %t2013 %cICML %f/ICML/ICML-2013-970.pdf %*Analogy-preserving Semantic Embedding for Visual Object Categorization %@Sung Ju Hwang, Kristen Grauman, Fei Sha %t2013 %cICML %f/ICML/ICML-2013-971.pdf %*Algebraic classifiers: a generic approach to fast cross-validation, online training, and parallel training %@Michael Izbicki %t2013 %cICML %f/ICML/ICML-2013-972.pdf %*Algebraic classifiers: a generic approach to fast cross-validation, online training, and parallel training %@Michael Izbicki %t2013 %cICML %f/ICML/ICML-2013-973.pdf %*Factorial Multi-Task Learning : A Bayesian Nonparametric Approach %@Sunil Gupta, Dinh Phung, Svetha Venkatesh %t2013 %cICML %f/ICML/ICML-2013-974.pdf %*Modeling Information Propagation with Survival Theory %@Manuel Gomez-Rodriguez, Jure Leskovec, Bernhard Schlkopf %t2013 %cICML %f/ICML/ICML-2013-975.pdf %*Better Rates for Any Adversarial Deterministic MDP %@Ofer Dekel, Elad Hazan %t2013 %cICML %f/ICML/ICML-2013-976.pdf %*ABC Reinforcement Learning %@Christos Dimitrakakis, Nikolaos Tziortziotis %t2013 %cICML %f/ICML/ICML-2013-977.pdf %*Sharp Generalization Error Bounds for Randomly-projected Classifiers %@Robert Durrant, Ata Kaban %t2013 %cICML %f/ICML/ICML-2013-978.pdf %*On learning parametric-output HMMs %@Aryeh Kontorovich, Boaz Nadler, Roi Weiss %t2013 %cICML %f/ICML/ICML-2013-979.pdf %*On learning parametric-output HMMs %@Aryeh Kontorovich, Boaz Nadler, Roi Weiss %t2013 %cICML %f/ICML/ICML-2013-980.pdf %*LDA Topic Model with Soft Assignment of Descriptors to Words %@Daphna Weinshall, Gal Levi, Dmitri Hanukaev %t2013 %cICML %f/ICML/ICML-2013-981.pdf %*On autoencoder scoring %@Hanna Kamyshanska, Roland Memisevic %t2013 %cICML %f/ICML/ICML-2013-982.pdf %*Infinite Markov-Switching Maximum Entropy Discrimination Machines %@Sotirios Chatzis %t2013 %cICML %f/ICML/ICML-2013-983.pdf %*A PAC-Bayesian Approach for Domain Adaptation with Specialization to Linear Classifiers %@Pascal Germain, Amaury Habrard, Franois Laviolette, Emilie Morvant %t2013 %cICML %f/ICML/ICML-2013-984.pdf %*A PAC-Bayesian Approach for Domain Adaptation with Specialization to Linear Classifiers %@Pascal Germain, Amaury Habrard, Franois Laviolette, Emilie Morvant %t2013 %cICML %f/ICML/ICML-2013-985.pdf %*Sparse PCA through Low-rank Approximations %@Dimitris Papailiopoulos, Alexandros Dimakis, Stavros Korokythakis %t2013 %cICML %f/ICML/ICML-2013-986.pdf %*Computation-Risk Tradeoffs for Covariance-Thresholded Regression %@Dinah Shender, John Lafferty %t2013 %cICML %f/ICML/ICML-2013-987.pdf %*Exact Rule Learning via Boolean Compressed Sensing %@Dmitry Malioutov, Kush Varshney %t2013 %cICML %f/ICML/ICML-2013-988.pdf %*Robust Sparse Regression under Adversarial Corruption %@Yudong Chen, Constantine Caramanis, Shie Mannor %t2013 %cICML %f/ICML/ICML-2013-989.pdf %*Robust Sparse Regression under Adversarial Corruption %@Yudong Chen, Constantine Caramanis, Shie Mannor %t2013 %cICML %f/ICML/ICML-2013-990.pdf %*Optimization with First-Order Surrogate Functions %@Julien Mairal %t2013 %cICML %f/ICML/ICML-2013-991.pdf %*Optimization with First-Order Surrogate Functions %@Julien Mairal %t2013 %cICML %f/ICML/ICML-2013-992.pdf %*Learning Spatio-Temporal Structure from RGB-D Videos for Human Activity Detection and Anticipation %@Hema Koppula, Ashutosh Saxena %t2013 %cICML %f/ICML/ICML-2013-993.pdf %*Consistency versus Realizable H-Consistency for Multiclass Classification %@Phil Long, Rocco Servedio %t2013 %cICML %f/ICML/ICML-2013-994.pdf %*Consistency versus Realizable H-Consistency for Multiclass Classification %@Phil Long, Rocco Servedio %t2013 %cICML %f/ICML/ICML-2013-995.pdf %*Feature Multi-Selection among Subjective Features %@Sivan Sabato, Adam Kalai %t2013 %cICML %f/ICML/ICML-2013-996.pdf %*Domain Adaptation under Target and Conditional Shift %@Kun Zhang, Bernhard Schlkopf, Krikamol Muandet, Zhikun Wang %t2013 %cICML %f/ICML/ICML-2013-997.pdf %*Domain Adaptation under Target and Conditional Shift %@Kun Zhang, Bernhard Schlkopf, Krikamol Muandet, Zhikun Wang %t2013 %cICML %f/ICML/ICML-2013-998.pdf %*Collective Stability in Structured Prediction: Generalization from One Example %@Ben London, Bert Huang, Ben Taskar, Lise Getoor %t2013 %cICML %f/ICML/ICML-2013-999.pdf %*Collective Stability in Structured Prediction: Generalization from One Example %@Ben London, Bert Huang, Ben Taskar, Lise Getoor %t2013 %cICML %f/ICML/ICML-2013-1000.pdf %*Stable Coactive Learning via Perturbation %@Karthik Raman, Thorsten Joachims, Pannaga Shivaswamy, Tobias Schnabel %t2013 %cICML %f/ICML/ICML-2013-1001.pdf %*Stable Coactive Learning via Perturbation %@Karthik Raman, Thorsten Joachims, Pannaga Shivaswamy, Tobias Schnabel %t2013 %cICML %f/ICML/ICML-2013-1002.pdf %*Max-Margin Multiple-Instance Dictionary Learning %@Xinggang Wang, Baoyuan Wang, Xiang Bai, Wenyu Liu, Zhuowen Tu %t2013 %cICML %f/ICML/ICML-2013-1003.pdf %*Fast Semidifferential-based Submodular Function Optimization %@Rishabh Iyer, Stefanie Jegelka, Jeff Bilmes %t2013 %cICML %f/ICML/ICML-2013-1004.pdf %*Fast Semidifferential-based Submodular Function Optimization %@Rishabh Iyer, Stefanie Jegelka, Jeff Bilmes %t2013 %cICML %f/ICML/ICML-2013-1005.pdf %*Kernelized Bayesian Matrix Factorization %@Mehmet Gönen, Suleiman Khan, Samuel Kaski %t2013 %cICML %f/ICML/ICML-2013-1006.pdf %*Kernelized Bayesian Matrix Factorization %@Mehmet Gönen, Suleiman Khan, Samuel Kaski %t2013 %cICML %f/ICML/ICML-2013-1007.pdf %*Learning the Structure of Sum-Product Networks %@Robert Gens, Domingos Pedro %t2013 %cICML %f/ICML/ICML-2013-1008.pdf %*Quantile Regression for Large-scale Applications %@Jiyan Yang, Xiangrui Meng, Michael Mahoney %t2013 %cICML %f/ICML/ICML-2013-1009.pdf %*Robust Regression on MapReduce %@Xiangrui Meng, Michael Mahoney %t2013 %cICML %f/ICML/ICML-2013-1010.pdf %*Infinitesimal Annealing for Training Semi-Supervised Support Vector Machines %@Kohei Ogawa, Motoki Imamura, Ichiro Takeuchi, Masashi Sugiyama %t2013 %cICML %f/ICML/ICML-2013-1011.pdf %*Infinitesimal Annealing for Training Semi-Supervised Support Vector Machines %@Kohei Ogawa, Motoki Imamura, Ichiro Takeuchi, Masashi Sugiyama %t2013 %cICML %f/ICML/ICML-2013-1012.pdf %*One-Pass AUC Optimization %@Wei Gao, Rong Jin, Shenghuo Zhu, Zhi-Hua Zhou %t2013 %cICML %f/ICML/ICML-2013-1013.pdf %*Learning Convex QP Relaxations for Structured Prediction %@Jeremy Jancsary, Sebastian Nowozin, Carsten Rother %t2013 %cICML %f/ICML/ICML-2013-1014.pdf %*Concurrent Reinforcement Learning from Customer Interactions %@David Silver, Leonard Newnham, David Barker, Suzanne Weller, Jason McFall %t2013 %cICML %f/ICML/ICML-2013-1015.pdf %*Saving Evaluation Time for the Decision Function in Boosting: Representation and Reordering Base Learner %@Peng Sun, Jie Zhou %t2013 %cICML %f/ICML/ICML-2013-1016.pdf %*Saving Evaluation Time for the Decision Function in Boosting: Representation and Reordering Base Learner %@Peng Sun, Jie Zhou %t2013 %cICML %f/ICML/ICML-2013-1017.pdf %*Stability and Hypothesis Transfer Learning %@Ilja Kuzborskij, Francesco Orabona %t2013 %cICML %f/ICML/ICML-2013-1018.pdf %*Fast Dual Variational Inference for Non-Conjugate Latent Gaussian Models %@Mohammad Emtiyaz Khan, Aleksandr Aravkin, Michael Friedlander, Matthias Seeger %t2013 %cICML %f/ICML/ICML-2013-1019.pdf %*Modeling Temporal Evolution and Multiscale Structure in Networks %@Tue Herlau, Morten Mrup, Mikkel Schmidt %t2013 %cICML %f/ICML/ICML-2013-1020.pdf %*Modeling Temporal Evolution and Multiscale Structure in Networks %@Tue Herlau, Morten Mrup, Mikkel Schmidt %t2013 %cICML %f/ICML/ICML-2013-1021.pdf %*Dependent Normalized Random Measures %@Changyou Chen, Vinayak Rao, Wray Buntine, Yee Whye Teh %t2013 %cICML %f/ICML/ICML-2013-1022.pdf %*Dependent Normalized Random Measures %@Changyou Chen, Vinayak Rao, Wray Buntine, Yee Whye Teh %t2013 %cICML %f/ICML/ICML-2013-1023.pdf %*Fast Max-Margin Matrix Factorization with Data Augmentation %@Minjie Xu, Jun Zhu, Bo Zhang %t2013 %cICML %f/ICML/ICML-2013-1024.pdf %*Fast Max-Margin Matrix Factorization with Data Augmentation %@Minjie Xu, Jun Zhu, Bo Zhang %t2013 %cICML %f/ICML/ICML-2013-1025.pdf %*Natural Image Bases to Represent Neuroimaging Data %@Ashish Gupta, Murat Ayhan, Anthony Maida %t2013 %cICML %f/ICML/ICML-2013-1026.pdf %*Natural Image Bases to Represent Neuroimaging Data %@Ashish Gupta, Murat Ayhan, Anthony Maida %t2013 %cICML %f/ICML/ICML-2013-1027.pdf %*Breaking the Small Cluster Barrier of Graph Clustering %@Nir Ailon, Yudong Chen, Huan Xu %t2013 %cICML %f/ICML/ICML-2013-1028.pdf %*Breaking the Small Cluster Barrier of Graph Clustering %@Nir Ailon, Yudong Chen, Huan Xu %t2013 %cICML %f/ICML/ICML-2013-1029.pdf %*Approximate Inference in Collective Graphical Models %@Daniel Sheldon, Tao Sun, Akshat Kumar, Tom Dietterich %t2013 %cICML %f/ICML/ICML-2013-1030.pdf %*Scaling the Indian Buffet Process via Submodular Maximization %@Colorado Reed, Ghahramani Zoubin %t2013 %cICML %f/ICML/ICML-2013-1031.pdf %*Scaling the Indian Buffet Process via Submodular Maximization %@Colorado Reed, Ghahramani Zoubin %t2013 %cICML %f/ICML/ICML-2013-1032.pdf %*Mini-Batch Primal and Dual Methods for SVMs %@Martin Takac, Avleen Bijral, Peter Richtarik, Nati Srebro %t2013 %cICML %f/ICML/ICML-2013-1033.pdf %*Mini-Batch Primal and Dual Methods for SVMs %@Martin Takac, Avleen Bijral, Peter Richtarik, Nati Srebro %t2013 %cICML %f/ICML/ICML-2013-1034.pdf %*The lasso, persistence, and cross-validation %@Darren Homrighausen, Daniel McDonald %t2013 %cICML %f/ICML/ICML-2013-1035.pdf %*Spectral Experts for Estimating Mixtures of Linear Regressions %@Arun Tejasvi Chaganty, Percy Liang %t2013 %cICML %f/ICML/ICML-2013-1036.pdf %*Spectral Experts for Estimating Mixtures of Linear Regressions %@Arun Tejasvi Chaganty, Percy Liang %t2013 %cICML %f/ICML/ICML-2013-1037.pdf %*Distribution to Distribution Regression %@Junier Oliva, Barnabas Poczos, Jeff Schneider %t2013 %cICML %f/ICML/ICML-2013-1038.pdf %*Distribution to Distribution Regression %@Junier Oliva, Barnabas Poczos, Jeff Schneider %t2013 %cICML %f/ICML/ICML-2013-1039.pdf %*Regularization of Neural Networks using DropConnect %@Li Wan, Matthew Zeiler, Sixin Zhang, Yann Le Cun, Rob Fergus %t2013 %cICML %f/ICML/ICML-2013-1040.pdf %*Regularization of Neural Networks using DropConnect %@Li Wan, Matthew Zeiler, Sixin Zhang, Yann Le Cun, Rob Fergus %t2013 %cICML %f/ICML/ICML-2013-1041.pdf %*Gaussian Process Kernels for Pattern Discovery and Extrapolation %@Andrew Wilson, Ryan Adams %t2013 %cICML %f/ICML/ICML-2013-1042.pdf %*Gaussian Process Kernels for Pattern Discovery and Extrapolation %@Andrew Wilson, Ryan Adams %t2013 %cICML %f/ICML/ICML-2013-1043.pdf %*Anytime Representation Learning %@Zhixiang Xu, Matt Kusner, Gao Huang, Kilian Weinberger %t2013 %cICML %f/ICML/ICML-2013-1044.pdf %*Algorithms for Direct 0–1 Loss Optimization in Binary Classification %@Tan Nguyen, Scott Sanner %t2013 %cICML %f/ICML/ICML-2013-1045.pdf %*Top-k Selection based on Adaptive Sampling of Noisy Preferences %@Robert Busa-Fekete, Balazs Szorenyi, Weiwei Cheng, Paul Weng, Eyke Huellermeier %t2013 %cICML %f/ICML/ICML-2013-1046.pdf %*Top-k Selection based on Adaptive Sampling of Noisy Preferences %@Robert Busa-Fekete, Balazs Szorenyi, Weiwei Cheng, Paul Weng, Eyke Huellermeier %t2013 %cICML %f/ICML/ICML-2013-1047.pdf %*The Extended Parameter Filter %@Yusuf Bugra Erol, Lei Li, Bharath Ramsundar, Russell Stuart %t2013 %cICML %f/ICML/ICML-2013-1048.pdf %*The Extended Parameter Filter %@Yusuf Bugra Erol, Lei Li, Bharath Ramsundar, Russell Stuart %t2013 %cICML %f/ICML/ICML-2013-1049.pdf %*Exploiting Ontology Structures and Unlabeled Data for Learning %@Nina Balcan, Avrim Blum, Yishay Mansour %t2013 %cICML %f/ICML/ICML-2013-1050.pdf %*Exploiting Ontology Structures and Unlabeled Data for Learning %@Nina Balcan, Avrim Blum, Yishay Mansour %t2013 %cICML %f/ICML/ICML-2013-1051.pdf %*O(logT) Projections for Stochastic Optimization of Smooth and Strongly Convex Functions %@Lijun Zhang, Tianbao Yang, Rong Jin, Xiaofei He %t2013 %cICML %f/ICML/ICML-2013-1052.pdf %*O(logT) Projections for Stochastic Optimization of Smooth and Strongly Convex Functions %@Lijun Zhang, Tianbao Yang, Rong Jin, Xiaofei He %t2013 %cICML %f/ICML/ICML-2013-1053.pdf %*Optimizing the F-Measure in Multi-Label Classification: Plug-in Rule Approach versus Structured Loss Minimization %@Krzysztof Dembczynski, Arkadiusz Jachnik, Wojciech Kotlowski, Willem Waegeman, Eyke Huellermeier %t2013 %cICML %f/ICML/ICML-2013-1054.pdf %*On the importance of initialization and momentum in deep learning %@Ilya Sutskever, James Martens, George Dahl, Geoffrey Hinton %t2013 %cICML %f/ICML/ICML-2013-1055.pdf %*On the importance of initialization and momentum in deep learning %@Ilya Sutskever, James Martens, George Dahl, Geoffrey Hinton %t2013 %cICML %f/ICML/ICML-2013-1056.pdf %*A non-IID Framework for Collaborative Filtering with Restricted Boltzmann Machines %@Kostadin Georgiev, Preslav Nakov %t2013 %cICML %f/ICML/ICML-2013-1057.pdf %*Intersecting singularities for multi-structured estimation %@Emile Richard, Francis BACH, Jean-Philippe Vert %t2013 %cICML %f/ICML/ICML-2013-1058.pdf %*Intersecting singularities for multi-structured estimation %@Emile Richard, Francis BACH, Jean-Philippe Vert %t2013 %cICML %f/ICML/ICML-2013-1059.pdf %*Structure Discovery in Nonparametric Regression through Compositional Kernel Search %@David Duvenaud, James Lloyd, Roger Grosse, Joshua Tenenbaum, Ghahramani Zoubin %t2013 %cICML %f/ICML/ICML-2013-1060.pdf %*Copy or Coincidence? A Model for Detecting Social Influence and Duplication Events %@Lisa Friedland, David Jensen, Michael Lavine %t2013 %cICML %f/ICML/ICML-2013-1061.pdf %*Copy or Coincidence? A Model for Detecting Social Influence and Duplication Events %@Lisa Friedland, David Jensen, Michael Lavine %t2013 %cICML %f/ICML/ICML-2013-1062.pdf %*Smooth Operators %@Steffen Grunewalder, Gretton Arthur, John Shawe-Taylor %t2013 %cICML %f/ICML/ICML-2013-1063.pdf %*Smooth Operators %@Steffen Grunewalder, Gretton Arthur, John Shawe-Taylor %t2013 %cICML %f/ICML/ICML-2013-1064.pdf %*The Cross-Entropy Method Optimizes for Quantiles %@Sergiu Goschin, Ari Weinstein, Michael Littman %t2013 %cICML %f/ICML/ICML-2013-1065.pdf %*Topic Discovery through Data Dependent and Random Projections %@Weicong Ding, Mohammad Hossein Rohban, Prakash Ishwar, Venkatesh Saligrama %t2013 %cICML %f/ICML/ICML-2013-1066.pdf %*Topic Discovery through Data Dependent and Random Projections %@Weicong Ding, Mohammad Hossein Rohban, Prakash Ishwar, Venkatesh Saligrama %t2013 %cICML %f/ICML/ICML-2013-1067.pdf %*Bayesian Learning of Recursively Factored Environments %@Marc Bellemare, Joel Veness, Michael Bowling %t2013 %cICML %f/ICML/ICML-2013-1068.pdf %*Selective sampling algorithms for cost-sensitive multiclass prediction %@Alekh Agarwal %t2013 %cICML %f/ICML/ICML-2013-1069.pdf %*Selective sampling algorithms for cost-sensitive multiclass prediction %@Alekh Agarwal %t2013 %cICML %f/ICML/ICML-2013-1070.pdf %*The Bigraphical Lasso %@Alfredo Kalaitzis, John Lafferty, Neil Lawrence, Shuheng Zhou %t2013 %cICML %f/ICML/ICML-2013-1071.pdf %*The Bigraphical Lasso %@Alfredo Kalaitzis, John Lafferty, Neil Lawrence, Shuheng Zhou %t2013 %cICML %f/ICML/ICML-2013-1072.pdf %*Almost Optimal Exploration in Multi-Armed Bandits %@Zohar Karnin, Tomer Koren, Oren Somekh %t2013 %cICML %f/ICML/ICML-2013-1073.pdf %*Deep Canonical Correlation Analysis %@Galen Andrew, Raman Arora, Jeff Bilmes, Karen Livescu %t2013 %cICML %f/ICML/ICML-2013-1074.pdf %*Consistency of Online Random Forests %@Misha Denil, David Matheson, De Freitas Nando %t2013 %cICML %f/ICML/ICML-2013-1075.pdf %*Consistency of Online Random Forests %@Misha Denil, David Matheson, De Freitas Nando %t2013 %cICML %f/ICML/ICML-2013-1076.pdf %*Sparse Gaussian Conditional Random Fields: Algorithms, Theory, and Application to Energy Forecasting %@Matt Wytock, Zico Kolter %t2013 %cICML %f/ICML/ICML-2013-1077.pdf %*Sparse Gaussian Conditional Random Fields: Algorithms, Theory, and Application to Energy Forecasting %@Matt Wytock, Zico Kolter %t2013 %cICML %f/ICML/ICML-2013-1078.pdf %*Fast Image Tagging %@Minmin Chen, Alice Zheng, Kilian Weinberger %t2013 %cICML %f/ICML/ICML-2013-1079.pdf %*Expensive Function Optimization with Stochastic Binary Outcomes %@Matthew Tesch, Jeff Schneider, Howie Choset %t2013 %cICML %f/ICML/ICML-2013-1080.pdf %*Multiple-source cross-validation %@Krzysztof Geras, Charles Sutton %t2013 %cICML %f/ICML/ICML-2013-1081.pdf %*Learning Triggering Kernels for Multi-dimensional Hawkes Processes %@Ke Zhou, Hongyuan Zha, Le Song %t2013 %cICML %f/ICML/ICML-2013-1082.pdf %*On the difficulty of training recurrent neural networks %@Razvan Pascanu, Tomas Mikolov, Yoshua Bengio %t2013 %cICML %f/ICML/ICML-2013-1083.pdf %*On the difficulty of training recurrent neural networks %@Razvan Pascanu, Tomas Mikolov, Yoshua Bengio %t2013 %cICML %f/ICML/ICML-2013-1084.pdf %*Maxout Networks %@Ian Goodfellow, David Warde-Farley, Mehdi Mirza, Aaron Courville, Yoshua Bengio %t2013 %cICML %f/ICML/ICML-2013-1085.pdf %*Predictable Dual-View Hashing %@Mohammad Rastegari, Jonghyun Choi, Shobeir Fakhraei, Daume Hal, Larry Davis %t2013 %cICML %f/ICML/ICML-2013-1086.pdf %*Deep learning with COTS HPC systems %@Adam Coates, Brody Huval, Tao Wang, David Wu, Bryan Catanzaro, Ng Andrew %t2013 %cICML %f/ICML/ICML-2013-1087.pdf %*Nonparametric Mixture of Gaussian Processes with Constraints %@James Ross, Jennifer Dy %t2013 %cICML %f/ICML/ICML-2013-1088.pdf %*Scale Invariant Conditional Dependence Measures %@Sashank J Reddi, Barnabas Poczos %t2013 %cICML %f/ICML/ICML-2013-1089.pdf %*Scale Invariant Conditional Dependence Measures %@Sashank J Reddi, Barnabas Poczos %t2013 %cICML %f/ICML/ICML-2013-1090.pdf %*Learning Policies for Contextual Submodular Prediction %@Stephane Ross, Jiaji Zhou, Yisong Yue, Debadeepta Dey, Drew Bagnell %t2013 %cICML %f/ICML/ICML-2013-1091.pdf %*Learning Policies for Contextual Submodular Prediction %@Stephane Ross, Jiaji Zhou, Yisong Yue, Debadeepta Dey, Drew Bagnell %t2013 %cICML %f/ICML/ICML-2013-1092.pdf %*Manifold Preserving Hierarchical Topic Models for Quantization and Approximation %@Minje Kim, Paris Smaragdis %t2013 %cICML %f/ICML/ICML-2013-1093.pdf %*Safe Screening of Non-Support Vectors in Pathwise SVM Computation %@Kohei Ogawa, Yoshiki Suzuki, Ichiro Takeuchi %t2013 %cICML %f/ICML/ICML-2013-1094.pdf %*Safe Screening of Non-Support Vectors in Pathwise SVM Computation %@Kohei Ogawa, Yoshiki Suzuki, Ichiro Takeuchi %t2013 %cICML %f/ICML/ICML-2013-1095.pdf %*Cost-sensitive Multiclass Classification Risk Bounds %@Bernardo Ávila Pires, Csaba Szepesvari, Mohammad Ghavamzadeh %t2013 %cICML %f/ICML/ICML-2013-1096.pdf %*Semi-supervised Clustering by Input Pattern Assisted Pairwise Similarity Matrix Completion %@Jinfeng Yi, Lijun Zhang, Rong Jin, Qi Qian, Anil Jain %t2013 %cICML %f/ICML/ICML-2013-1097.pdf %*Learning the beta-Divergence in Tweedie Compound Poisson Matrix Factorization Models %@Umut Simsekli, Ali Taylan Cemgil, Yusuf Kenan Yilmaz %t2013 %cICML %f/ICML/ICML-2013-1098.pdf %*Fast algorithms for sparse principal component analysis based on Rayleigh quotient iteration %@Volodymyr Kuleshov %t2013 %cICML %f/ICML/ICML-2013-1099.pdf %*Nested Chinese Restaurant Franchise Process: Applications to User Tracking and Document Modeling %@Amr Ahmed, Liangjie Hong, Alexander Smola %t2013 %cICML %f/ICML/ICML-2013-1100.pdf %*Nested Chinese Restaurant Franchise Process: Applications to User Tracking and Document Modeling %@Amr Ahmed, Liangjie Hong, Alexander Smola %t2013 %cICML %f/ICML/ICML-2013-1101.pdf %*Tree-Independent Dual-Tree Algorithms %@Ryan Curtin, William March, Parikshit Ram, David Anderson, Alexander Gray, Charles Isbell %t2013 %cICML %f/ICML/ICML-2013-1102.pdf %*Multilinear Multitask Learning %@Bernardino Romera-Paredes, Hane Aung, Nadia Bianchi-Berthouze, Massimiliano Pontil %t2013 %cICML %f/ICML/ICML-2013-1103.pdf %*Multilinear Multitask Learning %@Bernardino Romera-Paredes, Hane Aung, Nadia Bianchi-Berthouze, Massimiliano Pontil %t2013 %cICML %f/ICML/ICML-2013-1104.pdf %*Online Learning under Delayed Feedback %@Pooria Joulani, Andras Gyorgy, Csaba Szepesvari %t2013 %cICML %f/ICML/ICML-2013-1105.pdf %*Adaptive Hamiltonian and Riemann Manifold Monte Carlo %@Ziyu Wang, Shakir Mohamed, De Freitas Nando %t2013 %cICML %f/ICML/ICML-2013-1106.pdf %*Coco-Q: Learning in Stochastic Games with Side Payments %@Eric Sodomka, Elizabeth Hilliard, Michael Littman, Amy Greenwald %t2013 %cICML %f/ICML/ICML-2013-1107.pdf %*On A Nonlinear Generalization of Sparse Coding and Dictionary Learning %@Jeffrey Ho, Yuchen Xie, Baba Vemuri %t2013 %cICML %f/ICML/ICML-2013-1108.pdf %*Estimation of Causal Peer Influence Effects %@Panos Toulis, Edward Kao %t2013 %cICML %f/ICML/ICML-2013-1109.pdf %*Estimation of Causal Peer Influence Effects %@Panos Toulis, Edward Kao %t2013 %cICML %f/ICML/ICML-2013-1110.pdf %*A Discriminative Latent Variable Model for Online Clustering %@Rajhans Samdani, Kai-Wei Chang, Dan Roth %t2014 %cICML %f/ICML/ICML-2014-1111.pdf %*A Discriminative Latent Variable Model for Online Clustering %@Rajhans Samdani, Kai-Wei Chang, Dan Roth %t2014 %cICML %f/ICML/ICML-2014-1112.pdf %*Kernel Mean Estimation and Stein Effect %@Krikamol Muandet, Kenji Fukumizu, Bharath Sriperumbudur, Arthur Gretton, Bernhard Schoelkopf %t2014 %cICML %f/ICML/ICML-2014-1113.pdf %*Kernel Mean Estimation and Stein Effect %@Krikamol Muandet, Kenji Fukumizu, Bharath Sriperumbudur, Arthur Gretton, Bernhard Schoelkopf %t2014 %cICML %f/ICML/ICML-2014-1114.pdf %*Demystifying Information-Theoretic Clustering %@Greg Ver Steeg, Aram Galstyan, Fei Sha, Simon DeDeo %t2014 %cICML %f/ICML/ICML-2014-1115.pdf %*Demystifying Information-Theoretic Clustering %@Greg Ver Steeg, Aram Galstyan, Fei Sha, Simon DeDeo %t2014 %cICML %f/ICML/ICML-2014-1116.pdf %*Covering Number for Efficient Heuristic-based POMDP Planning %@Zongzhang Zhang, David Hsu, Wee Sun Lee %t2014 %cICML %f/ICML/ICML-2014-1117.pdf %*Covering Number for Efficient Heuristic-based POMDP Planning %@Zongzhang Zhang, David Hsu, Wee Sun Lee %t2014 %cICML %f/ICML/ICML-2014-1118.pdf %*The Coherent Loss Function for Classification %@Wenzhuo Yang, Melvyn Sim, Huan Xu %t2014 %cICML %f/ICML/ICML-2014-1119.pdf %*The Coherent Loss Function for Classification %@Wenzhuo Yang, Melvyn Sim, Huan Xu %t2014 %cICML %f/ICML/ICML-2014-1120.pdf %*Fast Stochastic Alternating Direction Method of Multipliers %@Wenliang Zhong, James Kwok %t2014 %cICML %f/ICML/ICML-2014-1121.pdf %*Active Detection via Adaptive Submodularity %@Yuxin Chen, Hiroaki Shioi, Cesar Fuentes Montesinos, Lian Pin Koh, Serge Wich, Andreas Krause %t2014 %cICML %f/ICML/ICML-2014-1122.pdf %*Active Detection via Adaptive Submodularity %@Yuxin Chen, Hiroaki Shioi, Cesar Fuentes Montesinos, Lian Pin Koh, Serge Wich, Andreas Krause %t2014 %cICML %f/ICML/ICML-2014-1123.pdf %*Accelerated Proximal Stochastic Dual Coordinate Ascent for Regularized Loss Minimization %@Shai Shalev-Shwartz, Tong Zhang %t2014 %cICML %f/ICML/ICML-2014-1124.pdf %*An Adaptive Accelerated Proximal Gradient Method and its Homotopy Continuation for Sparse Optimization %@Qihang Lin, Lin Xiao %t2014 %cICML %f/ICML/ICML-2014-1125.pdf %*An Adaptive Accelerated Proximal Gradient Method and its Homotopy Continuation for Sparse Optimization %@Qihang Lin, Lin Xiao %t2014 %cICML %f/ICML/ICML-2014-1126.pdf %*Recurrent Convolutional Neural Networks for Scene Labeling %@Pedro Pinheiro, Ronan Collobert %t2014 %cICML %f/ICML/ICML-2014-1127.pdf %*A Statistical Perspective on Algorithmic Leveraging %@Ping Ma, Michael Mahoney, Bin Yu %t2014 %cICML %f/ICML/ICML-2014-1128.pdf %*Thompson Sampling for Complex Online Problems %@Aditya Gopalan, Shie Mannor, Yishay Mansour %t2014 %cICML %f/ICML/ICML-2014-1129.pdf %*Thompson Sampling for Complex Online Problems %@Aditya Gopalan, Shie Mannor, Yishay Mansour %t2014 %cICML %f/ICML/ICML-2014-1130.pdf %*Boosting multi-step autoregressive forecasts %@Souhaib Ben Taieb, Rob Hyndman %t2014 %cICML %f/ICML/ICML-2014-1131.pdf %*Boosting multi-step autoregressive forecasts %@Souhaib Ben Taieb, Rob Hyndman %t2014 %cICML %f/ICML/ICML-2014-1132.pdf %*A Statistical Convergence Perspective of Algorithms for Rank Aggregation from Pairwise Data %@Arun Rajkumar, Shivani Agarwal %t2014 %cICML %f/ICML/ICML-2014-1133.pdf %*A Statistical Convergence Perspective of Algorithms for Rank Aggregation from Pairwise Data %@Arun Rajkumar, Shivani Agarwal %t2014 %cICML %f/ICML/ICML-2014-1134.pdf %*Scaling Up Approximate Value Iteration with Options: Better Policies with Fewer Iterations %@Timothy Mann, Shie Mannor %t2014 %cICML %f/ICML/ICML-2014-1135.pdf %*Scaling Up Approximate Value Iteration with Options: Better Policies with Fewer Iterations %@Timothy Mann, Shie Mannor %t2014 %cICML %f/ICML/ICML-2014-1136.pdf %*Latent Bandits %@Odalric-Ambrym Maillard, Shie Mannor %t2014 %cICML %f/ICML/ICML-2014-1137.pdf %*Fast Allocation of Gaussian Process Experts %@Trung Nguyen, Edwin Bonilla %t2014 %cICML %f/ICML/ICML-2014-1138.pdf %*Von Mises-Fisher Clustering Models %@Siddharth Gopal, Yiming Yang %t2014 %cICML %f/ICML/ICML-2014-1139.pdf %*Von Mises-Fisher Clustering Models %@Siddharth Gopal, Yiming Yang %t2014 %cICML %f/ICML/ICML-2014-1140.pdf %*Convergence rates for persistence diagram estimation in Topological Data Analysis %@Frédéric Chazal, Marc Glisse, Catherine Labruère, Bertrand Michel %t2014 %cICML %f/ICML/ICML-2014-1141.pdf %*Buffer k-d Trees: Processing Massive Nearest Neighbor Queries on GPUs %@Fabian Gieseke, Justin Heinermann, Cosmin Oancea, Christian Igel %t2014 %cICML %f/ICML/ICML-2014-1142.pdf %*Austerity in MCMC Land: Cutting the Metropolis-Hastings Budget %@Anoop Korattikara, Yutian Chen, Max Welling %t2014 %cICML %f/ICML/ICML-2014-1143.pdf %*Austerity in MCMC Land: Cutting the Metropolis-Hastings Budget %@Anoop Korattikara, Yutian Chen, Max Welling %t2014 %cICML %f/ICML/ICML-2014-1144.pdf %*Understanding the Limiting Factors of Topic Modeling via Posterior Contraction Analysis %@Jian Tang, Zhaoshi Meng, Xuanlong Nguyen, Qiaozhu Mei, Ming Zhang %t2014 %cICML %f/ICML/ICML-2014-1145.pdf %*The Inverse Regression Topic Model %@Maxim Rabinovich, David Blei %t2014 %cICML %f/ICML/ICML-2014-1146.pdf %*The Inverse Regression Topic Model %@Maxim Rabinovich, David Blei %t2014 %cICML %f/ICML/ICML-2014-1147.pdf %*A Consistent Histogram Estimator for Exchangeable Graph Models %@Stanley Chan, Edoardo Airoldi %t2014 %cICML %f/ICML/ICML-2014-1148.pdf %*Latent Variable Copula Inference for Bundle Pricing from Retail Transaction Data %@Benjamin Letham, Wei Sun, Anshul Sheopuri %t2014 %cICML %f/ICML/ICML-2014-1149.pdf %*Towards Minimax Online Learning with Unknown Time Horizon %@Haipeng Luo, Robert Schapire %t2014 %cICML %f/ICML/ICML-2014-1150.pdf %*Towards Minimax Online Learning with Unknown Time Horizon %@Haipeng Luo, Robert Schapire %t2014 %cICML %f/ICML/ICML-2014-1151.pdf %*Factorized Point Process Intensities: A Spatial Analysis of Professional Basketball %@Andrew Miller, Luke Bornn, Ryan Adams, Kirk Goldsberry %t2014 %cICML %f/ICML/ICML-2014-1152.pdf %*Factorized Point Process Intensities: A Spatial Analysis of Professional Basketball %@Andrew Miller, Luke Bornn, Ryan Adams, Kirk Goldsberry %t2014 %cICML %f/ICML/ICML-2014-1153.pdf %*Margins, Kernels and Non-linear Smoothed Perceptrons %@Aaditya Ramdas, Javier Peña %t2014 %cICML %f/ICML/ICML-2014-1154.pdf %*Margins, Kernels and Non-linear Smoothed Perceptrons %@Aaditya Ramdas, Javier Peña %t2014 %cICML %f/ICML/ICML-2014-1155.pdf %*Robust RegBayes: Selectively Incorporating First-Order Logic Domain Knowledge into Bayesian Models %@Shike Mei, Jun Zhu, Jerry Zhu %t2014 %cICML %f/ICML/ICML-2014-1156.pdf %*Learning Theory and Algorithms for revenue optimization in second price auctions with reserve %@Mehryar Mohri, Andres Munoz Medina %t2014 %cICML %f/ICML/ICML-2014-1157.pdf %*Learning Theory and Algorithms for revenue optimization in second price auctions with reserve %@Mehryar Mohri, Andres Munoz Medina %t2014 %cICML %f/ICML/ICML-2014-1158.pdf %*Low-density Parity Constraints for Hashing-Based Discrete Integration %@Stefano Ermon, Carla Gomes, Ashish Sabharwal, Bart Selman %t2014 %cICML %f/ICML/ICML-2014-1159.pdf %*Low-density Parity Constraints for Hashing-Based Discrete Integration %@Stefano Ermon, Carla Gomes, Ashish Sabharwal, Bart Selman %t2014 %cICML %f/ICML/ICML-2014-1160.pdf %*Prediction with Limited Advice and Multiarmed Bandits with Paid Observations %@Yevgeny Seldin, Peter Bartlett, Koby Crammer, Yasin Abbasi-Yadkori %t2014 %cICML %f/ICML/ICML-2014-1161.pdf %*Prediction with Limited Advice and Multiarmed Bandits with Paid Observations %@Yevgeny Seldin, Peter Bartlett, Koby Crammer, Yasin Abbasi-Yadkori %t2014 %cICML %f/ICML/ICML-2014-1162.pdf %*Bayesian Nonparametric Multilevel Clustering with Group-Level Contexts %@Tien Vu Nguyen, Dinh Phung, Xuanlong Nguyen, Swetha Venkatesh, Hung Bui %t2014 %cICML %f/ICML/ICML-2014-1163.pdf %*Bayesian Nonparametric Multilevel Clustering with Group-Level Contexts %@Tien Vu Nguyen, Dinh Phung, Xuanlong Nguyen, Swetha Venkatesh, Hung Bui %t2014 %cICML %f/ICML/ICML-2014-1164.pdf %*Large-Margin Metric Learning for Constrained Partitioning Problems %@Rémi Lajugie, Francis Bach, Sylvain Arlot %t2014 %cICML %f/ICML/ICML-2014-1165.pdf %*Wasserstein Propagation for Semi-Supervised Learning %@Justin Solomon, Raif Rustamov, Guibas Leonidas, Adrian Butscher %t2014 %cICML %f/ICML/ICML-2014-1166.pdf %*Max-Margin Infinite Hidden Markov Models %@Aonan Zhang, Jun Zhu, Bo Zhang %t2014 %cICML %f/ICML/ICML-2014-1167.pdf %*Efficient Approximation of Cross-Validation for Kernel Methods using Bouligand Influence Function %@Yong Liu, Shali Jiang, Shizhong Liao %t2014 %cICML %f/ICML/ICML-2014-1168.pdf %*Generalized Exponential Concentration Inequality for Renyi Divergence Estimation %@Shashank Singh, Barnabas Poczos %t2014 %cICML %f/ICML/ICML-2014-1169.pdf %*Boosting with Online Binary Learners for the Multiclass Bandit Problem %@Shang-Tse Chen, Hsuan-Tien Lin, Chi-Jen Lu %t2014 %cICML %f/ICML/ICML-2014-1170.pdf %*Optimal Budget Allocation: Theoretical Guarantee and Efficient Algorithm %@Tasuku Soma, Naonori Kakimura, Kazuhiro Inaba, Ken-ichi Kawarabayashi %t2014 %cICML %f/ICML/ICML-2014-1171.pdf %*Optimal Budget Allocation: Theoretical Guarantee and Efficient Algorithm %@Tasuku Soma, Naonori Kakimura, Kazuhiro Inaba, Ken-ichi Kawarabayashi %t2014 %cICML %f/ICML/ICML-2014-1172.pdf %*Computing Parametric Ranking Models via Rank-Breaking %@Hossein Azari Soufiani, David Parkes, Lirong Xia %t2014 %cICML %f/ICML/ICML-2014-1173.pdf %*Computing Parametric Ranking Models via Rank-Breaking %@Hossein Azari Soufiani, David Parkes, Lirong Xia %t2014 %cICML %f/ICML/ICML-2014-1174.pdf %*Tracking Adversarial Targets %@Yasin Abbasi-Yadkori, Peter Bartlett, Varun Kanade %t2014 %cICML %f/ICML/ICML-2014-1175.pdf %*Tracking Adversarial Targets %@Yasin Abbasi-Yadkori, Peter Bartlett, Varun Kanade %t2014 %cICML %f/ICML/ICML-2014-1176.pdf %*Online Bayesian Passive-Aggressive Learning %@Tianlin Shi, Jun Zhu %t2014 %cICML %f/ICML/ICML-2014-1177.pdf %*Online Bayesian Passive-Aggressive Learning %@Tianlin Shi, Jun Zhu %t2014 %cICML %f/ICML/ICML-2014-1178.pdf %*Deterministic Policy Gradient Algorithms %@David Silver, Guy Lever, Nicolas Heess, Thomas Degris, Daan Wierstra, Martin Riedmiller %t2014 %cICML %f/ICML/ICML-2014-1179.pdf %*Deterministic Policy Gradient Algorithms %@David Silver, Guy Lever, Nicolas Heess, Thomas Degris, Daan Wierstra, Martin Riedmiller %t2014 %cICML %f/ICML/ICML-2014-1180.pdf %*Modeling Correlated Arrival Events with Latent Semi-Markov Processes %@Wenzhao Lian, Vinayak Rao, Brian Eriksson, Lawrence Carin %t2014 %cICML %f/ICML/ICML-2014-1181.pdf %*Modeling Correlated Arrival Events with Latent Semi-Markov Processes %@Wenzhao Lian, Vinayak Rao, Brian Eriksson, Lawrence Carin %t2014 %cICML %f/ICML/ICML-2014-1182.pdf %*Towards scaling up Markov chain Monte Carlo: an adaptive subsampling approach %@Rémi Bardenet, Arnaud Doucet, Chris Holmes %t2014 %cICML %f/ICML/ICML-2014-1183.pdf %*Towards scaling up Markov chain Monte Carlo: an adaptive subsampling approach %@Rémi Bardenet, Arnaud Doucet, Chris Holmes %t2014 %cICML %f/ICML/ICML-2014-1184.pdf %*Diagnosis determination: decision trees optimizing simultaneously worst and expected testing cost %@Ferdinando Cicalese, Eduardo Laber, Aline Medeiros Saettler %t2014 %cICML %f/ICML/ICML-2014-1185.pdf %*Condensed Filter Tree for Cost-Sensitive Multi-Label Classification %@Chun-Liang Li, Hsuan-Tien Lin %t2014 %cICML %f/ICML/ICML-2014-1186.pdf %*Condensed Filter Tree for Cost-Sensitive Multi-Label Classification %@Chun-Liang Li, Hsuan-Tien Lin %t2014 %cICML %f/ICML/ICML-2014-1187.pdf %*On Measure Concentration of Random Maximum A-Posteriori Perturbations %@Francesco Orabona, Tamir Hazan, Anand Sarwate, Tommi Jaakkola %t2014 %cICML %f/ICML/ICML-2014-1188.pdf %*On Measure Concentration of Random Maximum A-Posteriori Perturbations %@Francesco Orabona, Tamir Hazan, Anand Sarwate, Tommi Jaakkola %t2014 %cICML %f/ICML/ICML-2014-1189.pdf %*Bias in Natural Actor-Critic Algorithms %@Philip Thomas %t2014 %cICML %f/ICML/ICML-2014-1190.pdf %*Dimension-free Concentration Bounds on Hankel Matrices for Spectral Learning %@François Denis, Mattias Gybels, Amaury Habrard %t2014 %cICML %f/ICML/ICML-2014-1191.pdf %*On Modelling Non-linear Topical Dependencies %@Zhixing Li, Siqiang Wen, Juanzi Li, Peng Zhang, Jie Tang %t2014 %cICML %f/ICML/ICML-2014-1192.pdf %*A Deep and Tractable Density Estimator %@Benigno Uria, Iain Murray, Hugo Larochelle %t2014 %cICML %f/ICML/ICML-2014-1193.pdf %*(Near) Dimension Independent Risk Bounds for Differentially Private Learning %@Prateek Jain, Abhradeep Guha Thakurta %t2014 %cICML %f/ICML/ICML-2014-1194.pdf %*(Near) Dimension Independent Risk Bounds for Differentially Private Learning %@Prateek Jain, Abhradeep Guha Thakurta %t2014 %cICML %f/ICML/ICML-2014-1195.pdf %*Quasi-Monte Carlo Feature Maps for Shift-Invariant Kernels %@Jiyan Yang, Vikas Sindhwani, Haim Avron, Michael Mahoney %t2014 %cICML %f/ICML/ICML-2014-1196.pdf %*Quasi-Monte Carlo Feature Maps for Shift-Invariant Kernels %@Jiyan Yang, Vikas Sindhwani, Haim Avron, Michael Mahoney %t2014 %cICML %f/ICML/ICML-2014-1197.pdf %*Discriminative Features via Generalized Eigenvectors %@Nikos Karampatziakis, Paul Mineiro %t2014 %cICML %f/ICML/ICML-2014-1198.pdf %*Forward-Backward Greedy Algorithms for General Convex Smooth Functions over A Cardinality Constraint %@Ji Liu, Jieping Ye, Ryohei Fujimaki %t2014 %cICML %f/ICML/ICML-2014-1199.pdf %*Online Learning in Markov Decision Processes with Changing Cost Sequences %@Travis Dick, Andras Gyorgy, Csaba Szepesvari %t2014 %cICML %f/ICML/ICML-2014-1200.pdf %*Online Learning in Markov Decision Processes with Changing Cost Sequences %@Travis Dick, Andras Gyorgy, Csaba Szepesvari %t2014 %cICML %f/ICML/ICML-2014-1201.pdf %*Unimodal Bandits: Regret Lower Bounds and Optimal Algorithms %@Richard Combes, Alexandre Proutiere %t2014 %cICML %f/ICML/ICML-2014-1202.pdf %*Maximum Mean Discrepancy for Class Ratio Estimation: Convergence Bounds and Kernel Selection %@Arun Iyer, Saketha Nath, Sunita Sarawagi %t2014 %cICML %f/ICML/ICML-2014-1203.pdf %*Maximum Mean Discrepancy for Class Ratio Estimation: Convergence Bounds and Kernel Selection %@Arun Iyer, Saketha Nath, Sunita Sarawagi %t2014 %cICML %f/ICML/ICML-2014-1204.pdf %*Asymptotically consistent estimation of the number of change points in highly dependent time series %@Azadeh Khaleghi, Daniil Ryabko %t2014 %cICML %f/ICML/ICML-2014-1205.pdf %*Coordinate-descent for learning orthogonal matrices through Givens rotations %@Uri Shalit, Gal Chechik %t2014 %cICML %f/ICML/ICML-2014-1206.pdf %*Coordinate-descent for learning orthogonal matrices through Givens rotations %@Uri Shalit, Gal Chechik %t2014 %cICML %f/ICML/ICML-2014-1207.pdf %*Densifying One Permutation Hashing via Rotation for Fast Near Neighbor Search %@Anshumali Shrivastava, Ping Li %t2014 %cICML %f/ICML/ICML-2014-1208.pdf %*A Divide-and-Conquer Solver for Kernel Support Vector Machines %@Cho-Jui Hsieh, Si Si, Inderjit Dhillon %t2014 %cICML %f/ICML/ICML-2014-1209.pdf %*A Divide-and-Conquer Solver for Kernel Support Vector Machines %@Cho-Jui Hsieh, Si Si, Inderjit Dhillon %t2014 %cICML %f/ICML/ICML-2014-1210.pdf %*Nuclear Norm Minimization via Active Subspace Selection %@Cho-Jui Hsieh, Peder Olsen %t2014 %cICML %f/ICML/ICML-2014-1211.pdf %*Nuclear Norm Minimization via Active Subspace Selection %@Cho-Jui Hsieh, Peder Olsen %t2014 %cICML %f/ICML/ICML-2014-1212.pdf %*Provable Bounds for Learning Some Deep Representations %@Sanjeev Arora, Aditya Bhaskara, Rong Ge, Tengyu Ma %t2014 %cICML %f/ICML/ICML-2014-1213.pdf %*Large-scale Multi-label Learning with Missing Labels %@Hsiang-Fu Yu, Prateek Jain, Purushottam Kar, Inderjit Dhillon %t2014 %cICML %f/ICML/ICML-2014-1214.pdf %*Large-scale Multi-label Learning with Missing Labels %@Hsiang-Fu Yu, Prateek Jain, Purushottam Kar, Inderjit Dhillon %t2014 %cICML %f/ICML/ICML-2014-1215.pdf %*Learning Graphs with a Few Hubs %@Rashish Tandon, Pradeep Ravikumar %t2014 %cICML %f/ICML/ICML-2014-1216.pdf %*Learning Graphs with a Few Hubs %@Rashish Tandon, Pradeep Ravikumar %t2014 %cICML %f/ICML/ICML-2014-1217.pdf %*Agnostic Bayesian Learning of Ensembles %@Alexandre Lacoste, Mario Marchand, Franois Laviolette, Hugo Larochelle %t2014 %cICML %f/ICML/ICML-2014-1218.pdf %*Agnostic Bayesian Learning of Ensembles %@Alexandre Lacoste, Mario Marchand, Franois Laviolette, Hugo Larochelle %t2014 %cICML %f/ICML/ICML-2014-1219.pdf %*Towards an optimal stochastic alternating direction method of multipliers %@Samaneh Azadi, Suvrit Sra %t2014 %cICML %f/ICML/ICML-2014-1220.pdf %*Towards an optimal stochastic alternating direction method of multipliers %@Samaneh Azadi, Suvrit Sra %t2014 %cICML %f/ICML/ICML-2014-1221.pdf %*Spherical Hamiltonian Monte Carlo for Constrained Target Distributions %@Shiwei Lan, Bo Zhou, Babak Shahbaba %t2014 %cICML %f/ICML/ICML-2014-1222.pdf %*Efficient Continuous-Time Markov Chain Estimation %@Monir Hajiaghayi, Bonnie Kirkpatrick, Liangliang Wang, Alexandre Bouchard-Côté %t2014 %cICML %f/ICML/ICML-2014-1223.pdf %*Efficient Continuous-Time Markov Chain Estimation %@Monir Hajiaghayi, Bonnie Kirkpatrick, Liangliang Wang, Alexandre Bouchard-Côté %t2014 %cICML %f/ICML/ICML-2014-1224.pdf %*DeCAF: A Deep Convolutional Activation Feature for Generic Visual Recognition %@Jeff Donahue, Yangqing Jia, Oriol Vinyals, Judy Hoffman, Ning Zhang, Eric Tzeng, Trevor Darrell %t2014 %cICML %f/ICML/ICML-2014-1225.pdf %*Making the Most of Bag of Words: Sentence Regularization with Alternating Direction Method of Multipliers %@Dani Yogatama, Noah Smith %t2014 %cICML %f/ICML/ICML-2014-1226.pdf %*Narrowing the Gap: Random Forests In Theory and In Practice %@Misha Denil, David Matheson, Nando De Freitas %t2014 %cICML %f/ICML/ICML-2014-1227.pdf %*Narrowing the Gap: Random Forests In Theory and In Practice %@Misha Denil, David Matheson, Nando De Freitas %t2014 %cICML %f/ICML/ICML-2014-1228.pdf %*Coherent Matrix Completion %@Yudong Chen, Srinadh Bhojanapalli, Sujay Sanghavi, Rachel Ward %t2014 %cICML %f/ICML/ICML-2014-1229.pdf %*Coherent Matrix Completion %@Yudong Chen, Srinadh Bhojanapalli, Sujay Sanghavi, Rachel Ward %t2014 %cICML %f/ICML/ICML-2014-1230.pdf %*Admixture of Poisson MRFs: A Topic Model with Word Dependencies %@David Inouye, Pradeep Ravikumar, Inderjit Dhillon %t2014 %cICML %f/ICML/ICML-2014-1231.pdf %*Admixture of Poisson MRFs: A Topic Model with Word Dependencies %@David Inouye, Pradeep Ravikumar, Inderjit Dhillon %t2014 %cICML %f/ICML/ICML-2014-1232.pdf %*True Online TD(lambda) %@Harm van Seijen, Rich Sutton %t2014 %cICML %f/ICML/ICML-2014-1233.pdf %*Memory Efficient Kernel Approximation %@Si Si, Cho-Jui Hsieh, Inderjit Dhillon %t2014 %cICML %f/ICML/ICML-2014-1234.pdf %*Memory Efficient Kernel Approximation %@Si Si, Cho-Jui Hsieh, Inderjit Dhillon %t2014 %cICML %f/ICML/ICML-2014-1235.pdf %*Learning Sum-Product Networks with Direct and Indirect Variable Interactions %@Amirmohammad Rooshenas, Daniel Lowd %t2014 %cICML %f/ICML/ICML-2014-1236.pdf %*Learning Sum-Product Networks with Direct and Indirect Variable Interactions %@Amirmohammad Rooshenas, Daniel Lowd %t2014 %cICML %f/ICML/ICML-2014-1237.pdf %*Hamiltonian Monte Carlo Without Detailed Balance %@Jascha Sohl-Dickstein, Mayur Mudigonda, Michael DeWeese %t2014 %cICML %f/ICML/ICML-2014-1238.pdf %*Filtering with Abstract Particles %@Jacob Steinhardt, Percy Liang %t2014 %cICML %f/ICML/ICML-2014-1239.pdf %*Filtering with Abstract Particles %@Jacob Steinhardt, Percy Liang %t2014 %cICML %f/ICML/ICML-2014-1240.pdf %*Stochastic Dual Coordinate Ascent with Alternating Direction Method of Multipliers %@Taiji Suzuki %t2014 %cICML %f/ICML/ICML-2014-1241.pdf %*Stochastic Dual Coordinate Ascent with Alternating Direction Method of Multipliers %@Taiji Suzuki %t2014 %cICML %f/ICML/ICML-2014-1242.pdf %*Deep Supervised and Convolutional Generative Stochastic Network for Protein Secondary Structure Prediction %@Jian Zhou, Olga Troyanskaya %t2014 %cICML %f/ICML/ICML-2014-1243.pdf %*An Efficient Approach for Assessing Hyperparameter Importance %@Frank Hutter, Holger Hoos, Kevin Leyton-Brown %t2014 %cICML %f/ICML/ICML-2014-1244.pdf %*An Efficient Approach for Assessing Hyperparameter Importance %@Frank Hutter, Holger Hoos, Kevin Leyton-Brown %t2014 %cICML %f/ICML/ICML-2014-1245.pdf %*Global Graph Kernels Using Geometric Embeddings %@Fredrik Johansson, Vinay Jethava, Devdatt Dubhashi, Chiranjib Bhattacharyya %t2014 %cICML %f/ICML/ICML-2014-1246.pdf %*Global Graph Kernels Using Geometric Embeddings %@Fredrik Johansson, Vinay Jethava, Devdatt Dubhashi, Chiranjib Bhattacharyya %t2014 %cICML %f/ICML/ICML-2014-1247.pdf %*Topic Modeling using Topics from Many Domains, Lifelong Learning and Big Data %@Zhiyuan Chen, Bing Liu %t2014 %cICML %f/ICML/ICML-2014-1248.pdf %*K-means Recovers ICA Filters when Independent Components are Sparse %@Alon Vinnikov, Shai Shalev-Shwartz %t2014 %cICML %f/ICML/ICML-2014-1249.pdf %*Learning Mixtures of Linear Classifiers %@Yuekai Sun, Stratis Ioannidis, Andrea Montanari %t2014 %cICML %f/ICML/ICML-2014-1250.pdf %*Learning Mixtures of Linear Classifiers %@Yuekai Sun, Stratis Ioannidis, Andrea Montanari %t2014 %cICML %f/ICML/ICML-2014-1251.pdf %*The Falling Factorial Basis and Its Statistical Applications %@Yu-Xiang Wang, Ryan Tibshirani, Alex Smola %t2014 %cICML %f/ICML/ICML-2014-1252.pdf %*The Falling Factorial Basis and Its Statistical Applications %@Yu-Xiang Wang, Ryan Tibshirani, Alex Smola %t2014 %cICML %f/ICML/ICML-2014-1253.pdf %*Nonmyopic $\epsilon$-Bayes-Optimal Active Learning of Gaussian Processes %@Trong Nghia Hoang, Bryan Kian Hsiang Low, Patrick Jaillet, Mohan Kankanhalli %t2014 %cICML %f/ICML/ICML-2014-1254.pdf %*A Unifying View of Representer Theorems %@Andreas Argyriou, Francesco Dinuzzo %t2014 %cICML %f/ICML/ICML-2014-1255.pdf %*A Unifying View of Representer Theorems %@Andreas Argyriou, Francesco Dinuzzo %t2014 %cICML %f/ICML/ICML-2014-1256.pdf %*Online Clustering of Bandits %@Claudio Gentile, Shuai Li, Giovanni Zappella %t2014 %cICML %f/ICML/ICML-2014-1257.pdf %*Online Clustering of Bandits %@Claudio Gentile, Shuai Li, Giovanni Zappella %t2014 %cICML %f/ICML/ICML-2014-1258.pdf %*Cold-start Active Learning with Robust Ordinal Matrix Factorization %@Neil Houlsby, Jose Miguel Hernandez-Lobato, Zoubin Ghahramani %t2014 %cICML %f/ICML/ICML-2014-1259.pdf %*Multivariate Maximal Correlation Analysis %@Hoang Vu Nguyen, Emmanuel Müller, Jilles Vreeken, Pavel Efros, Klemens Böhm %t2014 %cICML %f/ICML/ICML-2014-1260.pdf %*Efficient Label Propagation %@Yasuhiro Fujiwara, Go Irie %t2014 %cICML %f/ICML/ICML-2014-1261.pdf %*Estimating Diffusion Network Structures: Recovery Conditions, Sample Complexity & Soft-thresholding Algorithm %@Hadi Daneshmand, Manuel Gomez-Rodriguez, Le Song, Bernhard Schoelkopf %t2014 %cICML %f/ICML/ICML-2014-1262.pdf %*Coupled Group Lasso for Web-Scale CTR Prediction in Display Advertising %@Ling Yan, Wu-Jun Li, Gui-Rong Xue, Dingyi Han %t2014 %cICML %f/ICML/ICML-2014-1263.pdf %*Putting MRFs on a Tensor Train %@Alexander Novikov, Anton Rodomanov, Anton Osokin, Dmitry Vetrov %t2014 %cICML %f/ICML/ICML-2014-1264.pdf %*Putting MRFs on a Tensor Train %@Alexander Novikov, Anton Rodomanov, Anton Osokin, Dmitry Vetrov %t2014 %cICML %f/ICML/ICML-2014-1265.pdf %*Efficient Algorithms for Robust One-bit Compressive Sensing %@Lijun Zhang, Jinfeng Yi, Rong Jin %t2014 %cICML %f/ICML/ICML-2014-1266.pdf %*Learning Complex Neural Network Policies with Trajectory Optimization %@Sergey Levine, Vladlen Koltun %t2014 %cICML %f/ICML/ICML-2014-1267.pdf %*Composite Quantization for Approximate Nearest Neighbor Search %@Ting Zhang, Chao Du, Jingdong Wang %t2014 %cICML %f/ICML/ICML-2014-1268.pdf %*Local Ordinal Embedding %@Yoshikazu Terada, Ulrike von Luxburg %t2014 %cICML %f/ICML/ICML-2014-1269.pdf %*Reducing Dueling Bandits to Cardinal Bandits %@Nir Ailon, Zohar Karnin, Thorsten Joachims %t2014 %cICML %f/ICML/ICML-2014-1270.pdf %*Large-margin Weakly Supervised Dimensionality Reduction %@Chang Xu, Dacheng Tao, Chao Xu, Yong Rui %t2014 %cICML %f/ICML/ICML-2014-1271.pdf %*Large-margin Weakly Supervised Dimensionality Reduction %@Chang Xu, Dacheng Tao, Chao Xu, Yong Rui %t2014 %cICML %f/ICML/ICML-2014-1272.pdf %*Joint Inference of Multiple Label Types in Large Networks %@Deepayan Chakrabarti, Stanislav Funiak, Jonathan Chang, Sofus Macskassy %t2014 %cICML %f/ICML/ICML-2014-1273.pdf %*Hard-margin Active Linear Regression %@Zohar Karnin, Elad Hazan %t2014 %cICML %f/ICML/ICML-2014-1274.pdf %*Maximum Margin Multiclass Nearest Neighbors %@Aryeh Kontorovich, Roi Weiss %t2014 %cICML %f/ICML/ICML-2014-1275.pdf %*Combinatorial Partial Monitoring Game with Linear Feedback and Its Applications %@Tian Lin, Bruno Abrahao, Robert Kleinberg, John Lui, Wei Chen %t2014 %cICML %f/ICML/ICML-2014-1276.pdf %*Sparse Meta-Gaussian Information Bottleneck %@Melani Rey, Volker Roth, Thomas Fuchs %t2014 %cICML %f/ICML/ICML-2014-1277.pdf %*Nonparametric Estimation of Renyi Divergence and Friends %@Akshay Krishnamurthy, Kirthevasan Kandasamy, Barnabas Poczos, Larry Wasserman %t2014 %cICML %f/ICML/ICML-2014-1278.pdf %*Nonparametric Estimation of Renyi Divergence and Friends %@Akshay Krishnamurthy, Kirthevasan Kandasamy, Barnabas Poczos, Larry Wasserman %t2014 %cICML %f/ICML/ICML-2014-1279.pdf %*Robust Inverse Covariance Estimation under Noisy Measurements %@Jun-Kun Wang, Ting-Wei Lin, Shou-de Lin %t2014 %cICML %f/ICML/ICML-2014-1280.pdf %*Bayesian Optimization with Inequality Constraints %@Jacob Gardner, Matt Kusner, Kilian Weinberger, John Cunningham, Zhixiang (Eddie) Xu %t2014 %cICML %f/ICML/ICML-2014-1281.pdf %*Circulant Binary Embedding %@Felix Yu, Sanjiv Kumar, Yunchao Gong, Shih-Fu Chang %t2014 %cICML %f/ICML/ICML-2014-1282.pdf %*Multiple Testing under Dependence via Semiparametric Graphical Models %@Jie Liu, Chunming Zhang, Elizabeth Burnside, David Page %t2014 %cICML %f/ICML/ICML-2014-1283.pdf %*Making Fisher Discriminant Analysis Scalable %@Bojun Tu, Hui Qian, Zhihua Zhang %t2014 %cICML %f/ICML/ICML-2014-1284.pdf %*Hierarchical Dirichlet Scaling Process %@Dongwoo Kim, Alice Oh %t2014 %cICML %f/ICML/ICML-2014-1285.pdf %*Hierarchical Dirichlet Scaling Process %@Dongwoo Kim, Alice Oh %t2014 %cICML %f/ICML/ICML-2014-1286.pdf %*Approximation Analysis of Stochastic Gradient Langevin Dynamics by using Fokker-Planck Equation and Ito Process %@Issei Sato, Hiroshi Nakagawa %t2014 %cICML %f/ICML/ICML-2014-1287.pdf %*A PAC-Bayesian Bound for Lifelong Learning %@Anastasia Pentina, Christoph Lampert %t2014 %cICML %f/ICML/ICML-2014-1288.pdf %*Communication-Efficient Distributed Optimization using an Approximate Newton-type Method %@Ohad Shamir, Nati Srebro, Tong Zhang %t2014 %cICML %f/ICML/ICML-2014-1289.pdf %*Communication-Efficient Distributed Optimization using an Approximate Newton-type Method %@Ohad Shamir, Nati Srebro, Tong Zhang %t2014 %cICML %f/ICML/ICML-2014-1290.pdf %*Concept Drift Detection Through Resampling %@Maayan Harel, Shie Mannor, Ran El-Yaniv, Koby Crammer %t2014 %cICML %f/ICML/ICML-2014-1291.pdf %*Concept Drift Detection Through Resampling %@Maayan Harel, Shie Mannor, Ran El-Yaniv, Koby Crammer %t2014 %cICML %f/ICML/ICML-2014-1292.pdf %*Anti-differentiating Approximation Algorithms: A case study with Min-cuts, Spectral, and Flow %@David Gleich, Michael Mahoney %t2014 %cICML %f/ICML/ICML-2014-1293.pdf %*A Bayesian Wilcoxon Signed-rank Test Based on the Dirichlet Process %@Alessio Benavoli, Giorgio Corani, Francesca Mangili, Marco Zaffalon, Fabrizio Ruggeri %t2014 %cICML %f/ICML/ICML-2014-1294.pdf %*A Bayesian Wilcoxon Signed-rank Test Based on the Dirichlet Process %@Alessio Benavoli, Giorgio Corani, Francesca Mangili, Marco Zaffalon, Fabrizio Ruggeri %t2014 %cICML %f/ICML/ICML-2014-1295.pdf %*Min-Max Problems on Factor Graphs %@Siamak Ravanbakhsh, Christopher Srinivasa, Brendan Frey, Russell Greiner %t2014 %cICML %f/ICML/ICML-2014-1296.pdf %*Min-Max Problems on Factor Graphs %@Siamak Ravanbakhsh, Christopher Srinivasa, Brendan Frey, Russell Greiner %t2014 %cICML %f/ICML/ICML-2014-1297.pdf %*Distributed Stochastic Gradient MCMC %@Sungjin Ahn, Babak Shahbaba, Max Welling %t2014 %cICML %f/ICML/ICML-2014-1298.pdf %*Distributed Stochastic Gradient MCMC %@Sungjin Ahn, Babak Shahbaba, Max Welling %t2014 %cICML %f/ICML/ICML-2014-1299.pdf %*Nearest Neighbors Using Compact Sparse Codes %@Anoop Cherian %t2014 %cICML %f/ICML/ICML-2014-1300.pdf %*Optimal Mean Robust Principal Component Analysis %@Feiping Nie, Jianjun Yuan, Heng Huang %t2014 %cICML %f/ICML/ICML-2014-1301.pdf %*Preference-Based Rank Elicitation using Statistical Models: The Case of Mallows %@Robert Busa-Fekete, Balázs Szörényi, Eyke Huellermeier %t2014 %cICML %f/ICML/ICML-2014-1302.pdf %*Preference-Based Rank Elicitation using Statistical Models: The Case of Mallows %@Robert Busa-Fekete, Balázs Szörényi, Eyke Huellermeier %t2014 %cICML %f/ICML/ICML-2014-1303.pdf %*Hierarchical Conditional Random Fields for Outlier Detection: An Application to Detecting Epileptogenic Cortical Malformations %@Bilal Ahmed, Karen Blackmon, Thomas Thesen, Ruben Kuzniecky, Chad Carlson, Jacqueline French, Werner Doyle, Carla Brodley %t2014 %cICML %f/ICML/ICML-2014-1304.pdf %*A Physics-Based Model Prior for Object-Oriented MDPs %@Jonathan Scholz, Martin Levihn, Charles Isbell %t2014 %cICML %f/ICML/ICML-2014-1305.pdf %*Outlier Path: A Homotopy Algorithm for Robust SVM %@Shinya Suzumura, Kohei Ogawa, Masashi Sugiyama, Ichiro Takeuchi %t2014 %cICML %f/ICML/ICML-2014-1306.pdf %*Outlier Path: A Homotopy Algorithm for Robust SVM %@Shinya Suzumura, Kohei Ogawa, Masashi Sugiyama, Ichiro Takeuchi %t2014 %cICML %f/ICML/ICML-2014-1307.pdf %*Ensemble-Based Tracking: Aggregating Crowdsourced Structured Time Series Data %@Naiyan Wang, Dit-Yan Yeung %t2014 %cICML %f/ICML/ICML-2014-1308.pdf %*Ensemble-Based Tracking: Aggregating Crowdsourced Structured Time Series Data %@Naiyan Wang, Dit-Yan Yeung %t2014 %cICML %f/ICML/ICML-2014-1309.pdf %*Latent Confusion Analysis by Normalized Gamma Construction %@Issei Sato, Kashima Hisashi, Hiroshi Nakagawa %t2014 %cICML %f/ICML/ICML-2014-1310.pdf %*Latent Confusion Analysis by Normalized Gamma Construction %@Issei Sato, Kashima Hisashi, Hiroshi Nakagawa %t2014 %cICML %f/ICML/ICML-2014-1311.pdf %*Finito: A Faster, Permutable Incremental Gradient Method for Big Data Problems %@Aaron Defazio, Justin Domke, Tiberio Caetano %t2014 %cICML %f/ICML/ICML-2014-1312.pdf %*Ensemble Methods for Structured Prediction %@Corinna Cortes, Vitaly Kuznetsov, Mehryar Mohri %t2014 %cICML %f/ICML/ICML-2014-1313.pdf %*Standardized Mutual Information for Clustering Comparisons: One Step Further in Adjustment for Chance %@Simone Romano, James Bailey, Vinh Nguyen, Karin Verspoor %t2014 %cICML %f/ICML/ICML-2014-1314.pdf %*Standardized Mutual Information for Clustering Comparisons: One Step Further in Adjustment for Chance %@Simone Romano, James Bailey, Vinh Nguyen, Karin Verspoor %t2014 %cICML %f/ICML/ICML-2014-1315.pdf %*Preserving Modes and Messages via Diverse Particle Selection %@Jason Pacheco, Silvia Zuffi, Michael Black, Erik Sudderth %t2014 %cICML %f/ICML/ICML-2014-1316.pdf %*Nonlinear Information-Theoretic Compressive Measurement Design %@Liming Wang, Abolfazl Razi, Miguel Rodrigues, Robert Calderbank, Lawrence Carin %t2014 %cICML %f/ICML/ICML-2014-1317.pdf %*Dual Query: Practical Private Query Release for High Dimensional Data %@Marco Gaboardi Emilio Jesus Gallego Arias, Justin Hsu, Aaron Roth, Zhiwei Steven Wu %t2014 %cICML %f/ICML/ICML-2014-1318.pdf %*Deep Boosting %@Corinna Cortes, Mehryar Mohri, Umar Syed %t2014 %cICML %f/ICML/ICML-2014-1319.pdf %*Distributed Representations of Sentences and Documents %@Quoc Le, Tomas Mikolov %t2014 %cICML %f/ICML/ICML-2014-1320.pdf %*Understanding Protein Dynamics with L1-Regularized Reversible Hidden Markov Models %@Robert McGibbon, Bharath Ramsundar, Mohammad Sultan, Gert Kiss, Vijay Pande %t2014 %cICML %f/ICML/ICML-2014-1321.pdf %*Online Multi-Task Learning for Policy Gradient Methods %@Haitham Bou Ammar, Eric Eaton, Paul Ruvolo, Matthew Taylor %t2014 %cICML %f/ICML/ICML-2014-1322.pdf %*Affinity Weighted Embedding %@Jason Weston, Ron Weiss, Hector Yee %t2014 %cICML %f/ICML/ICML-2014-1323.pdf %*Learning the Parameters of Determinantal Point Process Kernels %@Raja Hafiz Affandi, Emily Fox, Ryan Adams, Ben Taskar %t2014 %cICML %f/ICML/ICML-2014-1324.pdf %*Learning the Parameters of Determinantal Point Process Kernels %@Raja Hafiz Affandi, Emily Fox, Ryan Adams, Ben Taskar %t2014 %cICML %f/ICML/ICML-2014-1325.pdf %*Discrete Chebyshev Classifiers %@Elad Eban, Elad Mezuman, Amir Globerson %t2014 %cICML %f/ICML/ICML-2014-1326.pdf %*Deep AutoRegressive Networks %@Karol Gregor, Ivo Danihelka, Andriy Mnih, Charles Blundell, Daan Wierstra %t2014 %cICML %f/ICML/ICML-2014-1327.pdf %*Deep AutoRegressive Networks %@Karol Gregor, Ivo Danihelka, Andriy Mnih, Charles Blundell, Daan Wierstra %t2014 %cICML %f/ICML/ICML-2014-1328.pdf %*A Convergence Rate Analysis for LogitBoost, MART and Their Variant %@Peng Sun, Tong Zhang, Jie Zhou %t2014 %cICML %f/ICML/ICML-2014-1329.pdf %*A Convergence Rate Analysis for LogitBoost, MART and Their Variant %@Peng Sun, Tong Zhang, Jie Zhou %t2014 %cICML %f/ICML/ICML-2014-1330.pdf %*Inferning with High Girth Graphical Models %@Uri Heinemann, Amir Globerson %t2014 %cICML %f/ICML/ICML-2014-1331.pdf %*Inferning with High Girth Graphical Models %@Uri Heinemann, Amir Globerson %t2014 %cICML %f/ICML/ICML-2014-1332.pdf %*Learning Latent Variable Gaussian Graphical Models %@Zhaoshi Meng, Brian Eriksson, Al Hero %t2014 %cICML %f/ICML/ICML-2014-1333.pdf %*Stochastic Backpropagation and Approximate Inference in Deep Generative Models %@Danilo Jimenez Rezende, Shakir Mohamed, Daan Wierstra %t2014 %cICML %f/ICML/ICML-2014-1334.pdf %*Stochastic Backpropagation and Approximate Inference in Deep Generative Models %@Danilo Jimenez Rezende, Shakir Mohamed, Daan Wierstra %t2014 %cICML %f/ICML/ICML-2014-1335.pdf %*One Practical Algorithm for Both Stochastic and Adversarial Bandits %@Yevgeny Seldin, Aleksandrs Slivkins %t2014 %cICML %f/ICML/ICML-2014-1336.pdf %*One Practical Algorithm for Both Stochastic and Adversarial Bandits %@Yevgeny Seldin, Aleksandrs Slivkins %t2014 %cICML %f/ICML/ICML-2014-1337.pdf %*Robust and Efficient Kernel Hyperparameter Paths with Guarantees %@Joachim Giesen, Soeren Laue, Patrick Wieschollek %t2014 %cICML %f/ICML/ICML-2014-1338.pdf %*Active Transfer Learning under Model Shift %@Xuezhi Wang, Tzu-Kuo Huang, Jeff Schneider %t2014 %cICML %f/ICML/ICML-2014-1339.pdf %*Approximate Policy Iteration Schemes: A Comparison %@Bruno Scherrer %t2014 %cICML %f/ICML/ICML-2014-1340.pdf %*Robust and Efficient Representation Learning with Nonnegativity Constraints %@Tsung-Han Lin %t2014 %cICML %f/ICML/ICML-2014-1341.pdf %*Sample Efficient Reinforcement Learning with Gaussian Processes %@Robert Grande, Thomas Walsh, Jonathan How %t2014 %cICML %f/ICML/ICML-2014-1342.pdf %*Memory and Computation Efficient PCA via Very Sparse Random Projections %@Farhad Pourkamali Anaraki, Shannon Hughes %t2014 %cICML %f/ICML/ICML-2014-1343.pdf %*Time-Regularized Interrupting Options (TRIO) %@Timothy Mann, Daniel Mankowitz, Shie Mannor %t2014 %cICML %f/ICML/ICML-2014-1344.pdf %*Time-Regularized Interrupting Options (TRIO) %@Timothy Mann, Daniel Mankowitz, Shie Mannor %t2014 %cICML %f/ICML/ICML-2014-1345.pdf %*Randomized Nonlinear Component Analysis %@David Lopez-Paz, Suvrit Sra, Alex Smola, Zoubin Ghahramani, Bernhard Schoelkopf %t2014 %cICML %f/ICML/ICML-2014-1346.pdf %*High Order Regularization for Semi-Supervised Learning of Structured Output Problems %@Yujia Li, Rich Zemel %t2014 %cICML %f/ICML/ICML-2014-1347.pdf %*Transductive Learning with Multi-class Volume Approximation %@Gang Niu, Bo Dai, Christoffel du Plessis, Masashi Sugiyama %t2014 %cICML %f/ICML/ICML-2014-1348.pdf %*Methods of Moments for Learning Stochastic Languages: Unified Presentation and Empirical Comparison %@Borja Balle, William Hamilton, Joelle Pineau %t2014 %cICML %f/ICML/ICML-2014-1349.pdf %*Methods of Moments for Learning Stochastic Languages: Unified Presentation and Empirical Comparison %@Borja Balle, William Hamilton, Joelle Pineau %t2014 %cICML %f/ICML/ICML-2014-1350.pdf %*Effective Bayesian Modeling of Groups of Related Count Time Series %@Nicolas Chapados %t2014 %cICML %f/ICML/ICML-2014-1351.pdf %*Effective Bayesian Modeling of Groups of Related Count Time Series %@Nicolas Chapados %t2014 %cICML %f/ICML/ICML-2014-1352.pdf %*Variational Inference for Sequential Distance Dependent Chinese Restaurant Process %@Sergey Bartunov, Dmitry Vetrov %t2014 %cICML %f/ICML/ICML-2014-1353.pdf %*Discovering Latent Network Structure in Point Process Data %@Scott Linderman, Ryan Adams %t2014 %cICML %f/ICML/ICML-2014-1354.pdf %*A Kernel Independence Test for Random Processes %@Kacper Chwialkowski, Arthur Gretton %t2014 %cICML %f/ICML/ICML-2014-1355.pdf %*Learning Representations for Interacting Manifolds with Higher-order Boltzmann Machines %@Scott Reed, Kihyuk Sohn, Yuting Zhang, Honglak Lee %t2014 %cICML %f/ICML/ICML-2014-1356.pdf %*Learning Modular Structures from Network Data and Node Variables %@Elham Azizi, Edoardo Airoldi %t2014 %cICML %f/ICML/ICML-2014-1357.pdf %*Probabilistic Partial Canonical Correlation Analysis %@Yusuke Mukuta, Tatsuya Harada %t2014 %cICML %f/ICML/ICML-2014-1358.pdf %*Probabilistic Partial Canonical Correlation Analysis %@Yusuke Mukuta, Tatsuya Harada %t2014 %cICML %f/ICML/ICML-2014-1359.pdf %*Skip Context Tree Switching %@Marc Bellemare, Joel Veness, Erik Talvitie, Alex Graves %t2014 %cICML %f/ICML/ICML-2014-1360.pdf %*Skip Context Tree Switching %@Marc Bellemare, Joel Veness, Erik Talvitie, Alex Graves %t2014 %cICML %f/ICML/ICML-2014-1361.pdf %*Lower Bounds for the Gibbs Sampler over Mixtures of Gaussians %@Christopher Tosh, Sanjoy Dasgupta %t2014 %cICML %f/ICML/ICML-2014-1362.pdf %*Marginalized Denoising Auto-encoders for Nonlinear Representations %@Minmin Chen, Kilian Weinberger, Fei Sha, Yoshua Bengio %t2014 %cICML %f/ICML/ICML-2014-1363.pdf %*Gaussian Processes for Bayesian Estimation in Ordinary Differential Equations %@David Barber, Yali Wang %t2014 %cICML %f/ICML/ICML-2014-1364.pdf %*Fast Multi-stage Submodular Maximization %@Kai Wei, Rishabh Iyer, Jeff Bilmes %t2014 %cICML %f/ICML/ICML-2014-1365.pdf %*Fast Multi-stage Submodular Maximization %@Kai Wei, Rishabh Iyer, Jeff Bilmes %t2014 %cICML %f/ICML/ICML-2014-1366.pdf %*Programming by Feedback %@Marc Schoenauer, Riad Akrour, Michele Sebag, Jean-Christophe Souplet %t2014 %cICML %f/ICML/ICML-2014-1367.pdf %*Probabilistic Matrix Factorization with Non-random Missing Data %@Jose Miguel Hernandez-Lobato, Neil Houlsby, Zoubin Ghahramani %t2014 %cICML %f/ICML/ICML-2014-1368.pdf %*Pursuit-Evasion Without Regrets, with an Application to Trading %@Lili Dworkin, Michael Kearns, Yuriy Nevmyvaka %t2014 %cICML %f/ICML/ICML-2014-1369.pdf %*The f-Adjusted Laplacian: a Diagonal Perturbation with a Geometric Interpretation %@Sven Kurras, Ulrike von Luxburg, Gilles Blanchard %t2014 %cICML %f/ICML/ICML-2014-1370.pdf %*The f-Adjusted Laplacian: a Diagonal Perturbation with a Geometric Interpretation %@Sven Kurras, Ulrike von Luxburg, Gilles Blanchard %t2014 %cICML %f/ICML/ICML-2014-1371.pdf %*Riemannian Pursuit for Big Matrix Recovery %@Mingkui Tan, Ivor W. Tsang, Li Wang, Jialin Pan, Bart Vandereycken %t2014 %cICML %f/ICML/ICML-2014-1372.pdf %*Dynamic Programming Boosting for Discriminative Macro-Action Discovery %@Leonidas Lefakis, Francois Fleuret %t2014 %cICML %f/ICML/ICML-2014-1373.pdf %*Resource-Efficient Stochastic Optimization of a Locally Smooth Function under Correlated Bandit Feedback %@Mohammad Gheshlaghi azar, Alessandro Lazaric, Emma Brunskill %t2014 %cICML %f/ICML/ICML-2014-1374.pdf %*Weighted Graph Clustering with Non-Uniform Uncertainties %@Yudong Chen, Shiau Hong Lim, Huan Xu %t2014 %cICML %f/ICML/ICML-2014-1375.pdf %*Weighted Graph Clustering with Non-Uniform Uncertainties %@Yudong Chen, Shiau Hong Lim, Huan Xu %t2014 %cICML %f/ICML/ICML-2014-1376.pdf %*GeNGA: A Generalization of Natural Gradient Ascent with Positive and Negative Convergence Results %@Philip Thomas %t2014 %cICML %f/ICML/ICML-2014-1377.pdf %*A Bayesian Framework for Online Classifier Ensemble %@Qinxun Bai, Henry Lam, Stan Sclaroff %t2014 %cICML %f/ICML/ICML-2014-1378.pdf %*A Bayesian Framework for Online Classifier Ensemble %@Qinxun Bai, Henry Lam, Stan Sclaroff %t2014 %cICML %f/ICML/ICML-2014-1379.pdf %*Adaptivity and Optimism: An Improved Exponentiated Gradient Algorithm %@Jacob Steinhardt, Percy Liang %t2014 %cICML %f/ICML/ICML-2014-1380.pdf %*Gaussian Approximation of Collective Graphical Models %@Liping Liu, Daniel Sheldon, Thomas Dietterich %t2014 %cICML %f/ICML/ICML-2014-1381.pdf %*One-Bit Object Detection: On Learning to Localize Objects with Minimal Supervision %@Hyun Oh Song, Ross Girshick, Stefanie Jegelka, Julien Mairal, Zaid Harchaoui, Trevor Darrell %t2014 %cICML %f/ICML/ICML-2014-1382.pdf %*Multiresolution Matrix Factorization %@Risi Kondor, Nedelina Teneva, Vikas Garg %t2014 %cICML %f/ICML/ICML-2014-1383.pdf %*Multiresolution Matrix Factorization %@Risi Kondor, Nedelina Teneva, Vikas Garg %t2014 %cICML %f/ICML/ICML-2014-1384.pdf %*Learnability of the Superset Label Learning Problem %@Liping Liu, Thomas Dietterich %t2014 %cICML %f/ICML/ICML-2014-1385.pdf %*Taming the Monster: A Fast and Simple Algorithm for Contextual Bandits %@Alekh Agarwal, Daniel Hsu, Satyen Kale, John Langford, Lihong Li, Robert Schapire %t2014 %cICML %f/ICML/ICML-2014-1386.pdf %*Structured Recurrent Temporal Restricted Boltzmann Machines %@Roni Mittelman, Benjamin Kuipers, Silvio Savarese, Honglak Lee %t2014 %cICML %f/ICML/ICML-2014-1387.pdf %*Scalable and Robust Bayesian Inference via the Median Posterior %@Stanislav Minsker, Sanvesh Srivastava, Lizhen Lin, David Dunson %t2014 %cICML %f/ICML/ICML-2014-1388.pdf %*Scalable and Robust Bayesian Inference via the Median Posterior %@Stanislav Minsker, Sanvesh Srivastava, Lizhen Lin, David Dunson %t2014 %cICML %f/ICML/ICML-2014-1389.pdf %*Kernel Adaptive Metropolis-Hastings %@Dino Sejdinovic, Heiko Strathmann, Maria Lomeli Garcia, Christophe Andrieu, Arthur Gretton %t2014 %cICML %f/ICML/ICML-2014-1390.pdf %*Input Warping for Bayesian Optimization of Non-stationary Functions %@Jasper Snoek, Kevin Swersky, Rich Zemel, Ryan Adams %t2014 %cICML %f/ICML/ICML-2014-1391.pdf %*Stochastic Gradient Hamiltonian Monte Carlo %@Tianqi Chen, Emily Fox, Carlos Guestrin %t2014 %cICML %f/ICML/ICML-2014-1392.pdf %*Stochastic Gradient Hamiltonian Monte Carlo %@Tianqi Chen, Emily Fox, Carlos Guestrin %t2014 %cICML %f/ICML/ICML-2014-1393.pdf %*A Deep Semi-NMF Model for Learning Hidden Representations %@George Trigeorgis, Konstantinos Bousmalis, Stefanos Zafeiriou, Bjoern Schuller %t2014 %cICML %f/ICML/ICML-2014-1394.pdf %*A Deep Semi-NMF Model for Learning Hidden Representations %@George Trigeorgis, Konstantinos Bousmalis, Stefanos Zafeiriou, Bjoern Schuller %t2014 %cICML %f/ICML/ICML-2014-1395.pdf %*Asynchronous Distributed ADMM Algorithm for Global Variable Consensus Optimization %@Ruiliang Zhang, James Kwok %t2014 %cICML %f/ICML/ICML-2014-1396.pdf %*Spectral Regularization for Max-Margin Sequence Tagging %@Ariadna Quattoni, Borja Balle, Xavier Carreras, Amir Globerson %t2014 %cICML %f/ICML/ICML-2014-1397.pdf %*Learning by Stretching Deep Networks %@Gaurav Pandey, Ambedkar Dukkipati %t2014 %cICML %f/ICML/ICML-2014-1398.pdf %*Nonnegative Sparse PCA with Provable Guarantees %@Megasthenis Asteris, Alexandros Dimakis, Dimitris Papailiopoulos %t2014 %cICML %f/ICML/ICML-2014-1399.pdf %*Active Learning of Parameterized Skills %@Bruno Da Silva, George Konidaris, Andrew Barto %t2014 %cICML %f/ICML/ICML-2014-1400.pdf %*Learning Ordered Representations with Nested Dropout %@Oren Rippel, Michael Gelbart, Ryan Adams %t2014 %cICML %f/ICML/ICML-2014-1401.pdf %*Learning Ordered Representations with Nested Dropout %@Oren Rippel, Michael Gelbart, Ryan Adams %t2014 %cICML %f/ICML/ICML-2014-1402.pdf %*Learning the Irreducible Representations of Commutative Lie Groups %@Taco Cohen, Max Welling %t2014 %cICML %f/ICML/ICML-2014-1403.pdf %*Learning the Irreducible Representations of Commutative Lie Groups %@Taco Cohen, Max Welling %t2014 %cICML %f/ICML/ICML-2014-1404.pdf %*Towards End-To-End Speech Recognition with Recurrent Neural Networks %@Alex Graves, Navdeep Jaitly %t2014 %cICML %f/ICML/ICML-2014-1405.pdf %*Multi-period Trading Prediction Markets with Connections to Machine Learning %@Jinli Hu, Amos Storkey %t2014 %cICML %f/ICML/ICML-2014-1406.pdf %*Multi-period Trading Prediction Markets with Connections to Machine Learning %@Jinli Hu, Amos Storkey %t2014 %cICML %f/ICML/ICML-2014-1407.pdf %*Efficient Gradient-Based Inference through Transformations between Bayes Nets and Neural Nets %@Diederik Kingma, Max Welling %t2014 %cICML %f/ICML/ICML-2014-1408.pdf %*Neural Variational Inference and Learning in Belief Networks %@Andriy Mnih, Karol Gregor %t2014 %cICML %f/ICML/ICML-2014-1409.pdf %*Neural Variational Inference and Learning in Belief Networks %@Andriy Mnih, Karol Gregor %t2014 %cICML %f/ICML/ICML-2014-1410.pdf %*Scalable Nonparametric Bayesian Analysis of Incomplete Multiway Data %@Piyush Rai, Yingjian Wang, Lawrence Carin %t2014 %cICML %f/ICML/ICML-2014-1411.pdf %*Scalable Nonparametric Bayesian Analysis of Incomplete Multiway Data %@Piyush Rai, Yingjian Wang, Lawrence Carin %t2014 %cICML %f/ICML/ICML-2014-1412.pdf %*Beta Diffusion Trees %@Creighton Heaukulani, David Knowles, Zoubin Ghahramani %t2014 %cICML %f/ICML/ICML-2014-1413.pdf %*Learning Character-level Representations for Part-of-Speech Tagging %@Cicero Dos Santos, Bianca Zadrozny %t2014 %cICML %f/ICML/ICML-2014-1414.pdf %*Saddle Points and Accelerated Perceptron Algorithms %@Adams Wei Yu, fatma Kilinc-Karzan, Jaime Carbonell %t2014 %cICML %f/ICML/ICML-2014-1415.pdf %*Robust Distance Metric Learning via Simultaneous L1-Norm Minimization and Maximization %@Hua Wang, Feiping Nie, Heng Huang %t2014 %cICML %f/ICML/ICML-2014-1416.pdf %*Learning from Contagion (Without Timestamps) %@Kareem Amin, Hoda Heidari, Michael Kearns %t2014 %cICML %f/ICML/ICML-2014-1417.pdf %*Stochastic Variational Inference for Bayesian Time Series Models %@Matthew Johnson, Alan Willsky %t2014 %cICML %f/ICML/ICML-2014-1418.pdf %*A Clockwork RNN %@Jan Koutnik, Klaus Greff, Faustino Gomez, Juergen Schmidhuber %t2014 %cICML %f/ICML/ICML-2014-1419.pdf %*Estimating Latent-Variable Graphical Models using Moments and Likelihoods %@Arun Tejasvi Chaganty, Percy Liang %t2014 %cICML %f/ICML/ICML-2014-1420.pdf %*Estimating Latent-Variable Graphical Models using Moments and Likelihoods %@Arun Tejasvi Chaganty, Percy Liang %t2014 %cICML %f/ICML/ICML-2014-1421.pdf %*Universal Matrix Completion %@Srinadh Bhojanapalli, Prateek Jain %t2014 %cICML %f/ICML/ICML-2014-1422.pdf %*Finding Dense Subgraphs via Low-Rank Bilinear Optimization %@Dimitris Papailiopoulos, Ioannis Mitliagkas, Alexandros Dimakis, Constantine Caramanis %t2014 %cICML %f/ICML/ICML-2014-1423.pdf %*Finding Dense Subgraphs via Low-Rank Bilinear Optimization %@Dimitris Papailiopoulos, Ioannis Mitliagkas, Alexandros Dimakis, Constantine Caramanis %t2014 %cICML %f/ICML/ICML-2014-1424.pdf %*Compositional Morphology for Word Representations and Language Modelling %@Jan Botha, Phil Blunsom %t2014 %cICML %f/ICML/ICML-2014-1425.pdf %*Learning Polynomials with Neural Networks %@Alexandr Andoni, Rina Panigrahy, Gregory Valiant, Li Zhang %t2014 %cICML %f/ICML/ICML-2014-1426.pdf %*Exponential Family Matrix Completion under Structural Constraints %@Suriya Gunasekar, Pradeep Ravikumar, Joydeep Ghosh %t2014 %cICML %f/ICML/ICML-2014-1427.pdf %*Sample-based Approximate Regularization %@Philip Bachman, Amir-Massoud Farahmand, Doina Precup %t2014 %cICML %f/ICML/ICML-2014-1428.pdf %*A Compilation Target for Probabilistic Programming Languages %@Brooks Paige, Frank Wood %t2014 %cICML %f/ICML/ICML-2014-1429.pdf %*Adaptive Monte-Carlo via Bandit Allocation %@James Neufeld, Andras Gyorgy, Csaba Szepesvari, Dale Schuurmans %t2014 %cICML %f/ICML/ICML-2014-1430.pdf %*Adaptive Monte-Carlo via Bandit Allocation %@James Neufeld, Andras Gyorgy, Csaba Szepesvari, Dale Schuurmans %t2014 %cICML %f/ICML/ICML-2014-1431.pdf %*Efficient Dimensionality Reduction for High-Dimensional Network Estimation %@Safiye Celik, Benjamin Logsdon, Su-In Lee %t2014 %cICML %f/ICML/ICML-2014-1432.pdf %*Deterministic Anytime Inference for Stochastic Continuous-Time Markov Processes %@E. Busra Celikkaya, Christian Shelton %t2014 %cICML %f/ICML/ICML-2014-1433.pdf %*Doubly Stochastic Variational Bayes for non-Conjugate Inference %@Michalis Titsias, Miguel Lázaro-Gredilla %t2014 %cICML %f/ICML/ICML-2014-1434.pdf %*Doubly Stochastic Variational Bayes for non-Conjugate Inference %@Michalis Titsias, Miguel Lázaro-Gredilla %t2014 %cICML %f/ICML/ICML-2014-1435.pdf %*Efficient Learning of Mahalanobis Metrics for Ranking %@Daryl Lim, Gert Lanckriet %t2014 %cICML %f/ICML/ICML-2014-1436.pdf %*Efficient Learning of Mahalanobis Metrics for Ranking %@Daryl Lim, Gert Lanckriet %t2014 %cICML %f/ICML/ICML-2014-1437.pdf %*GEV-Canonical Regression for Accurate Binary Class Probability Estimation when One Class is Rare %@Arpit Agarwal, Harikrishna Narasimhan, Shivaram Kalyanakrishnan, Shivani Agarwal %t2014 %cICML %f/ICML/ICML-2014-1438.pdf %*A Reversible Infinite HMM using Normalised Random Measures %@Konstantina Palla, David Knowles, Zoubin Ghahramani %t2014 %cICML %f/ICML/ICML-2014-1439.pdf %*A Reversible Infinite HMM using Normalised Random Measures %@Konstantina Palla, David Knowles, Zoubin Ghahramani %t2014 %cICML %f/ICML/ICML-2014-1440.pdf %*Structured Low-Rank Matrix Factorization: Optimality, Algorithm, and Applications to Image Processing %@Benjamin Haeffele, Rene Vidal, Eric Young %t2014 %cICML %f/ICML/ICML-2014-1441.pdf %*Structured Low-Rank Matrix Factorization: Optimality, Algorithm, and Applications to Image Processing %@Benjamin Haeffele, Rene Vidal, Eric Young %t2014 %cICML %f/ICML/ICML-2014-1442.pdf %*Influence Function Learning in Information Diffusion Networks %@Nan Du, Yingyu Liang, Le Song, Maria Balcan %t2014 %cICML %f/ICML/ICML-2014-1443.pdf %*An Information Geometry of Statistical Manifold Learning %@Ke Sun, Stéphane Marchand-Maillet %t2014 %cICML %f/ICML/ICML-2014-1444.pdf %*An Information Geometry of Statistical Manifold Learning %@Ke Sun, Stéphane Marchand-Maillet %t2014 %cICML %f/ICML/ICML-2014-1445.pdf %*Relative Upper Confidence Bound for the K-Armed Dueling Bandit Problem %@Masrour Zoghi, Shimon Whiteson, Remi Munos, Maarten de Rijke %t2014 %cICML %f/ICML/ICML-2014-1446.pdf %*Relative Upper Confidence Bound for the K-Armed Dueling Bandit Problem %@Masrour Zoghi, Shimon Whiteson, Remi Munos, Maarten de Rijke %t2014 %cICML %f/ICML/ICML-2014-1447.pdf %*Compact Random Feature Maps %@Raffay Hamid, Alex Gittens, Ying Xiao, Dennis Decoste %t2014 %cICML %f/ICML/ICML-2014-1448.pdf %*Concentration in Unbounded Metric Spaces and Algorithmic Stability %@Aryeh Kontorovich %t2014 %cICML %f/ICML/ICML-2014-1449.pdf %*Heavy-tailed Regression with a Generalized Median-of-means %@Daniel Hsu, Sivan Sabato %t2014 %cICML %f/ICML/ICML-2014-1450.pdf %*Spectral Bandits for Smooth Graph Functions %@Remi Munos, Michal Valko, Branislav Kveton, Tomas Kocak %t2014 %cICML %f/ICML/ICML-2014-1451.pdf %*Robust Principal Component Analysis with Complex Noise %@Qian Zhao, Deyu Meng, Lei Zhang, Wangmeng Zuo, Zongben Xu %t2014 %cICML %f/ICML/ICML-2014-1452.pdf %*Robust Principal Component Analysis with Complex Noise %@Qian Zhao, Deyu Meng, Lei Zhang, Wangmeng Zuo, Zongben Xu %t2014 %cICML %f/ICML/ICML-2014-1453.pdf %*Scalable Semidefinite Relaxation for Maximum A Posteriori Estimation %@Qixing Huang, Yuxin Chen, Guibas Leonidas %t2014 %cICML %f/ICML/ICML-2014-1454.pdf %*Scalable Semidefinite Relaxation for Maximum A Posteriori Estimation %@Qixing Huang, Yuxin Chen, Guibas Leonidas %t2014 %cICML %f/ICML/ICML-2014-1455.pdf %*Square Deal: Lower Bounds and Improved Relaxations for Tensor Recovery %@Cun Mu, Bo Huang, John Wright, Donald Goldfarb %t2014 %cICML %f/ICML/ICML-2014-1456.pdf %*Automated Inference of Point of View from User Interactions in Collective Intelligence Venues %@Sanmay Das, Allen Lavoie %t2014 %cICML %f/ICML/ICML-2014-1457.pdf %*Orthogonal Rank-One Matrix Pursuit for Matrix Completion %@Zheng Wang, Ming-Jun Lai, Zhaosong Lu, Wei Fan, Hasan Davulcu, Jieping Ye %t2014 %cICML %f/ICML/ICML-2014-1458.pdf %*Near-Optimal Joint Object Matching via Convex Relaxation %@Yuxin Chen, Guibas Leonidas, Qixing Huang %t2014 %cICML %f/ICML/ICML-2014-1459.pdf %*Convex Total Least Squares %@Dmitry Malioutov, Nikolai Slavov %t2014 %cICML %f/ICML/ICML-2014-1460.pdf %*On p-norm Path Following in Multiple Kernel Learning for Non-linear Feature Selection %@Pratik Jawanpuria, Manik Varma, Saketha Nath %t2014 %cICML %f/ICML/ICML-2014-1461.pdf %*On p-norm Path Following in Multiple Kernel Learning for Non-linear Feature Selection %@Pratik Jawanpuria, Manik Varma, Saketha Nath %t2014 %cICML %f/ICML/ICML-2014-1462.pdf %*Gradient Hard Thresholding Pursuit for Sparsity-Constrained Optimization %@Xiaotong Yuan, Ping Li, Tong Zhang %t2014 %cICML %f/ICML/ICML-2014-1463.pdf %*Learning With Priors %@Jean Honorio, Tommi Jaakkola %t2014 %cICML %f/ICML/ICML-2014-1464.pdf %*Learning With Priors %@Jean Honorio, Tommi Jaakkola %t2014 %cICML %f/ICML/ICML-2014-1465.pdf %*Geodesic Distance Function Learning via Heat Flows on Vector Fields %@Binbin Lin, Ji Yang, Xiaofei He, Jieping Ye %t2014 %cICML %f/ICML/ICML-2014-1466.pdf %*Active Teaching for Crowdsourcing Classification %@Adish Singla, Ilija Bogunovic, Gabor Bartok, Amin Karbasi, Andreas Krause %t2014 %cICML %f/ICML/ICML-2014-1467.pdf %*On the Convergence of No-regret Learning in Selfish Routing %@Benjamin Drighès, Walid Krichene, Alexandre Bayen %t2014 %cICML %f/ICML/ICML-2014-1468.pdf %*Offline Evaluation of Recommendation Systems %@Olivier Nicol, Jérémie Mary, Philippe Preux %t2014 %cICML %f/ICML/ICML-2014-1469.pdf %*Offline Evaluation of Recommendation Systems %@Olivier Nicol, Jérémie Mary, Philippe Preux %t2014 %cICML %f/ICML/ICML-2014-1470.pdf %*Scaling Up Robust MDPs by Reinforcement Learning %@Aviv Tamar, Huan Xu, Shie Mannor %t2014 %cICML %f/ICML/ICML-2014-1471.pdf %*Marginal Structured SVM with Hidden Variables %@Wei Ping, Qiang Liu, Alex Ihler %t2014 %cICML %f/ICML/ICML-2014-1472.pdf %*Marginal Structured SVM with Hidden Variables %@Wei Ping, Qiang Liu, Alex Ihler %t2014 %cICML %f/ICML/ICML-2014-1473.pdf %*From Exponential to Linear Complexity When Learning Practical Markov Random Fields %@Yariv Mizrahi, Nando De Freitas, Luis Tenorio %t2014 %cICML %f/ICML/ICML-2014-1474.pdf %*Pitfalls in the Use of Parallel Inference for the Dirichlet Process %@Yarin Gal, Zoubin Ghahramani %t2014 %cICML %f/ICML/ICML-2014-1475.pdf %*Optimal PAC Multiple Arm Identification with Applications to Crowdsourcing %@Yuan Zhou, Xi Chen, Jian Li %t2014 %cICML %f/ICML/ICML-2014-1476.pdf %*Optimal PAC Multiple Arm Identification with Applications to Crowdsourcing %@Yuan Zhou, Xi Chen, Jian Li %t2014 %cICML %f/ICML/ICML-2014-1477.pdf %*Deep Generative Stochastic Networks Trainable by Backprop %@Yoshua Bengio, Eric Laufer, Jason Yosinski %t2014 %cICML %f/ICML/ICML-2014-1478.pdf %*A Highly Scalable Parallel Algorithm for Isotropic Total Variation Models %@Jie Wang, Qingyang Li, Sen Yang, Wei Fan, Jieping Ye %t2014 %cICML %f/ICML/ICML-2014-1479.pdf %*Statistical-Computational Phase Transitions in Planted Models: The High-Dimensional Setting %@Yudong Chen, Jiaming Xu %t2014 %cICML %f/ICML/ICML-2014-1480.pdf %*Statistical-Computational Phase Transitions in Planted Models: The High-Dimensional Setting %@Yudong Chen, Jiaming Xu %t2014 %cICML %f/ICML/ICML-2014-1481.pdf %*Gaussian Process Optimization with Mutual Information %@Emile Contal, Nicolas Vayatis %t2014 %cICML %f/ICML/ICML-2014-1482.pdf %*Aggregating Ordinal Labels from Crowds by Minimax Conditional Entropy %@Dengyong Zhou, Qiang Liu, John Platt, Christopher Meek %t2014 %cICML %f/ICML/ICML-2014-1483.pdf %*Exchangeable Variable Models %@Mathias Niepert, Pedro Domingos %t2014 %cICML %f/ICML/ICML-2014-1484.pdf %*Clustering in the Presence of Background Noise %@Nika Haghtalab, Shai Ben-David %t2014 %cICML %f/ICML/ICML-2014-1485.pdf %*Safe Screening with Variational Inequalities and Its Application to Lasso %@Jun Liu, Zheng Zhao, Jie Wang, Jieping Ye %t2014 %cICML %f/ICML/ICML-2014-1486.pdf %*Safe Screening with Variational Inequalities and Its Application to Lasso %@Jun Liu, Zheng Zhao, Jie Wang, Jieping Ye %t2014 %cICML %f/ICML/ICML-2014-1487.pdf %*Learning the Consistent Behavior of Common Users for Target Node Prediction across Social Networks %@Shan-Hung Wu, Hao-Heng Chien, Kuan-Hua Lin, Philip Yu %t2014 %cICML %f/ICML/ICML-2014-1488.pdf %*Learning the Consistent Behavior of Common Users for Target Node Prediction across Social Networks %@Shan-Hung Wu, Hao-Heng Chien, Kuan-Hua Lin, Philip Yu %t2014 %cICML %f/ICML/ICML-2014-1489.pdf %*Signal Recovery from $\ell_p$ Pooling Representations %@Joan Bruna Estrach, Arthur Szlam, Yann LeCun %t2014 %cICML %f/ICML/ICML-2014-1490.pdf %*Signal Recovery from $\ell_p$ Pooling Representations %@Joan Bruna Estrach, Arthur Szlam, Yann LeCun %t2014 %cICML %f/ICML/ICML-2014-1491.pdf %*PAC-inspired Option Discovery in Lifelong Reinforcement Learning %@Emma Brunskill, Lihong Li %t2014 %cICML %f/ICML/ICML-2014-1492.pdf %*PAC-inspired Option Discovery in Lifelong Reinforcement Learning %@Emma Brunskill, Lihong Li %t2014 %cICML %f/ICML/ICML-2014-1493.pdf %*Multi-label Classification via Feature-aware Implicit Label Space Encoding %@Zijia Lin, Guiguang Ding, Mingqing Hu, Jianmin Wang %t2014 %cICML %f/ICML/ICML-2014-1494.pdf %*Scalable Gaussian Process Structured Prediction for Grid Factor Graph Applications %@Sebastien Bratieres, Novi Quadrianto, Sebastian Nowozin, Zoubin Ghahramani %t2014 %cICML %f/ICML/ICML-2014-1495.pdf %*Scalable Gaussian Process Structured Prediction for Grid Factor Graph Applications %@Sebastien Bratieres, Novi Quadrianto, Sebastian Nowozin, Zoubin Ghahramani %t2014 %cICML %f/ICML/ICML-2014-1496.pdf %*Anomaly Ranking as Supervised Bipartite Ranking %@Stephan Clémençon, Sylvain Robbiano %t2014 %cICML %f/ICML/ICML-2014-1497.pdf %*Hierarchical Quasi-Clustering Methods for Asymmetric Networks %@Gunnar Carlsson, Facundo Mémoli, Alejandro Ribeiro, Santiago Segarra %t2014 %cICML %f/ICML/ICML-2014-1498.pdf %*Rectangular Tiling Process %@Masahiro Nakano, Katsuhiko Ishiguro, Akisato Kimura, Takeshi Yamada, Naonori Ueda %t2014 %cICML %f/ICML/ICML-2014-1499.pdf %*Two-Stage Metric Learning %@Jun Wang, Ke Sun, Fei Sha, Stéphane Marchand-Maillet, Alexandros Kalousis %t2014 %cICML %f/ICML/ICML-2014-1500.pdf %*Stochastic Inference for Scalable Probabilistic Modeling of Binary Matrices %@Jose Miguel Hernandez-Lobato, Neil Houlsby, Zoubin Ghahramani %t2014 %cICML %f/ICML/ICML-2014-1501.pdf %*Elementary Estimators for High-Dimensional Linear Regression %@Eunho Yang, Aurelie Lozano, Pradeep Ravikumar %t2014 %cICML %f/ICML/ICML-2014-1502.pdf %*Elementary Estimators for Sparse Covariance Matrices and other Structured Moments %@Eunho Yang, Aurelie Lozano, Pradeep Ravikumar %t2014 %cICML %f/ICML/ICML-2014-1503.pdf %*Learning with Smoothness: Pointwise, Graph-based, Probabilistic %@Yuan Fang, Kevin Chang, Hady Lauw %t2014 %cICML %f/ICML/ICML-2014-1504.pdf %*Bayesian Max-margin Multi-Task Learning with Data Augmentation %@Chengtao Li, Jun Zhu, Jianfei Chen %t2014 %cICML %f/ICML/ICML-2014-1505.pdf %*Sparse Reinforcement Learning via Convex Optimization %@Zhiwei Qin, Weichang Li %t2014 %cICML %f/ICML/ICML-2014-1506.pdf %*Sparse Reinforcement Learning via Convex Optimization %@Zhiwei Qin, Weichang Li %t2014 %cICML %f/ICML/ICML-2014-1507.pdf %*Gaussian Process Classification and Active Learning with Multiple Annotators %@Filipe Rodrigues, Francisco Pereira, Bernardete Ribeiro %t2014 %cICML %f/ICML/ICML-2014-1508.pdf %*Gaussian Process Classification and Active Learning with Multiple Annotators %@Filipe Rodrigues, Francisco Pereira, Bernardete Ribeiro %t2014 %cICML %f/ICML/ICML-2014-1509.pdf %*Structured Prediction of Network Response %@Hongyu Su, Aristides Gionis, Juho Rousu %t2014 %cICML %f/ICML/ICML-2014-1510.pdf %*Structured Prediction of Network Response %@Hongyu Su, Aristides Gionis, Juho Rousu %t2014 %cICML %f/ICML/ICML-2014-1511.pdf %*An Analysis of State-Relevance Weights and Sampling Distributions on L1-Regularized Approximate Linear Programming Approximation Accuracy %@Gavin Taylor, Connor Geer, David Piekut %t2014 %cICML %f/ICML/ICML-2014-1512.pdf %*Optimization Equivalence of Divergences Improves Neighbor Embedding %@Zhirong Yang, Jaakko Peltonen, Samuel Kaski %t2014 %cICML %f/ICML/ICML-2014-1513.pdf %*Optimization Equivalence of Divergences Improves Neighbor Embedding %@Zhirong Yang, Jaakko Peltonen, Samuel Kaski %t2014 %cICML %f/ICML/ICML-2014-1514.pdf %*An Asynchronous Parallel Stochastic Coordinate Descent Algorithm %@Ji Liu, Steve Wright, Christopher Re, Srikrishna Sridhar, Vicotr Bittorf %t2014 %cICML %f/ICML/ICML-2014-1515.pdf %*Consistency of Causal Inference under the Additive Noise Model %@Samory Kpotufe, Eleni Sgouritsa, Dominik Janzing, Bernhard Schoelkopf %t2014 %cICML %f/ICML/ICML-2014-1516.pdf %*Globally Convergent Parallel MAP LP Relaxation Solver using the Frank-Wolfe Algorithm %@Alexander Schwing, Tamir Hazan, Marc Pollefeys, Raquel Urtasun %t2014 %cICML %f/ICML/ICML-2014-1517.pdf %*Linear Programming for Large-Scale Markov Decision Problems %@Alan Malek, Yasin Abbasi-Yadkori, Peter Bartlett %t2014 %cICML %f/ICML/ICML-2014-1518.pdf %*Linear Programming for Large-Scale Markov Decision Problems %@Alan Malek, Yasin Abbasi-Yadkori, Peter Bartlett %t2014 %cICML %f/ICML/ICML-2014-1519.pdf %*Linear Time Solver for Primal SVM %@Feiping Nie, Yizhen Huang, Heng Huang %t2014 %cICML %f/ICML/ICML-2014-1520.pdf %*Implicit Particle Sequential Monte Carlo %@Seong-Hwan Jun, Alexandre Bouchard-Côté %t2014 %cICML %f/ICML/ICML-2014-1521.pdf %*Implicit Particle Sequential Monte Carlo %@Seong-Hwan Jun, Alexandre Bouchard-Côté %t2014 %cICML %f/ICML/ICML-2014-1522.pdf %*Scaling SVM and Least Absolute Deviations via Exact Data Reduction %@Jie Wang, Jieping Ye %t2014 %cICML %f/ICML/ICML-2014-1523.pdf %*Latent Semantic Representation Learning for Scene Classification %@Xin Li, Yuhong Guo %t2014 %cICML %f/ICML/ICML-2014-1524.pdf %*Least Squares Revisited: Scalable Approaches for Multi-class Prediction %@Alekh Agarwal, Sham Kakade, Nikos Karampatziakis, Le Song, Gregory Valiant %t2014 %cICML %f/ICML/ICML-2014-1525.pdf %*Local Algorithms for Interactive Clustering %@Pranjal Awasthi, Konstantin Voevodski, Maria Balcan %t2014 %cICML %f/ICML/ICML-2014-1526.pdf %*Learning and Planning with Relational Uncertainty Predicates over the Existence of Objects %@Vien Ngo, Marc Toussaint %t2014 %cICML %f/ICML/ICML-2014-1527.pdf %*A New Q(\lambda) %@Rich Sutton, Ashique Rupam Mahmood, Doina Precup, Hado van Hasselt %t2014 %cICML %f/ICML/ICML-2014-1528.pdf %*A New Q(\lambda) %@Rich Sutton, Ashique Rupam Mahmood, Doina Precup, Hado van Hasselt %t2014 %cICML %f/ICML/ICML-2014-1529.pdf %*On Robustness and Regularization of Structural Support Vector Machines %@Mohamad Ali Torkamani, Daniel Lowd %t2014 %cICML %f/ICML/ICML-2014-1530.pdf %*On Robustness and Regularization of Structural Support Vector Machines %@Mohamad Ali Torkamani, Daniel Lowd %t2014 %cICML %f/ICML/ICML-2014-1531.pdf %*Guess-Averse Loss Functions for Cost-Sensitive Multiclass Boosting %@Oscar Beijbom, Mohammad Saberian, Nuno Vasconcelos, David Kriegman %t2014 %cICML %f/ICML/ICML-2014-1532.pdf %*Guess-Averse Loss Functions for Cost-Sensitive Multiclass Boosting %@Oscar Beijbom, Mohammad Saberian, Nuno Vasconcelos, David Kriegman %t2014 %cICML %f/ICML/ICML-2014-1533.pdf %*Multimodal Neural Language Models %@Ryan Kiros, Ruslan Salakhutdinov, Rich Zemel %t2014 %cICML %f/ICML/ICML-2014-1534.pdf %*An Adaptive Low Dimensional quasi-Newton Sum of Functions Optimizer %@Jascha Sohl-Dickstein, Ben Poole, Surya Ganguli %t2014 %cICML %f/ICML/ICML-2014-1535.pdf %*Alternating Minimization for Mixed Linear Regression %@Xinyang Yi, Constantine Caramanis, Sujay Sanghavi %t2014 %cICML %f/ICML/ICML-2014-1536.pdf %*Alternating Minimization for Mixed Linear Regression %@Xinyang Yi, Constantine Caramanis, Sujay Sanghavi %t2014 %cICML %f/ICML/ICML-2014-1537.pdf %*Stochastic Neighbor Compression %@Matt Kusner, Stephen Tyree, Kilian Weinberger, Kunal Agrawal %t2014 %cICML %f/ICML/ICML-2014-1538.pdf %*Robust Learning under Uncertain Test Distributions: Relating Covariate Shift to Model Misspecification %@Junfeng Wen, Chun-Nam Yu, Russell Greiner %t2014 %cICML %f/ICML/ICML-2014-1539.pdf %*Robust Learning under Uncertain Test Distributions: Relating Covariate Shift to Model Misspecification %@Junfeng Wen, Chun-Nam Yu, Russell Greiner %t2014 %cICML %f/ICML/ICML-2014-1540.pdf %*Nonparametric Estimation of Multi-View Latent Variable Models %@Le Song, Animashree Anandkumar, Bo Dai, Bo Xie %t2014 %cICML %f/ICML/ICML-2014-1541.pdf %*Structured Generative Models of Natural Source Code %@Chris Maddison, Daniel Tarlow %t2014 %cICML %f/ICML/ICML-2014-1542.pdf %*Structured Generative Models of Natural Source Code %@Chris Maddison, Daniel Tarlow %t2014 %cICML %f/ICML/ICML-2014-1543.pdf %*A Single-Pass Algorithm for Efficiently Recovering Sparse Cluster Centers for High-dimensional Data %@Jinfeng Yi, Lijun Zhang, Jun Wang, Rong Jin, Anil Jain %t2014 %cICML %f/ICML/ICML-2014-1544.pdf %*A Single-Pass Algorithm for Efficiently Recovering Sparse Cluster Centers for High-dimensional Data %@Jinfeng Yi, Lijun Zhang, Jun Wang, Rong Jin, Anil Jain %t2014 %cICML %f/ICML/ICML-2014-1545.pdf %*Stochastic Approximation with Implicit Updates. Applications in Robust Online Learning of GLMs %@Panagiotis Toulis, Edoardo Airoldi, Jason Rennie %t2014 %cICML %f/ICML/ICML-2014-1546.pdf %*Coding for Random Projections %@Ping Li, Michael Mitzenmacher, Anshumali Shrivastava %t2014 %cICML %f/ICML/ICML-2014-1547.pdf %*Fast Computation of Wasserstein Barycenters %@Marco Cuturi, Arnaud Doucet %t2014 %cICML %f/ICML/ICML-2014-1548.pdf %*Peilin Zhao, Tong Zhang %@Stochastic Optimization with Importance Sampling for Regularized Loss Minimization %t2015 %cICML %f/ICML/ICML-2015-1549.pdf %*Nihar Shah, Dengyong Zhou, Yuval Peres %@Approval Voting and Incentives in Crowdsourcing %t2015 %cICML %f/ICML/ICML-2015-1550.pdf %*Nihar Shah, Dengyong Zhou, Yuval Peres %@Approval Voting and Incentives in Crowdsourcing %t2015 %cICML %f/ICML/ICML-2015-1551.pdf %*Wacha Bounliphone, Arthur Gretton, Arthur Tenenhaus, Matthew Blaschko %@A low variance consistent test of relative dependency %t2015 %cICML %f/ICML/ICML-2015-1552.pdf %*Lu Bai, Luca Rossi, Zhihong Zhang, Edwin Hancock %@An Aligned Subtree Kernel for Weighted Graphs %t2015 %cICML %f/ICML/ICML-2015-1553.pdf %*Christos Boutsidis, Prabhanjan Kambadur, Alex Gittens %@Spectral Clustering via the Power Method - Provably %t2015 %cICML %f/ICML/ICML-2015-1554.pdf %*Ke Sun, Jun Wang, Alexandros Kalousis, Stephan Marchand-Maillet %@Information Geometry and Minimum Description Length Networks %t2015 %cICML %f/ICML/ICML-2015-1555.pdf %*Ke Sun, Jun Wang, Alexandros Kalousis, Stephan Marchand-Maillet %@Information Geometry and Minimum Description Length Networks %t2015 %cICML %f/ICML/ICML-2015-1556.pdf %*Jean-Baptiste Tristan, Joseph Tassarotti, Guy Steele %@Efficient Training of LDA on a GPU by Mean-for-Mode Estimation %t2015 %cICML %f/ICML/ICML-2015-1557.pdf %*Peilin Zhao, Jinwei Yang, Tong Zhang, Ping Li %@Adaptive Stochastic Alternating Direction Method of Multipliers %t2015 %cICML %f/ICML/ICML-2015-1558.pdf %*Alekh Agarwal, Leon Bottou %@A Lower Bound for the Optimization of Finite Sums %t2015 %cICML %f/ICML/ICML-2015-1559.pdf %*Alekh Agarwal, Leon Bottou %@A Lower Bound for the Optimization of Finite Sums %t2015 %cICML %f/ICML/ICML-2015-1560.pdf %*Dani Yogatama, Manaal Faruqui, Chris Dyer, Noah Smith %@Learning Word Representations with Hierarchical Sparse Coding %t2015 %cICML %f/ICML/ICML-2015-1561.pdf %*Dani Yogatama, Manaal Faruqui, Chris Dyer, Noah Smith %@Learning Word Representations with Hierarchical Sparse Coding %t2015 %cICML %f/ICML/ICML-2015-1562.pdf %*Mingsheng Long, Yue Cao, Jianmin Wang, Michael Jordan %@Learning Transferable Features with Deep Adaptation Networks %t2015 %cICML %f/ICML/ICML-2015-1563.pdf %*Takayuki Osogami %@Robust partially observable Markov decision process %t2015 %cICML %f/ICML/ICML-2015-1564.pdf %*Takayuki Osogami %@Robust partially observable Markov decision process %t2015 %cICML %f/ICML/ICML-2015-1565.pdf %*Han Zhao, Mazen Melibari, Pascal Poupart %@On the Relationship between Sum-Product Networks and Bayesian Networks %t2015 %cICML %f/ICML/ICML-2015-1566.pdf %*Han Zhao, Mazen Melibari, Pascal Poupart %@On the Relationship between Sum-Product Networks and Bayesian Networks %t2015 %cICML %f/ICML/ICML-2015-1567.pdf %*Aditya Menon, Brendan Van Rooyen, Cheng Soon Ong, Bob Williamson %@Learning from Corrupted Binary Labels via Class-Probability Estimation %t2015 %cICML %f/ICML/ICML-2015-1568.pdf %*Aditya Menon, Brendan Van Rooyen, Cheng Soon Ong, Bob Williamson %@Learning from Corrupted Binary Labels via Class-Probability Estimation %t2015 %cICML %f/ICML/ICML-2015-1569.pdf %*Tianbao Yang, Lijun Zhang, Rong Jin, Shenghuo Zhu %@An Explicit Sampling Dependent Spectral Error Bound for Column Subset Selection %t2015 %cICML %f/ICML/ICML-2015-1570.pdf %*Ohad Shamir %@A Stochastic PCA and SVD Algorithm with an Exponential Convergence Rate %t2015 %cICML %f/ICML/ICML-2015-1571.pdf %*Ohad Shamir %@A Stochastic PCA and SVD Algorithm with an Exponential Convergence Rate %t2015 %cICML %f/ICML/ICML-2015-1572.pdf %*Doron Kukliansky, Ohad Shamir %@Attribute Efficient Linear Regression with Distribution-Dependent Sampling %t2015 %cICML %f/ICML/ICML-2015-1573.pdf %*Doron Kukliansky, Ohad Shamir %@Attribute Efficient Linear Regression with Distribution-Dependent Sampling %t2015 %cICML %f/ICML/ICML-2015-1574.pdf %*Ethan Fetaya, Shimon Ullman %@Learning Local Invariant Mahalanobis Distances %t2015 %cICML %f/ICML/ICML-2015-1575.pdf %*Zhuang Ma, Yichao Lu, Dean Foster %@Finding Linear Structure in Large Datasets with Scalable Canonical Correlation Analysis %t2015 %cICML %f/ICML/ICML-2015-1576.pdf %*Zhuang Ma, Yichao Lu, Dean Foster %@Finding Linear Structure in Large Datasets with Scalable Canonical Correlation Analysis %t2015 %cICML %f/ICML/ICML-2015-1577.pdf %*Nan Jiang, Alex Kulesza, Satinder Singh %@Abstraction Selection in Model-based Reinforcement Learning %t2015 %cICML %f/ICML/ICML-2015-1578.pdf %*Nan Jiang, Alex Kulesza, Satinder Singh %@Abstraction Selection in Model-based Reinforcement Learning %t2015 %cICML %f/ICML/ICML-2015-1579.pdf %*Purushottam Kar, Harikrishna Narasimhan, Prateek Jain %@Surrogate Functions for Maximizing Precision at the Top %t2015 %cICML %f/ICML/ICML-2015-1580.pdf %*Purushottam Kar, Harikrishna Narasimhan, Prateek Jain %@Surrogate Functions for Maximizing Precision at the Top %t2015 %cICML %f/ICML/ICML-2015-1581.pdf %*Harikrishna Narasimhan, Purushottam Kar, Prateek Jain %@Optimizing Non-decomposable Performance Measures: A Tale of Two Classes %t2015 %cICML %f/ICML/ICML-2015-1582.pdf %*Harikrishna Narasimhan, Purushottam Kar, Prateek Jain %@Optimizing Non-decomposable Performance Measures: A Tale of Two Classes %t2015 %cICML %f/ICML/ICML-2015-1583.pdf %*Olivier Bachem, Mario Lucic, Andreas Krause %@Coresets for Nonparametric Estimation - the Case of DP-Means %t2015 %cICML %f/ICML/ICML-2015-1584.pdf %*Olivier Bachem, Mario Lucic, Andreas Krause %@Coresets for Nonparametric Estimation - the Case of DP-Means %t2015 %cICML %f/ICML/ICML-2015-1585.pdf %*Pratik Gajane, Tanguy Urvoy, Fabrice Clérot %@A Relative Exponential Weighing Algorithm for Adversarial Utility-based Dueling Bandits %t2015 %cICML %f/ICML/ICML-2015-1586.pdf %*Mohammad Taha Bahadori, David Kale, Yingying Fan, Yan Liu %@Functional Subspace Clustering with Application to Time Series %t2015 %cICML %f/ICML/ICML-2015-1587.pdf %*Mohammad Taha Bahadori, David Kale, Yingying Fan, Yan Liu %@Functional Subspace Clustering with Application to Time Series %t2015 %cICML %f/ICML/ICML-2015-1588.pdf %*Rose Yu, Dehua Cheng, Yan Liu %@Accelerated Online Low Rank Tensor Learning for Multivariate Spatiotemporal Streams %t2015 %cICML %f/ICML/ICML-2015-1589.pdf %*Rose Yu, Dehua Cheng, Yan Liu %@Accelerated Online Low Rank Tensor Learning for Multivariate Spatiotemporal Streams %t2015 %cICML %f/ICML/ICML-2015-1590.pdf %*Sean Jewell, Neil Spencer, Alexandre Bouchard-Côté %@Atomic Spatial Processes %t2015 %cICML %f/ICML/ICML-2015-1591.pdf %*Sean Jewell, Neil Spencer, Alexandre Bouchard-Côté %@Atomic Spatial Processes %t2015 %cICML %f/ICML/ICML-2015-1592.pdf %*Elad Hazan, Roi Livni, Yishay Mansour %@Classification with Low Rank and Missing Data %t2015 %cICML %f/ICML/ICML-2015-1593.pdf %*Elad Hazan, Roi Livni, Yishay Mansour %@Classification with Low Rank and Missing Data %t2015 %cICML %f/ICML/ICML-2015-1594.pdf %*Oran Richman, Shie Mannor %@Dynamic Sensing: Better Classification under Acquisition Constraints %t2015 %cICML %f/ICML/ICML-2015-1595.pdf %*Pinghua Gong, Jieping Ye %@A Modified Orthant-Wise Limited Memory Quasi-Newton Method with Convergence Analysis %t2015 %cICML %f/ICML/ICML-2015-1596.pdf %*Pinghua Gong, Jieping Ye %@A Modified Orthant-Wise Limited Memory Quasi-Newton Method with Convergence Analysis %t2015 %cICML %f/ICML/ICML-2015-1597.pdf %*Naji Shajarisales, Dominik Janzing, Bernhard Schoelkopf, Michel Besserve %@Telling cause from effect in deterministic linear dynamical systems %t2015 %cICML %f/ICML/ICML-2015-1598.pdf %*Naji Shajarisales, Dominik Janzing, Bernhard Schoelkopf, Michel Besserve %@Telling cause from effect in deterministic linear dynamical systems %t2015 %cICML %f/ICML/ICML-2015-1599.pdf %*Kirthevasan Kandasamy, Jeff Schneider, Barnabas Poczos %@High Dimensional Bayesian Optimisation and Bandits via Additive Models %t2015 %cICML %f/ICML/ICML-2015-1600.pdf %*Kirthevasan Kandasamy, Jeff Schneider, Barnabas Poczos %@High Dimensional Bayesian Optimisation and Bandits via Additive Models %t2015 %cICML %f/ICML/ICML-2015-1601.pdf %*Tianbao Yang, Lijun Zhang, Rong Jin, Shenghuo Zhu %@Theory of Dual-sparse Regularized Randomized Reduction %t2015 %cICML %f/ICML/ICML-2015-1602.pdf %*Ambuj Tewari, Sougata Chaudhuri %@Generalization error bounds for learning to rank: Does the length of document lists matter? %t2015 %cICML %f/ICML/ICML-2015-1603.pdf %*Ambuj Tewari, Sougata Chaudhuri %@Generalization error bounds for learning to rank: Does the length of document lists matter? %t2015 %cICML %f/ICML/ICML-2015-1604.pdf %*Toby Hocking, Guillem Rigaill, Guillaume Bourque %@PeakSeg: constrained optimal segmentation and supervised penalty learning for peak detection in count data %t2015 %cICML %f/ICML/ICML-2015-1605.pdf %*Olivier Fercoq, Alexandre Gramfort, Joseph Salmon %@Mind the duality gap: safer rules for the Lasso %t2015 %cICML %f/ICML/ICML-2015-1606.pdf %*Olivier Fercoq, Alexandre Gramfort, Joseph Salmon %@Mind the duality gap: safer rules for the Lasso %t2015 %cICML %f/ICML/ICML-2015-1607.pdf %*Robert Nishihara, Laurent Lessard, Ben Recht, Andrew Packard, Michael Jordan %@A General Analysis of the Convergence of ADMM %t2015 %cICML %f/ICML/ICML-2015-1608.pdf %*Yuchen Zhang, Xiao Lin %@Stochastic Primal-Dual Coordinate Method for Regularized Empirical Risk Minimization %t2015 %cICML %f/ICML/ICML-2015-1609.pdf %*Yuchen Zhang, Xiao Lin %@DiSCO: Distributed Optimization for Self-Concordant Empirical Loss %t2015 %cICML %f/ICML/ICML-2015-1610.pdf %*Yuxin Chen, Changho Suh %@Spectral MLE: Top-K Rank Aggregation from Pairwise Comparisons %t2015 %cICML %f/ICML/ICML-2015-1611.pdf %*Yuxin Chen, Changho Suh %@Spectral MLE: Top-K Rank Aggregation from Pairwise Comparisons %t2015 %cICML %f/ICML/ICML-2015-1612.pdf %*Stephen Bach, Bert Huang, Jordan Boyd-Graber, Lise Getoor %@Paired-Dual Learning for Fast Training of Latent Variable Hinge-Loss MRFs %t2015 %cICML %f/ICML/ICML-2015-1613.pdf %*Stephen Bach, Bert Huang, Jordan Boyd-Graber, Lise Getoor %@Paired-Dual Learning for Fast Training of Latent Variable Hinge-Loss MRFs %t2015 %cICML %f/ICML/ICML-2015-1614.pdf %*Corinna Cortes, Vitaly Kuznetsov, Mehryar Mohri, Umar Syed %@Structural Maxent Models %t2015 %cICML %f/ICML/ICML-2015-1615.pdf %*Corinna Cortes, Vitaly Kuznetsov, Mehryar Mohri, Umar Syed %@Structural Maxent Models %t2015 %cICML %f/ICML/ICML-2015-1616.pdf %*Debarghya Ghoshdastidar, Ambedkar Dukkipati %@A Provable Generalized Tensor Spectral Method for Uniform Hypergraph Partitioning %t2015 %cICML %f/ICML/ICML-2015-1617.pdf %*Debarghya Ghoshdastidar, Ambedkar Dukkipati %@A Provable Generalized Tensor Spectral Method for Uniform Hypergraph Partitioning %t2015 %cICML %f/ICML/ICML-2015-1618.pdf %*Ben London, Bert Huang, Lise Getoor %@The Benefits of Learning with Strongly Convex Approximate Inference %t2015 %cICML %f/ICML/ICML-2015-1619.pdf %*Ben London, Bert Huang, Lise Getoor %@The Benefits of Learning with Strongly Convex Approximate Inference %t2015 %cICML %f/ICML/ICML-2015-1620.pdf %*Bo Xin, David Wipf %@Pushing the Limits of Affine Rank Minimization by Adapting Probabilistic PCA %t2015 %cICML %f/ICML/ICML-2015-1621.pdf %*Takanori Maehara, Akihiro Yabe, Ken-ichi Kawarabayashi %@Budget Allocation Problem with Multiple Advertisers: A Game Theoretic View %t2015 %cICML %f/ICML/ICML-2015-1622.pdf %*Takanori Maehara, Akihiro Yabe, Ken-ichi Kawarabayashi %@Budget Allocation Problem with Multiple Advertisers: A Game Theoretic View %t2015 %cICML %f/ICML/ICML-2015-1623.pdf %*Katharina Blechschmidt, Joachim Giesen, Soeren Laue %@Tracking Approximate Solutions of Parameterized Optimization Problems over Multi-Dimensional (Hyper-)Parameter Domains %t2015 %cICML %f/ICML/ICML-2015-1624.pdf %*Sergey Ioffe, Christian Szegedy %@Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift %t2015 %cICML %f/ICML/ICML-2015-1625.pdf %*Sergey Ioffe, Christian Szegedy %@Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift %t2015 %cICML %f/ICML/ICML-2015-1626.pdf %*Yuchen Zhang, Martin Wainwright, Michael Jordan %@Distributed Estimation of Generalized Matrix Rank: Efficient Algorithms and Lower Bounds %t2015 %cICML %f/ICML/ICML-2015-1627.pdf %*Dawen Liang, John Paisley %@Landmarking Manifolds with Gaussian Processes %t2015 %cICML %f/ICML/ICML-2015-1628.pdf %*Aonan Zhang, John Paisley %@Markov Mixed Membership Models %t2015 %cICML %f/ICML/ICML-2015-1629.pdf %*Wenzhuo Yang, Huan Xu %@A Unified Framework for Outlier-Robust PCA-like Algorithms %t2015 %cICML %f/ICML/ICML-2015-1630.pdf %*Wenzhuo Yang, Huan Xu %@A Unified Framework for Outlier-Robust PCA-like Algorithms %t2015 %cICML %f/ICML/ICML-2015-1631.pdf %*Wenzhuo Yang, Huan Xu %@Streaming Sparse Principal Component Analysis %t2015 %cICML %f/ICML/ICML-2015-1632.pdf %*Wenzhuo Yang, Huan Xu %@Streaming Sparse Principal Component Analysis %t2015 %cICML %f/ICML/ICML-2015-1633.pdf %*Wenzhuo Yang, Huan Xu %@A Divide and Conquer Framework for Distributed Graph Clustering %t2015 %cICML %f/ICML/ICML-2015-1634.pdf %*Wenzhuo Yang, Huan Xu %@A Divide and Conquer Framework for Distributed Graph Clustering %t2015 %cICML %f/ICML/ICML-2015-1635.pdf %*Senjian An, Farid Boussaid, Mohammed Bennamoun %@How Can Deep Rectifier Networks Achieve Linear Separability and Preserve Distances? %t2015 %cICML %f/ICML/ICML-2015-1636.pdf %*K. Lakshmanan, Ronald Ortner, Daniil Ryabko %@Improved Regret Bounds for Undiscounted Continuous Reinforcement Learning %t2015 %cICML %f/ICML/ICML-2015-1637.pdf %*Michael Betancourt %@The Fundamental Incompatibility of Scalable Hamiltonian Monte Carlo and Naive Data Subsampling %t2015 %cICML %f/ICML/ICML-2015-1638.pdf %*Dan Garber, Elad Hazan %@Faster Rates for the Frank-Wolfe Method over Strongly-Convex Sets %t2015 %cICML %f/ICML/ICML-2015-1639.pdf %*Dan Garber, Elad Hazan %@Faster Rates for the Frank-Wolfe Method over Strongly-Convex Sets %t2015 %cICML %f/ICML/ICML-2015-1640.pdf %*Mrinal Das, Trapit Bansal, Chiranjib Bhattacharyya %@Ordered Stick-Breaking Prior for Sequential MCMC Inference of Bayesian Nonparametric Models %t2015 %cICML %f/ICML/ICML-2015-1641.pdf %*Mrinal Das, Trapit Bansal, Chiranjib Bhattacharyya %@Ordered Stick-Breaking Prior for Sequential MCMC Inference of Bayesian Nonparametric Models %t2015 %cICML %f/ICML/ICML-2015-1642.pdf %*Dan Garber, Elad Hazan, Tengyu Ma %@Online Learning of Eigenvectors %t2015 %cICML %f/ICML/ICML-2015-1643.pdf %*Dan Garber, Elad Hazan, Tengyu Ma %@Online Learning of Eigenvectors %t2015 %cICML %f/ICML/ICML-2015-1644.pdf %*Trong Nghia Hoang, Quang Minh Hoang, Bryan Kian Hsiang Low %@A Unifying Framework of Anytime Sparse Gaussian Process Regression Models with Stochastic Variational Inference for Big Data %t2015 %cICML %f/ICML/ICML-2015-1645.pdf %*Trong Nghia Hoang, Quang Minh Hoang, Bryan Kian Hsiang Low %@A Unifying Framework of Anytime Sparse Gaussian Process Regression Models with Stochastic Variational Inference for Big Data %t2015 %cICML %f/ICML/ICML-2015-1646.pdf %*Yufei Ding, Yue Zhao, Xipeng Shen, Madanlal Musuvathi, Todd Mytkowicz %@Yinyang K-Means: A Drop-In Replacement of the Classic K-Means with Consistent Speedup %t2015 %cICML %f/ICML/ICML-2015-1647.pdf %*Seppo Virtanen, Mark Girolami %@Ordinal Mixed Membership Models %t2015 %cICML %f/ICML/ICML-2015-1648.pdf %*Seunghoon Hong, Tackgeun You, Suha Kwak, Bohyung Han %@Online Tracking by Learning Discriminative Saliency Map with Convolutional Neural Network %t2015 %cICML %f/ICML/ICML-2015-1649.pdf %*Seth Flaxman, Andrew Wilson, Daniel Neill, Hannes Nickisch, Alex Smola %@Fast Kronecker Inference in Gaussian Processes with non-Gaussian Likelihoods %t2015 %cICML %f/ICML/ICML-2015-1650.pdf %*Seth Flaxman, Andrew Wilson, Daniel Neill, Hannes Nickisch, Alex Smola %@Fast Kronecker Inference in Gaussian Processes with non-Gaussian Likelihoods %t2015 %cICML %f/ICML/ICML-2015-1651.pdf %*Garvesh Raskutti, Michael Mahoney %@Statistical and Algorithmic Perspectives on Randomized Sketching for Ordinary Least-Squares %t2015 %cICML %f/ICML/ICML-2015-1652.pdf %*Nathaniel Korda, Prashanth La %@On TD(0) with function approximation: Concentration bounds and a centered variant with exponential convergence %t2015 %cICML %f/ICML/ICML-2015-1653.pdf %*Roi Weiss, Boaz Nadler %@Learning Parametric-Output HMMs with Two Aliased States %t2015 %cICML %f/ICML/ICML-2015-1654.pdf %*Roi Weiss, Boaz Nadler %@Learning Parametric-Output HMMs with Two Aliased States %t2015 %cICML %f/ICML/ICML-2015-1655.pdf %*Yarin Gal, Yutian Chen, Zoubin Ghahramani %@Latent Gaussian Processes for Distribution Estimation of Multivariate Categorical Data %t2015 %cICML %f/ICML/ICML-2015-1656.pdf %*Yarin Gal, Yutian Chen, Zoubin Ghahramani %@Latent Gaussian Processes for Distribution Estimation of Multivariate Categorical Data %t2015 %cICML %f/ICML/ICML-2015-1657.pdf %*Yarin Gal, Richard Turner %@Improving the Gaussian Process Sparse Spectrum Approximation by Representing Uncertainty in Frequency Inputs %t2015 %cICML %f/ICML/ICML-2015-1658.pdf %*Yarin Gal, Richard Turner %@Improving the Gaussian Process Sparse Spectrum Approximation by Representing Uncertainty in Frequency Inputs %t2015 %cICML %f/ICML/ICML-2015-1659.pdf %*Arun Rajkumar, Suprovat Ghoshal, Lek-Heng Lim, Shivani Agarwal %@Ranking from Stochastic Pairwise Preferences: Recovering Condorcet Winners and Tournament Solution Sets at the Top %t2015 %cICML %f/ICML/ICML-2015-1660.pdf %*Arun Rajkumar, Suprovat Ghoshal, Lek-Heng Lim, Shivani Agarwal %@Ranking from Stochastic Pairwise Preferences: Recovering Condorcet Winners and Tournament Solution Sets at the Top %t2015 %cICML %f/ICML/ICML-2015-1661.pdf %*Dominik Csiba, Zheng Qu, Peter Richtarik %@Stochastic Dual Coordinate Ascent with Adaptive Probabilities %t2015 %cICML %f/ICML/ICML-2015-1662.pdf %*Dominik Csiba, Zheng Qu, Peter Richtarik %@Stochastic Dual Coordinate Ascent with Adaptive Probabilities %t2015 %cICML %f/ICML/ICML-2015-1663.pdf %*Wesley Tansey, Oscar Hernan Madrid Padilla, Arun Sai Suggala, Pradeep Ravikumar %@Vector-Space Markov Random Fields via Exponential Families %t2015 %cICML %f/ICML/ICML-2015-1664.pdf %*Wesley Tansey, Oscar Hernan Madrid Padilla, Arun Sai Suggala, Pradeep Ravikumar %@Vector-Space Markov Random Fields via Exponential Families %t2015 %cICML %f/ICML/ICML-2015-1665.pdf %*Jonathan Huggins, Karthik Narasimhan, Ardavan Saeedi, Vikash Mansinghka %@JUMP-Means: Small-Variance Asymptotics for Markov Jump Processes %t2015 %cICML %f/ICML/ICML-2015-1666.pdf %*Jonathan Huggins, Karthik Narasimhan, Ardavan Saeedi, Vikash Mansinghka %@JUMP-Means: Small-Variance Asymptotics for Markov Jump Processes %t2015 %cICML %f/ICML/ICML-2015-1667.pdf %*Shashanka Ubaru, Arya Mazumdar, Yousef Saad %@Low Rank Approximation using Error Correcting Coding Matrices %t2015 %cICML %f/ICML/ICML-2015-1668.pdf %*Assaf Hallak, Francois Schnitzler, Timothy Mann, Shie Mannor %@Off-policy Model-based Learning under Unknown Factored Dynamics %t2015 %cICML %f/ICML/ICML-2015-1669.pdf %*Assaf Hallak, Francois Schnitzler, Timothy Mann, Shie Mannor %@Off-policy Model-based Learning under Unknown Factored Dynamics %t2015 %cICML %f/ICML/ICML-2015-1670.pdf %*Zhiwu Huang, Ruiping Wang, Shiguang Shan, Xianqiu Li, Xilin Chen %@Log-Euclidean Metric Learning on Symmetric Positive Definite Manifold with Application to Image Set Classification %t2015 %cICML %f/ICML/ICML-2015-1671.pdf %*Melih Kandemir %@Asymmetric Transfer Learning with Deep Gaussian Processes %t2015 %cICML %f/ICML/ICML-2015-1672.pdf %*Rongda Zhu, Quanquan Gu %@Towards a Lower Sample Complexity for Robust One-bit Compressed Sensing %t2015 %cICML %f/ICML/ICML-2015-1673.pdf %*Stephan Gouws, Yoshua Bengio, Greg Corrado %@BilBOWA: Fast Bilingual Distributed Representations without Word Alignments %t2015 %cICML %f/ICML/ICML-2015-1674.pdf %*Jiangwen Sun, Jin Lu, Tingyang Xu, Jinbo Bi %@Multi-view Sparse Co-clustering via Proximal Alternating Linearized Minimization %t2015 %cICML %f/ICML/ICML-2015-1675.pdf %*Jiangwen Sun, Jin Lu, Tingyang Xu, Jinbo Bi %@Multi-view Sparse Co-clustering via Proximal Alternating Linearized Minimization %t2015 %cICML %f/ICML/ICML-2015-1676.pdf %*Branislav Kveton, Csaba Szepesvari, Zheng Wen, Azin Ashkan %@Cascading Bandits: Learning to Rank in the Cascade Model %t2015 %cICML %f/ICML/ICML-2015-1677.pdf %*Branislav Kveton, Csaba Szepesvari, Zheng Wen, Azin Ashkan %@Cascading Bandits: Learning to Rank in the Cascade Model %t2015 %cICML %f/ICML/ICML-2015-1678.pdf %*James Foulds, Shachi Kumar, Lise Getoor %@Latent Topic Networks: A Versatile Probabilistic Programming Framework for Topic Models %t2015 %cICML %f/ICML/ICML-2015-1679.pdf %*James Foulds, Shachi Kumar, Lise Getoor %@Latent Topic Networks: A Versatile Probabilistic Programming Framework for Topic Models %t2015 %cICML %f/ICML/ICML-2015-1680.pdf %*Alina Ene, Huy Nguyen %@Random Coordinate Descent Methods for Minimizing Decomposable Submodular Functions %t2015 %cICML %f/ICML/ICML-2015-1681.pdf %*Alina Ene, Huy Nguyen %@Random Coordinate Descent Methods for Minimizing Decomposable Submodular Functions %t2015 %cICML %f/ICML/ICML-2015-1682.pdf %*Karthik Narayan, Ali Punjani, Pieter Abbeel %@Alpha-Beta Divergences Discover Micro and Macro Structures in Data %t2015 %cICML %f/ICML/ICML-2015-1683.pdf %*Karthik Narayan, Ali Punjani, Pieter Abbeel %@Alpha-Beta Divergences Discover Micro and Macro Structures in Data %t2015 %cICML %f/ICML/ICML-2015-1684.pdf %*Johannes Heinrich, Marc Lanctot, David Silver %@Fictitious Self-Play in Extensive-Form Games %t2015 %cICML %f/ICML/ICML-2015-1685.pdf %*Johannes Heinrich, Marc Lanctot, David Silver %@Fictitious Self-Play in Extensive-Form Games %t2015 %cICML %f/ICML/ICML-2015-1686.pdf %*Adith Swaminathan, Thorsten Joachims %@Counterfactual Risk Minimization: Learning from Logged Bandit Feedback %t2015 %cICML %f/ICML/ICML-2015-1687.pdf %*Walid Krichene, Maximilian Balandat, Claire Tomlin, Alexandre Bayen %@The Hedge Algorithm on a Continuum %t2015 %cICML %f/ICML/ICML-2015-1688.pdf %*Walid Krichene, Maximilian Balandat, Claire Tomlin, Alexandre Bayen %@The Hedge Algorithm on a Continuum %t2015 %cICML %f/ICML/ICML-2015-1689.pdf %*David Belanger, Sham Kakade %@A Linear Dynamical System Model for Text %t2015 %cICML %f/ICML/ICML-2015-1690.pdf %*David Belanger, Sham Kakade %@A Linear Dynamical System Model for Text %t2015 %cICML %f/ICML/ICML-2015-1691.pdf %*Nitish Srivastava, Elman Mansimov, Ruslan Salakhudinov %@Unsupervised Learning of Video Representations using LSTMs %t2015 %cICML %f/ICML/ICML-2015-1692.pdf %*Tao Sun, Dan Sheldon, Akshat Kumar %@Message Passing for Collective Graphical Models %t2015 %cICML %f/ICML/ICML-2015-1693.pdf %*Yining Wang, Jun Zhu %@DP-space: Bayesian Nonparametric Subspace Clustering with Small-variance Asymptotics %t2015 %cICML %f/ICML/ICML-2015-1694.pdf %*Yining Wang, Jun Zhu %@DP-space: Bayesian Nonparametric Subspace Clustering with Small-variance Asymptotics %t2015 %cICML %f/ICML/ICML-2015-1695.pdf %*Xinran He, Theodoros Rekatsinas, James Foulds, Lise Getoor, Yan Liu %@HawkesTopic: A Joint Model for Network Inference and Topic Modeling from Text-Based Cascades %t2015 %cICML %f/ICML/ICML-2015-1696.pdf %*Xinran He, Theodoros Rekatsinas, James Foulds, Lise Getoor, Yan Liu %@HawkesTopic: A Joint Model for Network Inference and Topic Modeling from Text-Based Cascades %t2015 %cICML %f/ICML/ICML-2015-1697.pdf %*Mathieu Germain, Karol Gregor, Iain Murray, Hugo Larochelle %@MADE: Masked Autoencoder for Distribution Estimation %t2015 %cICML %f/ICML/ICML-2015-1698.pdf %*Mathieu Germain, Karol Gregor, Iain Murray, Hugo Larochelle %@MADE: Masked Autoencoder for Distribution Estimation %t2015 %cICML %f/ICML/ICML-2015-1699.pdf %*Yuanbin Wu, Shiliang Sun %@An Online Learning Algorithm for Bilinear Models %t2015 %cICML %f/ICML/ICML-2015-1700.pdf %*Yuanbin Wu, Shiliang Sun %@An Online Learning Algorithm for Bilinear Models %t2015 %cICML %f/ICML/ICML-2015-1701.pdf %*Georgios Papachristoudis, John Fisher %@Adaptive Belief Propagation %t2015 %cICML %f/ICML/ICML-2015-1702.pdf %*Georgios Papachristoudis, John Fisher %@Adaptive Belief Propagation %t2015 %cICML %f/ICML/ICML-2015-1703.pdf %*Insu Han, Dmitry Malioutov, Jinwoo Shin %@Large-scale log-determinant computation through stochastic Chebyshev expansions %t2015 %cICML %f/ICML/ICML-2015-1704.pdf %*Insu Han, Dmitry Malioutov, Jinwoo Shin %@Large-scale log-determinant computation through stochastic Chebyshev expansions %t2015 %cICML %f/ICML/ICML-2015-1705.pdf %*Matt Kusner, Jacob Gardner, Roman Garnett, Kilian Weinberger %@Differentially Private Bayesian Optimization %t2015 %cICML %f/ICML/ICML-2015-1706.pdf %*Matt Kusner, Jacob Gardner, Roman Garnett, Kilian Weinberger %@Differentially Private Bayesian Optimization %t2015 %cICML %f/ICML/ICML-2015-1707.pdf %*Chinmay Hegde, Piotr Indyk, Ludwig Schmidt %@A Nearly-Linear Time Framework for Graph-Structured Sparsity %t2015 %cICML %f/ICML/ICML-2015-1708.pdf %*Chinmay Hegde, Piotr Indyk, Ludwig Schmidt %@A Nearly-Linear Time Framework for Graph-Structured Sparsity %t2015 %cICML %f/ICML/ICML-2015-1709.pdf %*Luo Luo, Yubo Xie, Zhihua Zhang, Wu-Jun Li %@Support Matrix Machines %t2015 %cICML %f/ICML/ICML-2015-1710.pdf %*Luo Luo, Yubo Xie, Zhihua Zhang, Wu-Jun Li %@Support Matrix Machines %t2015 %cICML %f/ICML/ICML-2015-1711.pdf %*Richard Nock, Giorgio Patrini, Arik Friedman %@Rademacher Observations, Private Data, and Boosting %t2015 %cICML %f/ICML/ICML-2015-1712.pdf %*Matt Kusner, Yu Sun, Nicholas Kolkin, Kilian Weinberger %@From Word Embeddings To Document Distances %t2015 %cICML %f/ICML/ICML-2015-1713.pdf %*Taddy Matthew, Chun-Sheng Chen, Jun Yu, Mitch Wyle %@Bayesian and Empirical Bayesian Forests %t2015 %cICML %f/ICML/ICML-2015-1714.pdf %*Jean Pouget-Abadie, Thibaut Horel %@Inferring Graphs from Cascades: A Sparse Recovery Framework %t2015 %cICML %f/ICML/ICML-2015-1715.pdf %*Jean Pouget-Abadie, Thibaut Horel %@Inferring Graphs from Cascades: A Sparse Recovery Framework %t2015 %cICML %f/ICML/ICML-2015-1716.pdf %*Ching-Pei Lee, Dan Roth %@Distributed Box-Constrained Quadratic Optimization for Dual Linear SVM %t2015 %cICML %f/ICML/ICML-2015-1717.pdf %*Ching-Pei Lee, Dan Roth %@Distributed Box-Constrained Quadratic Optimization for Dual Linear SVM %t2015 %cICML %f/ICML/ICML-2015-1718.pdf %*Yanan Sui, Alkis Gotovos, Joel Burdick, Andreas Krause %@Safe Exploration for Optimization with Gaussian Processes %t2015 %cICML %f/ICML/ICML-2015-1719.pdf %*Yanan Sui, Alkis Gotovos, Joel Burdick, Andreas Krause %@Safe Exploration for Optimization with Gaussian Processes %t2015 %cICML %f/ICML/ICML-2015-1720.pdf %*Avrim Blum, Moritz Hardt %@The Ladder: A Reliable Leaderboard for Machine Learning Competitions %t2015 %cICML %f/ICML/ICML-2015-1721.pdf %*Maurizio Filippone, Raphael Engler %@Enabling scalable stochastic gradient-based inference for Gaussian processes by employing the Unbiased LInear System SolvEr (ULISSE) %t2015 %cICML %f/ICML/ICML-2015-1722.pdf %*Roman Garnett, Shirley Ho, Jeff Schneider %@Finding Galaxies in the Shadows of Quasars with Gaussian Processes %t2015 %cICML %f/ICML/ICML-2015-1723.pdf %*Alon Cohen, Tamir Hazan %@Following the Perturbed Leader for Online Structured Learning %t2015 %cICML %f/ICML/ICML-2015-1724.pdf %*Alon Cohen, Tamir Hazan %@Following the Perturbed Leader for Online Structured Learning %t2015 %cICML %f/ICML/ICML-2015-1725.pdf %*Jacob Steinhardt, Percy Liang %@Reified Context Models %t2015 %cICML %f/ICML/ICML-2015-1726.pdf %*Yasin Abbasi-Yadkori, Peter Bartlett, Xi Chen, Alan Malek %@Large-Scale Markov Decision Problems with KL Control Cost and its Application to Crowdsourcing %t2015 %cICML %f/ICML/ICML-2015-1727.pdf %*Yasin Abbasi-Yadkori, Peter Bartlett, Xi Chen, Alan Malek %@Large-Scale Markov Decision Problems with KL Control Cost and its Application to Crowdsourcing %t2015 %cICML %f/ICML/ICML-2015-1728.pdf %*Jacob Steinhardt, Percy Liang %@Learning Fast-Mixing Models for Structured Prediction %t2015 %cICML %f/ICML/ICML-2015-1729.pdf %*Jacob Steinhardt, Percy Liang %@Learning Fast-Mixing Models for Structured Prediction %t2015 %cICML %f/ICML/ICML-2015-1730.pdf %*Daniel Hernandez-Lobato, Jose Miguel Hernandez-Lobato, Zoubin Ghahramani %@A Probabilistic Model for Dirty Multi-task Feature Selection %t2015 %cICML %f/ICML/ICML-2015-1731.pdf %*Weiran Wang, Raman Arora, Karen Livescu, Jeff Bilmes %@On Deep Multi-View Representation Learning %t2015 %cICML %f/ICML/ICML-2015-1732.pdf %*Weiran Wang, Raman Arora, Karen Livescu, Jeff Bilmes %@On Deep Multi-View Representation Learning %t2015 %cICML %f/ICML/ICML-2015-1733.pdf %*Chris Piech, Jonathan Huang, Andy Nguyen, Mike Phulsuksombati, Mehran Sahami, Leonidas Guibas %@Learning Program Embeddings to Propagate Feedback on Student Code %t2015 %cICML %f/ICML/ICML-2015-1734.pdf %*Qiang Zhou, Qi Zhao %@Safe Subspace Screening for Nuclear Norm Regularized Least Squares Problems %t2015 %cICML %f/ICML/ICML-2015-1735.pdf %*Qiang Zhou, Qi Zhao %@Safe Subspace Screening for Nuclear Norm Regularized Least Squares Problems %t2015 %cICML %f/ICML/ICML-2015-1736.pdf %*Zheng Wen, Branislav Kveton, Azin Ashkan %@Efficient Learning in Large-Scale Combinatorial Semi-Bandits %t2015 %cICML %f/ICML/ICML-2015-1737.pdf %*Zheng Wen, Branislav Kveton, Azin Ashkan %@Efficient Learning in Large-Scale Combinatorial Semi-Bandits %t2015 %cICML %f/ICML/ICML-2015-1738.pdf %*Andre Manoel, Florent Krzakala, Eric Tramel, Lenka Zdeborovà %@Swept Approximate Message Passing for Sparse Estimation %t2015 %cICML %f/ICML/ICML-2015-1739.pdf %*Alexandra Carpentier, Michal Valko %@Simple regret for infinitely many armed bandits %t2015 %cICML %f/ICML/ICML-2015-1740.pdf %*Wei-Lun Chao, Justin Solomon, Dominik Michels, Fei Sha %@Exponential Integration for Hamiltonian Monte Carlo %t2015 %cICML %f/ICML/ICML-2015-1741.pdf %*Wei-Lun Chao, Justin Solomon, Dominik Michels, Fei Sha %@Exponential Integration for Hamiltonian Monte Carlo %t2015 %cICML %f/ICML/ICML-2015-1742.pdf %*Junpei Komiyama, Junya Honda, Hiroshi Nakagawa %@Optimal Regret Analysis of Thompson Sampling in Stochastic Multi-armed Bandit Problem with Multiple Plays %t2015 %cICML %f/ICML/ICML-2015-1743.pdf %*Junpei Komiyama, Junya Honda, Hiroshi Nakagawa %@Optimal Regret Analysis of Thompson Sampling in Stochastic Multi-armed Bandit Problem with Multiple Plays %t2015 %cICML %f/ICML/ICML-2015-1744.pdf %*Mike Izbicki, Christian Shelton %@Faster cover trees %t2015 %cICML %f/ICML/ICML-2015-1745.pdf %*Tyler Johnson, Carlos Guestrin %@Blitz: A Principled Meta-Algorithm for Scaling Sparse Optimization %t2015 %cICML %f/ICML/ICML-2015-1746.pdf %*Yaroslav Ganin, Victor Lempitsky %@Unsupervised Domain Adaptation by Backpropagation %t2015 %cICML %f/ICML/ICML-2015-1747.pdf %*Yaroslav Ganin, Victor Lempitsky %@Unsupervised Domain Adaptation by Backpropagation %t2015 %cICML %f/ICML/ICML-2015-1748.pdf %*Yan-Fu Liu, Cheng-Yu Hsu, Shan-Hung Wu %@Non-Linear Cross-Domain Collaborative Filtering via Hyper-Structure Transfer %t2015 %cICML %f/ICML/ICML-2015-1749.pdf %*Yan-Fu Liu, Cheng-Yu Hsu, Shan-Hung Wu %@Non-Linear Cross-Domain Collaborative Filtering via Hyper-Structure Transfer %t2015 %cICML %f/ICML/ICML-2015-1750.pdf %*Hyunwoo Kim, Jia Xu, Baba Vemuri, Vikas Singh %@Manifold-valued Dirichlet Processes %t2015 %cICML %f/ICML/ICML-2015-1751.pdf %*Yu Wang, David Wipf, Qing Ling, Wei Chen, Ian Wassell %@Multi-Task Learning for Subspace Segmentation %t2015 %cICML %f/ICML/ICML-2015-1752.pdf %*Yu Wang, David Wipf, Qing Ling, Wei Chen, Ian Wassell %@Multi-Task Learning for Subspace Segmentation %t2015 %cICML %f/ICML/ICML-2015-1753.pdf %*Tim Salimans, Diederik Kingma, Max Welling %@Markov Chain Monte Carlo and Variational Inference: Bridging the Gap %t2015 %cICML %f/ICML/ICML-2015-1754.pdf %*Chunchen Liu, Lu Feng, Ryohei Fujimaki, Yusuke Muraoka %@Scalable Model Selection for Large-Scale Factorial Relational Models %t2015 %cICML %f/ICML/ICML-2015-1755.pdf %*Rafael Barbosa, Alina Ene, Huy Nguyen, Justin Ward %@The Power of Randomization: Distributed Submodular Maximization on Massive Datasets %t2015 %cICML %f/ICML/ICML-2015-1756.pdf %*Rafael Barbosa, Alina Ene, Huy Nguyen, Justin Ward %@The Power of Randomization: Distributed Submodular Maximization on Massive Datasets %t2015 %cICML %f/ICML/ICML-2015-1757.pdf %*Ralf Eggeling, Mikko Koivisto, Ivo Grosse %@Dealing with small data: On the generalization of context trees %t2015 %cICML %f/ICML/ICML-2015-1758.pdf %*Ralf Eggeling, Mikko Koivisto, Ivo Grosse %@Dealing with small data: On the generalization of context trees %t2015 %cICML %f/ICML/ICML-2015-1759.pdf %*Xin Yuan, Ricardo Henao, Ephraim Tsalik, Raymond Langley, Lawrence Carin %@Non-Gaussian Discriminative Factor Models via the Max-Margin Rank-Likelihood %t2015 %cICML %f/ICML/ICML-2015-1760.pdf %*Alessio Benavoli, Giorgio Corani, Francesca Mangili, Marco Zaffalon %@A Bayesian nonparametric procedure for comparing algorithms %t2015 %cICML %f/ICML/ICML-2015-1761.pdf %*Alessio Benavoli, Giorgio Corani, Francesca Mangili, Marco Zaffalon %@A Bayesian nonparametric procedure for comparing algorithms %t2015 %cICML %f/ICML/ICML-2015-1762.pdf %*Taiji Suzuki %@Convergence rate of Bayesian tensor estimator and its minimax optimality %t2015 %cICML %f/ICML/ICML-2015-1763.pdf %*Taiji Suzuki %@Convergence rate of Bayesian tensor estimator and its minimax optimality %t2015 %cICML %f/ICML/ICML-2015-1764.pdf %*Yifan Wu, Andras Gyorgy, Csaba Szepesvari %@On Identifying Good Options under Combinatorially Structured Feedback in Finite Noisy Environments %t2015 %cICML %f/ICML/ICML-2015-1765.pdf %*Yifan Wu, Andras Gyorgy, Csaba Szepesvari %@On Identifying Good Options under Combinatorially Structured Feedback in Finite Noisy Environments %t2015 %cICML %f/ICML/ICML-2015-1766.pdf %*Christian Naesseth, Fredrik Lindsten, Thomas Schon %@Nested Sequential Monte Carlo Methods %t2015 %cICML %f/ICML/ICML-2015-1767.pdf %*Rishit Sheth, Yuyang Wang, Roni Khardon %@Sparse Variational Inference for Generalized GP Models %t2015 %cICML %f/ICML/ICML-2015-1768.pdf %*Tom Schaul, Daniel Horgan, Karol Gregor, David Silver %@Universal Value Function Approximators %t2015 %cICML %f/ICML/ICML-2015-1769.pdf %*Tom Schaul, Daniel Horgan, Karol Gregor, David Silver %@Universal Value Function Approximators %t2015 %cICML %f/ICML/ICML-2015-1770.pdf %*Julien Perolat, Bruno Scherrer, Bilal Piot, Olivier Pietquin %@Approximate Dynamic Programming for Two-Player Zero-Sum Markov Games %t2015 %cICML %f/ICML/ICML-2015-1771.pdf %*Julien Perolat, Bruno Scherrer, Bilal Piot, Olivier Pietquin %@Approximate Dynamic Programming for Two-Player Zero-Sum Markov Games %t2015 %cICML %f/ICML/ICML-2015-1772.pdf %*Dravyansh Sharma, Ashish Kapoor, Amit Deshpande %@On Greedy Maximization of Entropy %t2015 %cICML %f/ICML/ICML-2015-1773.pdf %*Yi Wang, Bin Li, Yang Wang, Fang Chen %@Metadata Dependent Mondrian Processes %t2015 %cICML %f/ICML/ICML-2015-1774.pdf %*Xiaojun Chang, Yi Yang, Eric Xing, Yaoliang Yu %@Complex Event Detection using Semantic Saliency and Nearly-Isotonic SVM %t2015 %cICML %f/ICML/ICML-2015-1775.pdf %*Xiaojun Chang, Yi Yang, Eric Xing, Yaoliang Yu %@Complex Event Detection using Semantic Saliency and Nearly-Isotonic SVM %t2015 %cICML %f/ICML/ICML-2015-1776.pdf %*Kohei Hayashi, Shin-ichi Maeda, Ryohei Fujimaki %@Rebuilding Factorized Information Criterion: Asymptotically Accurate Marginal Likelihood %t2015 %cICML %f/ICML/ICML-2015-1777.pdf %*Kohei Hayashi, Shin-ichi Maeda, Ryohei Fujimaki %@Rebuilding Factorized Information Criterion: Asymptotically Accurate Marginal Likelihood %t2015 %cICML %f/ICML/ICML-2015-1778.pdf %*Woosang Lim, Minhwan Kim, Haesun Park, Kyomin Jung %@Double Nyström Method: An Efficient and Accurate Nyström Scheme for Large-Scale Data Sets %t2015 %cICML %f/ICML/ICML-2015-1779.pdf %*Woosang Lim, Minhwan Kim, Haesun Park, Kyomin Jung %@Double Nyström Method: An Efficient and Accurate Nyström Scheme for Large-Scale Data Sets %t2015 %cICML %f/ICML/ICML-2015-1780.pdf %*Peter Kairouz, Sewoong Oh, Pramod Viswanath %@The Composition Theorem for Differential Privacy %t2015 %cICML %f/ICML/ICML-2015-1781.pdf %*Peter Kairouz, Sewoong Oh, Pramod Viswanath %@The Composition Theorem for Differential Privacy %t2015 %cICML %f/ICML/ICML-2015-1782.pdf %*Marthinus Du Plessis, Gang Niu, Masashi Sugiyama %@Convex Formulation for Learning from Positive and Unlabeled Data %t2015 %cICML %f/ICML/ICML-2015-1783.pdf %*Marthinus Du Plessis, Gang Niu, Masashi Sugiyama %@Convex Formulation for Learning from Positive and Unlabeled Data %t2015 %cICML %f/ICML/ICML-2015-1784.pdf %*Atsushi Miyauchi, Yuni Iwamasa, Takuro Fukunaga, Naonori Kakimura %@Threshold Influence Model for Allocating Advertising Budgets %t2015 %cICML %f/ICML/ICML-2015-1785.pdf %*Atsushi Miyauchi, Yuni Iwamasa, Takuro Fukunaga, Naonori Kakimura %@Threshold Influence Model for Allocating Advertising Budgets %t2015 %cICML %f/ICML/ICML-2015-1786.pdf %*Amit Daniely, Alon Gonen, Shai Shalev-Shwartz %@Strongly Adaptive Online Learning %t2015 %cICML %f/ICML/ICML-2015-1787.pdf %*Amit Daniely, Alon Gonen, Shai Shalev-Shwartz %@Strongly Adaptive Online Learning %t2015 %cICML %f/ICML/ICML-2015-1788.pdf %*Miao Xu, Rong Jin, Zhi-Hua Zhou %@CUR Algorithm for Partially Observed Matrices %t2015 %cICML %f/ICML/ICML-2015-1789.pdf %*Miao Xu, Rong Jin, Zhi-Hua Zhou %@CUR Algorithm for Partially Observed Matrices %t2015 %cICML %f/ICML/ICML-2015-1790.pdf %*Yining Wang, Yu-Xiang Wang, Aarti Singh %@A Deterministic Analysis of Noisy Sparse Subspace Clustering for Dimensionality-reduced Data %t2015 %cICML %f/ICML/ICML-2015-1791.pdf %*Yining Wang, Yu-Xiang Wang, Aarti Singh %@A Deterministic Analysis of Noisy Sparse Subspace Clustering for Dimensionality-reduced Data %t2015 %cICML %f/ICML/ICML-2015-1792.pdf %*Eric Sibony, Stéphan Clemençon, Jérémie Jakubowicz %@MRA-based Statistical Learning from Incomplete Rankings %t2015 %cICML %f/ICML/ICML-2015-1793.pdf %*Eric Sibony, Stéphan Clemençon, Jérémie Jakubowicz %@MRA-based Statistical Learning from Incomplete Rankings %t2015 %cICML %f/ICML/ICML-2015-1794.pdf %*Jonathan Huggins, Josh Tenenbaum %@Risk and Regret of Hierarchical Bayesian Learners %t2015 %cICML %f/ICML/ICML-2015-1795.pdf %*Jonathan Huggins, Josh Tenenbaum %@Risk and Regret of Hierarchical Bayesian Learners %t2015 %cICML %f/ICML/ICML-2015-1796.pdf %*David Lopez-Paz, Krikamol Muandet, Bernhard Schölkopf, Iliya Tolstikhin %@Towards a Learning Theory of Cause-Effect Inference %t2015 %cICML %f/ICML/ICML-2015-1797.pdf %*David Lopez-Paz, Krikamol Muandet, Bernhard Schölkopf, Iliya Tolstikhin %@Towards a Learning Theory of Cause-Effect Inference %t2015 %cICML %f/ICML/ICML-2015-1798.pdf %*Karol Gregor, Ivo Danihelka, Alex Graves, Danilo Rezende, Daan Wierstra %@DRAW: A Recurrent Neural Network For Image Generation %t2015 %cICML %f/ICML/ICML-2015-1799.pdf %*Ehsan Amid, Antti Ukkonen %@Multiview Triplet Embedding: Learning Attributes in Multiple Maps %t2015 %cICML %f/ICML/ICML-2015-1800.pdf %*Marc Deisenroth, Jun Wei Ng %@Distributed Gaussian Processes %t2015 %cICML %f/ICML/ICML-2015-1801.pdf %*Gongguo Tang, Parikshit Shah %@Guaranteed Tensor Decomposition: A Moment Approach %t2015 %cICML %f/ICML/ICML-2015-1802.pdf %*Gongguo Tang, Parikshit Shah %@Guaranteed Tensor Decomposition: A Moment Approach %t2015 %cICML %f/ICML/ICML-2015-1803.pdf %*\(\ell_{1,p}\) Zirui Zhou, Qi Zhang, Anthony Man-Cho So %@\(\ell_{1,p}\)-Norm Regularization: Error Bounds and Convergence Rate Analysis of First-Order Methods %t2015 %cICML %f/ICML/ICML-2015-1804.pdf %*\(\ell_{1,p}\) Zirui Zhou, Qi Zhang, Anthony Man-Cho So %@\(\ell_{1,p}\)-Norm Regularization: Error Bounds and Convergence Rate Analysis of First-Order Methods %t2015 %cICML %f/ICML/ICML-2015-1805.pdf %*Qiuyi Han, Kevin Xu, Edoardo Airoldi %@Consistent estimation of dynamic and multi-layer block models %t2015 %cICML %f/ICML/ICML-2015-1806.pdf %*\(\lambda\) Manel Tagorti, Bruno Scherrer %@On the Rate of Convergence and Error Bounds for LSTD(\(\lambda\)) %t2015 %cICML %f/ICML/ICML-2015-1807.pdf %*\(\lambda\) Manel Tagorti, Bruno Scherrer %@On the Rate of Convergence and Error Bounds for LSTD(\(\lambda\)) %t2015 %cICML %f/ICML/ICML-2015-1808.pdf %*Danilo Rezende, Shakir Mohamed %@Variational Inference with Normalizing Flows %t2015 %cICML %f/ICML/ICML-2015-1809.pdf %*Danilo Rezende, Shakir Mohamed %@Variational Inference with Normalizing Flows %t2015 %cICML %f/ICML/ICML-2015-1810.pdf %*Benn Macdonald, Catherine Higham, Dirk Husmeier %@Controversy in mechanistic modelling with Gaussian processes %t2015 %cICML %f/ICML/ICML-2015-1811.pdf %*Carlo Ciliberto, Youssef Mroueh, Tomaso Poggio, Lorenzo Rosasco %@Convex Learning of Multiple Tasks and their Structure %t2015 %cICML %f/ICML/ICML-2015-1812.pdf %*Carlo Ciliberto, Youssef Mroueh, Tomaso Poggio, Lorenzo Rosasco %@Convex Learning of Multiple Tasks and their Structure %t2015 %cICML %f/ICML/ICML-2015-1813.pdf %*Margarita Osadchy, Tamir Hazan, Daniel Keren %@K-hyperplane Hinge-Minimax Classifier %t2015 %cICML %f/ICML/ICML-2015-1814.pdf %*Boris Lesner, Bruno Scherrer %@Non-Stationary Approximate Modified Policy Iteration %t2015 %cICML %f/ICML/ICML-2015-1815.pdf %*Boris Lesner, Bruno Scherrer %@Non-Stationary Approximate Modified Policy Iteration %t2015 %cICML %f/ICML/ICML-2015-1816.pdf %*Mathieu Serrurier, Henri Prade %@Entropy evaluation based on confidence intervals of frequency estimates : Application to the learning of decision trees %t2015 %cICML %f/ICML/ICML-2015-1817.pdf %*Chong You, Rene Vidal %@Geometric Conditions for Subspace-Sparse Recovery %t2015 %cICML %f/ICML/ICML-2015-1818.pdf %*Chong You, Rene Vidal %@Geometric Conditions for Subspace-Sparse Recovery %t2015 %cICML %f/ICML/ICML-2015-1819.pdf %*Amar Shah, David Knowles, Zoubin Ghahramani %@An Empirical Study of Stochastic Variational Inference Algorithms for the Beta Bernoulli Process %t2015 %cICML %f/ICML/ICML-2015-1820.pdf %*Amar Shah, David Knowles, Zoubin Ghahramani %@An Empirical Study of Stochastic Variational Inference Algorithms for the Beta Bernoulli Process %t2015 %cICML %f/ICML/ICML-2015-1821.pdf %*Xiaodan Zhu, Parinaz Sobihani, Hongyu Guo %@Long Short-Term Memory Over Recursive Structures %t2015 %cICML %f/ICML/ICML-2015-1822.pdf %*Charles Blundell, Julien Cornebise, Koray Kavukcuoglu, Daan Wierstra %@Weight Uncertainty in Neural Network %t2015 %cICML %f/ICML/ICML-2015-1823.pdf %*Jiaqian Yu, Matthew Blaschko %@Learning Submodular Losses with the Lovasz Hinge %t2015 %cICML %f/ICML/ICML-2015-1824.pdf %*Julie Nutini, Mark Schmidt, Issam Laradji, Michael Friedlander, Hoyt Koepke %@Coordinate Descent Converges Faster with the Gauss-Southwell Rule Than Random Selection %t2015 %cICML %f/ICML/ICML-2015-1825.pdf %*Julie Nutini, Mark Schmidt, Issam Laradji, Michael Friedlander, Hoyt Koepke %@Coordinate Descent Converges Faster with the Gauss-Southwell Rule Than Random Selection %t2015 %cICML %f/ICML/ICML-2015-1826.pdf %*Cong Leng, Jiaxiang Wu, Jian Cheng, Xi Zhang, Hanqing Lu %@Hashing for Distributed Data %t2015 %cICML %f/ICML/ICML-2015-1827.pdf %*Zhiting Hu, Ho Qirong, Avinava Dubey, Eric Xing %@Large-scale Distributed Dependent Nonparametric Trees %t2015 %cICML %f/ICML/ICML-2015-1828.pdf %*Zhiting Hu, Ho Qirong, Avinava Dubey, Eric Xing %@Large-scale Distributed Dependent Nonparametric Trees %t2015 %cICML %f/ICML/ICML-2015-1829.pdf %*Balazs Szorenyi, Robert Busa-Fekete, Paul Weng, Eyke Hüllermeier %@Qualitative Multi-Armed Bandits: A Quantile-Based Approach %t2015 %cICML %f/ICML/ICML-2015-1830.pdf %*Balazs Szorenyi, Robert Busa-Fekete, Paul Weng, Eyke Hüllermeier %@Qualitative Multi-Armed Bandits: A Quantile-Based Approach %t2015 %cICML %f/ICML/ICML-2015-1831.pdf %*Li Xu, Jimmy Ren, Qiong Yan, Renjie Liao, Jiaya Jia %@Deep Edge-Aware Filters %t2015 %cICML %f/ICML/ICML-2015-1832.pdf %*Shiau Hong Lim, Yudong Chen, Huan Xu %@A Convex Optimization Framework for Bi-Clustering %t2015 %cICML %f/ICML/ICML-2015-1833.pdf %*Shiau Hong Lim, Yudong Chen, Huan Xu %@A Convex Optimization Framework for Bi-Clustering %t2015 %cICML %f/ICML/ICML-2015-1834.pdf %*Huang Xiao, Battista Biggio, Gavin Brown, Giorgio Fumera, Claudia Eckert, Fabio Roli %@Is Feature Selection Secure against Training Data Poisoning? %t2015 %cICML %f/ICML/ICML-2015-1835.pdf %*Jose Miguel Hernandez-Lobato, Michael Gelbart, Matthew Hoffman, Ryan Adams, Zoubin Ghahramani %@Predictive Entropy Search for Bayesian Optimization with Unknown Constraints %t2015 %cICML %f/ICML/ICML-2015-1836.pdf %*Jose Miguel Hernandez-Lobato, Michael Gelbart, Matthew Hoffman, Ryan Adams, Zoubin Ghahramani %@Predictive Entropy Search for Bayesian Optimization with Unknown Constraints %t2015 %cICML %f/ICML/ICML-2015-1837.pdf %*Michaël Perrot, Amaury Habrard %@A Theoretical Analysis of Metric Hypothesis Transfer Learning %t2015 %cICML %f/ICML/ICML-2015-1838.pdf %*Michaël Perrot, Amaury Habrard %@A Theoretical Analysis of Metric Hypothesis Transfer Learning %t2015 %cICML %f/ICML/ICML-2015-1839.pdf %*Yujia Li, Kevin Swersky, Rich Zemel %@Generative Moment Matching Networks %t2015 %cICML %f/ICML/ICML-2015-1840.pdf %*Megasthenis Asteris, Anastasios Kyrillidis, Alex Dimakis, Han-Gyol Yi, Bharath Chandrasekaran %@Stay on path: PCA along graph paths %t2015 %cICML %f/ICML/ICML-2015-1841.pdf %*Megasthenis Asteris, Anastasios Kyrillidis, Alex Dimakis, Han-Gyol Yi, Bharath Chandrasekaran %@Stay on path: PCA along graph paths %t2015 %cICML %f/ICML/ICML-2015-1842.pdf %*Suyog Gupta, Ankur Agrawal, Kailash Gopalakrishnan, Pritish Narayanan %@Deep Learning with Limited Numerical Precision %t2015 %cICML %f/ICML/ICML-2015-1843.pdf %*Jie Wang, Jieping Ye %@Safe Screening for Multi-Task Feature Learning with Multiple Data Matrices %t2015 %cICML %f/ICML/ICML-2015-1844.pdf %*Taco Cohen, Max Welling %@Harmonic Exponential Families on Manifolds %t2015 %cICML %f/ICML/ICML-2015-1845.pdf %*Taco Cohen, Max Welling %@Harmonic Exponential Families on Manifolds %t2015 %cICML %f/ICML/ICML-2015-1846.pdf %*Christopher Clark, Amos Storkey %@Training Deep Convolutional Neural Networks to Play Go %t2015 %cICML %f/ICML/ICML-2015-1847.pdf %*Andrew Wilson, Hannes Nickisch %@Kernel Interpolation for Scalable Structured Gaussian Processes (KISS-GP) %t2015 %cICML %f/ICML/ICML-2015-1848.pdf %*Andrew Wilson, Hannes Nickisch %@Kernel Interpolation for Scalable Structured Gaussian Processes (KISS-GP) %t2015 %cICML %f/ICML/ICML-2015-1849.pdf %*Liang-Chieh Chen, Alexander Schwing, Alan Yuille, Raquel Urtasun %@Learning Deep Structured Models %t2015 %cICML %f/ICML/ICML-2015-1850.pdf %*Haim Avron, Lior Horesh %@Community Detection Using Time-Dependent Personalized PageRank %t2015 %cICML %f/ICML/ICML-2015-1851.pdf %*Haim Avron, Lior Horesh %@Community Detection Using Time-Dependent Personalized PageRank %t2015 %cICML %f/ICML/ICML-2015-1852.pdf %*Josip Djolonga, Andreas Krause %@Scalable Variational Inference in Log-supermodular Models %t2015 %cICML %f/ICML/ICML-2015-1853.pdf %*Josip Djolonga, Andreas Krause %@Scalable Variational Inference in Log-supermodular Models %t2015 %cICML %f/ICML/ICML-2015-1854.pdf %*Chris Lloyd, Tom Gunter, Michael Osborne, Stephen Roberts %@Variational Inference for Gaussian Process Modulated Poisson Processes %t2015 %cICML %f/ICML/ICML-2015-1855.pdf %*Zhe Gan, Changyou Chen, Ricardo Henao, David Carlson, Lawrence Carin %@Scalable Deep Poisson Factor Analysis for Topic Modeling %t2015 %cICML %f/ICML/ICML-2015-1856.pdf %*Zhe Gan, Changyou Chen, Ricardo Henao, David Carlson, Lawrence Carin %@Scalable Deep Poisson Factor Analysis for Topic Modeling %t2015 %cICML %f/ICML/ICML-2015-1857.pdf %*Nico Goernitz, Mikio Braun, Marius Kloft %@Hidden Markov Anomaly Detection %t2015 %cICML %f/ICML/ICML-2015-1858.pdf %*Nico Goernitz, Mikio Braun, Marius Kloft %@Hidden Markov Anomaly Detection %t2015 %cICML %f/ICML/ICML-2015-1859.pdf %*Huitong Qiu, Sheng Xu, Fang Han, Han Liu, Brian Caffo %@Robust Estimation of Transition Matrices in High Dimensional Heavy-tailed Vector Autoregressive Processes %t2015 %cICML %f/ICML/ICML-2015-1860.pdf %*Huitong Qiu, Sheng Xu, Fang Han, Han Liu, Brian Caffo %@Robust Estimation of Transition Matrices in High Dimensional Heavy-tailed Vector Autoregressive Processes %t2015 %cICML %f/ICML/ICML-2015-1861.pdf %*Harish Ramaswamy, Ambuj Tewari, Shivani Agarwal %@Convex Calibrated Surrogates for Hierarchical Classification %t2015 %cICML %f/ICML/ICML-2015-1862.pdf %*Harish Ramaswamy, Ambuj Tewari, Shivani Agarwal %@Convex Calibrated Surrogates for Hierarchical Classification %t2015 %cICML %f/ICML/ICML-2015-1863.pdf %*Jose Miguel Hernandez-Lobato, Ryan Adams %@Probabilistic Backpropagation for Scalable Learning of Bayesian Neural Networks %t2015 %cICML %f/ICML/ICML-2015-1864.pdf %*Jose Miguel Hernandez-Lobato, Ryan Adams %@Probabilistic Backpropagation for Scalable Learning of Bayesian Neural Networks %t2015 %cICML %f/ICML/ICML-2015-1865.pdf %*Christopher Berlind, Ruth Urner %@Active Nearest Neighbors in Changing Environments %t2015 %cICML %f/ICML/ICML-2015-1866.pdf %*Christopher Berlind, Ruth Urner %@Active Nearest Neighbors in Changing Environments %t2015 %cICML %f/ICML/ICML-2015-1867.pdf %*Hanxiao Liu, Yiming Yang %@Bipartite Edge Prediction via Transductive Learning over Product Graphs %t2015 %cICML %f/ICML/ICML-2015-1868.pdf %*Hanxiao Liu, Yiming Yang %@Bipartite Edge Prediction via Transductive Learning over Product Graphs %t2015 %cICML %f/ICML/ICML-2015-1869.pdf %*John Schulman, Sergey Levine, Pieter Abbeel, Michael Jordan, Philipp Moritz %@Trust Region Policy Optimization %t2015 %cICML %f/ICML/ICML-2015-1870.pdf %*John Schulman, Sergey Levine, Pieter Abbeel, Michael Jordan, Philipp Moritz %@Trust Region Policy Optimization %t2015 %cICML %f/ICML/ICML-2015-1871.pdf %*Mingming Gong, Kun Zhang, Bernhard Schoelkopf, Dacheng Tao, Philipp Geiger %@Discovering Temporal Causal Relations from Subsampled Data %t2015 %cICML %f/ICML/ICML-2015-1872.pdf %*Mingming Gong, Kun Zhang, Bernhard Schoelkopf, Dacheng Tao, Philipp Geiger %@Discovering Temporal Causal Relations from Subsampled Data %t2015 %cICML %f/ICML/ICML-2015-1873.pdf %*Dohyung Park, Joe Neeman, Jin Zhang, Sujay Sanghavi, Inderjit Dhillon %@Preference Completion: Large-scale Collaborative Ranking from Pairwise Comparisons %t2015 %cICML %f/ICML/ICML-2015-1874.pdf %*Dohyung Park, Joe Neeman, Jin Zhang, Sujay Sanghavi, Inderjit Dhillon %@Preference Completion: Large-scale Collaborative Ranking from Pairwise Comparisons %t2015 %cICML %f/ICML/ICML-2015-1875.pdf %*Philipp Geiger, Kun Zhang, Bernhard Schoelkopf, Mingming Gong, Dominik Janzing %@Causal Inference by Identification of Vector Autoregressive Processes with Hidden Components %t2015 %cICML %f/ICML/ICML-2015-1876.pdf %*Behnam Neyshabur, Nathan Srebro %@On Symmetric and Asymmetric LSHs for Inner Product Search %t2015 %cICML %f/ICML/ICML-2015-1877.pdf %*Behnam Neyshabur, Nathan Srebro %@On Symmetric and Asymmetric LSHs for Inner Product Search %t2015 %cICML %f/ICML/ICML-2015-1878.pdf %*Yunlong Jiao, Jean-Philippe Vert %@The Kendall and Mallows Kernels for Permutations %t2015 %cICML %f/ICML/ICML-2015-1879.pdf %*Yunlong Jiao, Jean-Philippe Vert %@The Kendall and Mallows Kernels for Permutations %t2015 %cICML %f/ICML/ICML-2015-1880.pdf %*Purnima Rajan, Weidong Han, Raphael Sznitman, Peter Frazier, Bruno Jedynak %@Bayesian Multiple Target Localization %t2015 %cICML %f/ICML/ICML-2015-1881.pdf %*Purnima Rajan, Weidong Han, Raphael Sznitman, Peter Frazier, Bruno Jedynak %@Bayesian Multiple Target Localization %t2015 %cICML %f/ICML/ICML-2015-1882.pdf %*Kai Wei, Rishabh Iyer, Jeff Bilmes %@Submodularity in Data Subset Selection and Active Learning %t2015 %cICML %f/ICML/ICML-2015-1883.pdf %*Kai Wei, Rishabh Iyer, Jeff Bilmes %@Submodularity in Data Subset Selection and Active Learning %t2015 %cICML %f/ICML/ICML-2015-1884.pdf %*Philip Bachman, Doina Precup %@Variational Generative Stochastic Networks with Collaborative Shaping %t2015 %cICML %f/ICML/ICML-2015-1885.pdf %*Philip Bachman, Doina Precup %@Variational Generative Stochastic Networks with Collaborative Shaping %t2015 %cICML %f/ICML/ICML-2015-1886.pdf %*Chenxin Ma, Virginia Smith, Martin Jaggi, Michael Jordan, Peter Richtarik, Martin Takac %@Adding vs. Averaging in Distributed Primal-Dual Optimization %t2015 %cICML %f/ICML/ICML-2015-1887.pdf %*Chenxin Ma, Virginia Smith, Martin Jaggi, Michael Jordan, Peter Richtarik, Martin Takac %@Adding vs. Averaging in Distributed Primal-Dual Optimization %t2015 %cICML %f/ICML/ICML-2015-1888.pdf %*Feng Nan, Joseph Wang, Venkatesh Saligrama %@Feature-Budgeted Random Forest %t2015 %cICML %f/ICML/ICML-2015-1889.pdf %*Feng Nan, Joseph Wang, Venkatesh Saligrama %@Feature-Budgeted Random Forest %t2015 %cICML %f/ICML/ICML-2015-1890.pdf %*Maxwell Libbrecht, Michael Hoffman, Jeff Bilmes, William Noble %@Entropic Graph-based Posterior Regularization %t2015 %cICML %f/ICML/ICML-2015-1891.pdf %*Maxwell Libbrecht, Michael Hoffman, Jeff Bilmes, William Noble %@Entropic Graph-based Posterior Regularization %t2015 %cICML %f/ICML/ICML-2015-1892.pdf %*Tam Le, Marco Cuturi %@Unsupervised Riemannian Metric Learning for Histograms Using Aitchison Transformations %t2015 %cICML %f/ICML/ICML-2015-1893.pdf %*Tam Le, Marco Cuturi %@Unsupervised Riemannian Metric Learning for Histograms Using Aitchison Transformations %t2015 %cICML %f/ICML/ICML-2015-1894.pdf %*Or Zuk, Avishai Wagner %@Low-Rank Matrix Recovery from Row-and-Column Affine Measurements %t2015 %cICML %f/ICML/ICML-2015-1895.pdf %*Or Zuk, Avishai Wagner %@Low-Rank Matrix Recovery from Row-and-Column Affine Measurements %t2015 %cICML %f/ICML/ICML-2015-1896.pdf %*Sébastien Giguère, Amélie Rolland, Francois Laviolette, Mario Marchand %@Algorithms for the Hard Pre-Image Problem of String Kernels and the General Problem of String Prediction %t2015 %cICML %f/ICML/ICML-2015-1897.pdf %*Sébastien Giguère, Amélie Rolland, Francois Laviolette, Mario Marchand %@Algorithms for the Hard Pre-Image Problem of String Kernels and the General Problem of String Prediction %t2015 %cICML %f/ICML/ICML-2015-1898.pdf %*Wenzhao Lian, Ricardo Henao, Vinayak Rao, Joseph Lucas, Lawrence Carin %@A Multitask Point Process Predictive Model %t2015 %cICML %f/ICML/ICML-2015-1899.pdf %*Wenzhao Lian, Ricardo Henao, Vinayak Rao, Joseph Lucas, Lawrence Carin %@A Multitask Point Process Predictive Model %t2015 %cICML %f/ICML/ICML-2015-1900.pdf %*Michael Zhu, Stefano Ermon %@A Hybrid Approach for Probabilistic Inference using Random Projections %t2015 %cICML %f/ICML/ICML-2015-1901.pdf %*Michael Zhu, Stefano Ermon %@A Hybrid Approach for Probabilistic Inference using Random Projections %t2015 %cICML %f/ICML/ICML-2015-1902.pdf %*Kelvin Xu, Jimmy Ba, Ryan Kiros, Kyunghyun Cho, Aaron Courville, Ruslan Salakhudinov, Rich Zemel, Yoshua Bengio %@Show, Attend and Tell: Neural Image Caption Generation with Visual Attention %t2015 %cICML %f/ICML/ICML-2015-1903.pdf %*Kelvin Xu, Jimmy Ba, Ryan Kiros, Kyunghyun Cho, Aaron Courville, Ruslan Salakhudinov, Rich Zemel, Yoshua Bengio %@Show, Attend and Tell: Neural Image Caption Generation with Visual Attention %t2015 %cICML %f/ICML/ICML-2015-1904.pdf %*Kai-Wei Chang, Akshay Krishnamurthy, Alekh Agarwal, Hal Daume, John Langford %@Learning to Search Better than Your Teacher %t2015 %cICML %f/ICML/ICML-2015-1905.pdf %*Kai-Wei Chang, Akshay Krishnamurthy, Alekh Agarwal, Hal Daume, John Langford %@Learning to Search Better than Your Teacher %t2015 %cICML %f/ICML/ICML-2015-1906.pdf %*Junyoung Chung, Caglar Gulcehre, Kyunghyun Cho, Yoshua Bengio %@Gated Feedback Recurrent Neural Networks %t2015 %cICML %f/ICML/ICML-2015-1907.pdf %*Junyoung Chung, Caglar Gulcehre, Kyunghyun Cho, Yoshua Bengio %@Gated Feedback Recurrent Neural Networks %t2015 %cICML %f/ICML/ICML-2015-1908.pdf %*Erfan Soltanmohammadi, Mort Naraghi-Pour, Mihaela van der Schaar %@Context-based Unsupervised Data Fusion for Decision Making %t2015 %cICML %f/ICML/ICML-2015-1909.pdf %*Remi Lebret, Pedro Pinheiro, Ronan Collobert %@Phrase-based Image Captioning %t2015 %cICML %f/ICML/ICML-2015-1910.pdf %*Jeffrey Regier, Andrew Miller, Jon McAuliffe, Ryan Adams, Matt Hoffman, Dustin Lang, David Schlegel, Mr Prabhat %@Celeste: Variational inference for a generative model of astronomical images %t2015 %cICML %f/ICML/ICML-2015-1911.pdf %*Adarsh Prasad, Harsh Pareek, Pradeep Ravikumar %@Distributional Rank Aggregation, and an Axiomatic Analysis %t2015 %cICML %f/ICML/ICML-2015-1912.pdf %*Adarsh Prasad, Harsh Pareek, Pradeep Ravikumar %@Distributional Rank Aggregation, and an Axiomatic Analysis %t2015 %cICML %f/ICML/ICML-2015-1913.pdf %*Dougal Maclaurin, David Duvenaud, Ryan Adams %@Gradient-based Hyperparameter Optimization through Reversible Learning %t2015 %cICML %f/ICML/ICML-2015-1914.pdf %*Dougal Maclaurin, David Duvenaud, Ryan Adams %@Gradient-based Hyperparameter Optimization through Reversible Learning %t2015 %cICML %f/ICML/ICML-2015-1915.pdf %*Miltos Allamanis, Daniel Tarlow, Andrew Gordon, Yi Wei %@Bimodal Modelling of Source Code and Natural Language %t2015 %cICML %f/ICML/ICML-2015-1916.pdf %*Miltos Allamanis, Daniel Tarlow, Andrew Gordon, Yi Wei %@Bimodal Modelling of Source Code and Natural Language %t2015 %cICML %f/ICML/ICML-2015-1917.pdf %*Manjesh Hanawal, Venkatesh Saligrama, Michal Valko, Remi Munos %@Cheap Bandits %t2015 %cICML %f/ICML/ICML-2015-1918.pdf %*Manjesh Hanawal, Venkatesh Saligrama, Michal Valko, Remi Munos %@Cheap Bandits %t2015 %cICML %f/ICML/ICML-2015-1919.pdf %*Frederic Chazal, Brittany Fasy, Fabrizio Lecci, Bertrand Michel, Alessandro Rinaldo, Larry Wasserman %@Subsampling Methods for Persistent Homology %t2015 %cICML %f/ICML/ICML-2015-1920.pdf %*Frederic Chazal, Brittany Fasy, Fabrizio Lecci, Bertrand Michel, Alessandro Rinaldo, Larry Wasserman %@Subsampling Methods for Persistent Homology %t2015 %cICML %f/ICML/ICML-2015-1921.pdf %*Bernardino Romera-Paredes, Philip Torr %@An embarrassingly simple approach to zero-shot learning %t2015 %cICML %f/ICML/ICML-2015-1922.pdf %*Bernardino Romera-Paredes, Philip Torr %@An embarrassingly simple approach to zero-shot learning %t2015 %cICML %f/ICML/ICML-2015-1923.pdf %*Xinyang Yi, Constantine Caramanis, Eric Price %@Binary Embedding: Fundamental Limits and Fast Algorithm %t2015 %cICML %f/ICML/ICML-2015-1924.pdf %*Xinyang Yi, Constantine Caramanis, Eric Price %@Binary Embedding: Fundamental Limits and Fast Algorithm %t2015 %cICML %f/ICML/ICML-2015-1925.pdf %*Jasper Snoek, Oren Rippel, Kevin Swersky, Ryan Kiros, Nadathur Satish, Narayanan Sundaram, Mostofa Patwary, Mr Prabhat, Ryan Adams %@Scalable Bayesian Optimization Using Deep Neural Networks %t2015 %cICML %f/ICML/ICML-2015-1926.pdf %*Jasper Snoek, Oren Rippel, Kevin Swersky, Ryan Kiros, Nadathur Satish, Narayanan Sundaram, Mostofa Patwary, Mr Prabhat, Ryan Adams %@Scalable Bayesian Optimization Using Deep Neural Networks %t2015 %cICML %f/ICML/ICML-2015-1927.pdf %*Amir Globerson, Tim Roughgarden, David Sontag, Cafer Yildirim %@How Hard is Inference for Structured Prediction? %t2015 %cICML %f/ICML/ICML-2015-1928.pdf %*Amir Globerson, Tim Roughgarden, David Sontag, Cafer Yildirim %@How Hard is Inference for Structured Prediction? %t2015 %cICML %f/ICML/ICML-2015-1929.pdf %*Oren Anava, Elad Hazan, Assaf Zeevi %@Online Time Series Prediction with Missing Data %t2015 %cICML %f/ICML/ICML-2015-1930.pdf %*Oren Anava, Elad Hazan, Assaf Zeevi %@Online Time Series Prediction with Missing Data %t2015 %cICML %f/ICML/ICML-2015-1931.pdf %*Jason Pacheco, Erik Sudderth %@Proteins, Particles, and Pseudo-Max-Marginals: A Submodular Approach %t2015 %cICML %f/ICML/ICML-2015-1932.pdf %*Yacine Jernite, Alexander Rush, David Sontag %@A Fast Variational Approach for Learning Markov Random Field Language Models %t2015 %cICML %f/ICML/ICML-2015-1933.pdf %*Yacine Jernite, Alexander Rush, David Sontag %@A Fast Variational Approach for Learning Markov Random Field Language Models %t2015 %cICML %f/ICML/ICML-2015-1934.pdf %*Bernhard Schölkopf, David Hogg, Dun Wang, Dan Foreman-Mackey, Dominik Janzing, Carl-Johann Simon-Gabriel, Jonas Peters %@Removing systematic errors for exoplanet search via latent causes %t2015 %cICML %f/ICML/ICML-2015-1935.pdf %*Yves-Laurent Kom Samo, Stephen Roberts %@Scalable Nonparametric Bayesian Inference on Point Processes with Gaussian Processes %t2015 %cICML %f/ICML/ICML-2015-1936.pdf %*Yves-Laurent Kom Samo, Stephen Roberts %@Scalable Nonparametric Bayesian Inference on Point Processes with Gaussian Processes %t2015 %cICML %f/ICML/ICML-2015-1937.pdf %*KookJin Ahn, Graham Cormode, Sudipto Guha, Andrew McGregor, Anthony Wirth %@Correlation Clustering in Data Streams %t2015 %cICML %f/ICML/ICML-2015-1938.pdf %*Qingming Tang, Siqi Sun, Jinbo Xu %@Learning Scale-Free Networks by Dynamic Node Specific Degree Prior %t2015 %cICML %f/ICML/ICML-2015-1939.pdf %*Qingming Tang, Siqi Sun, Jinbo Xu %@Learning Scale-Free Networks by Dynamic Node Specific Degree Prior %t2015 %cICML %f/ICML/ICML-2015-1940.pdf %*Jascha Sohl-Dickstein, Eric Weiss, Niru Maheswaranathan, Surya Ganguli %@Deep Unsupervised Learning using Nonequilibrium Thermodynamics %t2015 %cICML %f/ICML/ICML-2015-1941.pdf %*Jascha Sohl-Dickstein, Eric Weiss, Niru Maheswaranathan, Surya Ganguli %@Deep Unsupervised Learning using Nonequilibrium Thermodynamics %t2015 %cICML %f/ICML/ICML-2015-1942.pdf %*Andrew Trask, David Gilmore, Matthew Russell %@Modeling Order in Neural Word Embeddings at Scale %t2015 %cICML %f/ICML/ICML-2015-1943.pdf %*Hong Ge, Yutian Chen, Moquan Wan, Zoubin Ghahramani %@Distributed Inference for Dirichlet Process Mixture Models %t2015 %cICML %f/ICML/ICML-2015-1944.pdf %*Wenlin Chen, James Wilson, Stephen Tyree, Kilian Weinberger, Yixin Chen %@Compressing Neural Networks with the Hashing Trick %t2015 %cICML %f/ICML/ICML-2015-1945.pdf %*Rong Ge, James Zou %@Intersecting Faces: Non-negative Matrix Factorization With New Guarantees %t2015 %cICML %f/ICML/ICML-2015-1946.pdf %*Rong Ge, James Zou %@Intersecting Faces: Non-negative Matrix Factorization With New Guarantees %t2015 %cICML %f/ICML/ICML-2015-1947.pdf %*Roger Grosse, Ruslan Salakhudinov %@Scaling up Natural Gradient by Sparsely Factorizing the Inverse Fisher Matrix %t2015 %cICML %f/ICML/ICML-2015-1948.pdf %*Harm Vanseijen, Rich Sutton %@A Deeper Look at Planning as Learning from Replay %t2015 %cICML %f/ICML/ICML-2015-1949.pdf %*Alina Beygelzimer, Satyen Kale, Haipeng Luo %@Optimal and Adaptive Algorithms for Online Boosting %t2015 %cICML %f/ICML/ICML-2015-1950.pdf %*Alina Beygelzimer, Satyen Kale, Haipeng Luo %@Optimal and Adaptive Algorithms for Online Boosting %t2015 %cICML %f/ICML/ICML-2015-1951.pdf %*Christopher De Sa, Christopher Re, Kunle Olukotun %@Global Convergence of Stochastic Gradient Descent for Some Non-convex Matrix Problems %t2015 %cICML %f/ICML/ICML-2015-1952.pdf %*Christopher De Sa, Christopher Re, Kunle Olukotun %@Global Convergence of Stochastic Gradient Descent for Some Non-convex Matrix Problems %t2015 %cICML %f/ICML/ICML-2015-1953.pdf %*Rafal Jozefowicz, Wojciech Zaremba, Ilya Sutskever %@An Empirical Exploration of Recurrent Network Architectures %t2015 %cICML %f/ICML/ICML-2015-1954.pdf %*Ju Sun, Qing Qu, John Wright %@Complete Dictionary Recovery Using Nonconvex Optimization %t2015 %cICML %f/ICML/ICML-2015-1955.pdf %*Haitham Bou Ammar, Rasul Tutunov, Eric Eaton %@Safe Policy Search for Lifelong Reinforcement Learning with Sublinear Regret %t2015 %cICML %f/ICML/ICML-2015-1956.pdf %*Haitham Bou Ammar, Rasul Tutunov, Eric Eaton %@Safe Policy Search for Lifelong Reinforcement Learning with Sublinear Regret %t2015 %cICML %f/ICML/ICML-2015-1957.pdf %*Cho-Jui Hsieh, Hsiang-Fu Yu, Inderjit Dhillon %@PASSCoDe: Parallel ASynchronous Stochastic dual Co-ordinate Descent %t2015 %cICML %f/ICML/ICML-2015-1958.pdf %*Cho-Jui Hsieh, Hsiang-Fu Yu, Inderjit Dhillon %@PASSCoDe: Parallel ASynchronous Stochastic dual Co-ordinate Descent %t2015 %cICML %f/ICML/ICML-2015-1959.pdf %*Philip Thomas, Georgios Theocharous, Mohammad Ghavamzadeh %@High Confidence Policy Improvement %t2015 %cICML %f/ICML/ICML-2015-1960.pdf %*Zelda Mariet, Suvrit Sra %@Fixed-point algorithms for learning determinantal point processes %t2015 %cICML %f/ICML/ICML-2015-1961.pdf %*Harikrishna Narasimhan, Harish Ramaswamy, Aadirupa Saha, Shivani Agarwal %@Consistent Multiclass Algorithms for Complex Performance Measures %t2015 %cICML %f/ICML/ICML-2015-1962.pdf %*Harikrishna Narasimhan, Harish Ramaswamy, Aadirupa Saha, Shivani Agarwal %@Consistent Multiclass Algorithms for Complex Performance Measures %t2015 %cICML %f/ICML/ICML-2015-1963.pdf %*James Martens, Roger Grosse %@Optimizing Neural Networks with Kronecker-factored Approximate Curvature %t2015 %cICML %f/ICML/ICML-2015-1964.pdf %*James Martens, Roger Grosse %@Optimizing Neural Networks with Kronecker-factored Approximate Curvature %t2015 %cICML %f/ICML/ICML-2015-1965.pdf %*En-Hsu Yen, Xin Lin, Kai Zhong, Pradeep Ravikumar, Inderjit Dhillon %@A Convex Exemplar-based Approach to MAD-Bayes Dirichlet Process Mixture Models %t2015 %cICML %f/ICML/ICML-2015-1966.pdf %*En-Hsu Yen, Xin Lin, Kai Zhong, Pradeep Ravikumar, Inderjit Dhillon %@A Convex Exemplar-based Approach to MAD-Bayes Dirichlet Process Mixture Models %t2015 %cICML %f/ICML/ICML-2015-1967.pdf %*Anh Pham, Raviv Raich, Xiaoli Fern, Jesús Pérez Arriaga %@Multi-instance multi-label learning in the presence of novel class instances %t2015 %cICML %f/ICML/ICML-2015-1968.pdf %*Anh Pham, Raviv Raich, Xiaoli Fern, Jesús Pérez Arriaga %@Multi-instance multi-label learning in the presence of novel class instances %t2015 %cICML %f/ICML/ICML-2015-1969.pdf %*Liva Ralaivola, Massih-Reza Amini %@Entropy-Based Concentration Inequalities for Dependent Variables %t2015 %cICML %f/ICML/ICML-2015-1970.pdf %*Cho-Jui Hsieh, Nagarajan Natarajan, Inderjit Dhillon %@PU Learning for Matrix Completion %t2015 %cICML %f/ICML/ICML-2015-1971.pdf %*Cho-Jui Hsieh, Nagarajan Natarajan, Inderjit Dhillon %@PU Learning for Matrix Completion %t2015 %cICML %f/ICML/ICML-2015-1972.pdf %*Necdet Aybat, Zi Wang, Garud Iyengar %@An Asynchronous Distributed Proximal Gradient Method for Composite Convex Optimization %t2015 %cICML %f/ICML/ICML-2015-1973.pdf %*Necdet Aybat, Zi Wang, Garud Iyengar %@An Asynchronous Distributed Proximal Gradient Method for Composite Convex Optimization %t2015 %cICML %f/ICML/ICML-2015-1974.pdf %*Congyuan Yang, Daniel Robinson, Rene Vidal %@Sparse Subspace Clustering with Missing Entries %t2015 %cICML %f/ICML/ICML-2015-1975.pdf %*Jinyan Guan, Kyle Simek, Ernesto Brau, Clayton Morrison, Emily Butler, Kobus Barnard %@Moderated and Drifting Linear Dynamical Systems %t2015 %cICML %f/ICML/ICML-2015-1976.pdf %*Taehoon Lee, Sungroh Yoon %@Boosted Categorical Restricted Boltzmann Machine for Computational Prediction of Splice Junctions %t2015 %cICML %f/ICML/ICML-2015-1977.pdf %*Yu-Xiang Wang, Stephen Fienberg, Alex Smola %@Privacy for Free: Posterior Sampling and Stochastic Gradient Monte Carlo %t2015 %cICML %f/ICML/ICML-2015-1978.pdf %*Yu-Xiang Wang, Stephen Fienberg, Alex Smola %@Privacy for Free: Posterior Sampling and Stochastic Gradient Monte Carlo %t2015 %cICML %f/ICML/ICML-2015-1979.pdf %*Lucas Theis, Matt Hoffman %@A trust-region method for stochastic variational inference with applications to streaming data %t2015 %cICML %f/ICML/ICML-2015-1980.pdf %*Lucas Theis, Matt Hoffman %@A trust-region method for stochastic variational inference with applications to streaming data %t2015 %cICML %f/ICML/ICML-2015-1981.pdf %*Kevin Winner, Garrett Bernstein, Dan Sheldon %@Inference in a Partially Observed Queuing Model with Applications in Ecology %t2015 %cICML %f/ICML/ICML-2015-1982.pdf %*Kevin Winner, Garrett Bernstein, Dan Sheldon %@Inference in a Partially Observed Queuing Model with Applications in Ecology %t2015 %cICML %f/ICML/ICML-2015-1983.pdf %*Ruitong Huang, Andras Gyorgy, Csaba Szepesvári %@Deterministic Independent Component Analysis %t2015 %cICML %f/ICML/ICML-2015-1984.pdf %*Maxime Gasse, Alexandre Aussem, Haytham Elghazel %@On the Optimality of Multi-Label Classification under Subset Zero-One Loss for Distributions Satisfying the Composition Property %t2015 %cICML %f/ICML/ICML-2015-1985.pdf %*Roy Frostig, Rong Ge, Sham Kakade, Aaron Sidford %@Un-regularizing: approximate proximal point and faster stochastic algorithms for empirical risk minimization %t2015 %cICML %f/ICML/ICML-2015-1986.pdf %*Roy Frostig, Rong Ge, Sham Kakade, Aaron Sidford %@Un-regularizing: approximate proximal point and faster stochastic algorithms for empirical risk minimization %t2015 %cICML %f/ICML/ICML-2015-1987.pdf %*Bin Gu, Charles Ling %@A New Generalized Error Path Algorithm for Model Selection %t2015 %cICML %f/ICML/ICML-2015-1988.pdf %*Maximum Margin Multi-Instance Learning %@Hua Wang,Heng Huang,Farhad Kamangar,Feiping Nie,Chris H. Ding %t2011 %cNIPS %f/NIPS/NIPS-2011-1989.pdf %*Nonlinear Inverse Reinforcement Learning with Gaussian Processes %@Sergey Levine,Zoran Popovic,Vladlen Koltun %t2011 %cNIPS %f/NIPS/NIPS-2011-1990.pdf %*Video Annotation and Tracking with Active Learning %@Carl Vondrick,Deva Ramanan %t2011 %cNIPS %f/NIPS/NIPS-2011-1991.pdf %*Penalty Decomposition Methods for Rank Minimization %@Yong Zhang,Zhaosong Lu %t2011 %cNIPS %f/NIPS/NIPS-2011-1992.pdf %*Sparse Manifold Clustering and Embedding %@Ehsan Elhamifar,René Vidal %t2011 %cNIPS %f/NIPS/NIPS-2011-1993.pdf %*Image Parsing with Stochastic Scene Grammar %@Yibiao Zhao,Song-chun Zhu %t2011 %cNIPS %f/NIPS/NIPS-2011-1994.pdf %*A Reinforcement Learning Theory for Homeostatic Regulation %@Mehdi Keramati,Boris S. Gutkin %t2011 %cNIPS %f/NIPS/NIPS-2011-1995.pdf %*Learning large-margin halfspaces with more malicious noise %@Phil Long,Rocco Servedio %t2011 %cNIPS %f/NIPS/NIPS-2011-1996.pdf %*On Strategy Stitching in Large Extensive Form Multiplayer Games %@Richard G. Gibson,Duane Szafron %t2011 %cNIPS %f/NIPS/NIPS-2011-1997.pdf %*Efficient Inference in Fully Connected CRFs with Gaussian Edge Potentials %@Philipp Krähenbühl,Vladlen Koltun %t2011 %cNIPS %f/NIPS/NIPS-2011-1998.pdf %*Transfer Learning by Borrowing Examples for Multiclass Object Detection %@Joseph J. Lim,Ruslan R. Salakhutdinov,Antonio Torralba %t2011 %cNIPS %f/NIPS/NIPS-2011-1999.pdf %*Environmental statistics and the trade-off between model-based and TD learning in humans %@Dylan A. Simon,Nathaniel D. Daw %t2011 %cNIPS %f/NIPS/NIPS-2011-2000.pdf %*Variational Learning for Recurrent Spiking Networks %@Danilo J. Rezende,Daan Wierstra,Wulfram Gerstner %t2011 %cNIPS %f/NIPS/NIPS-2011-2001.pdf %*Multiple Instance Learning on Structured Data %@Dan Zhang,Yan Liu,Luo Si,Jian Zhang,Richard D. Lawrence %t2011 %cNIPS %f/NIPS/NIPS-2011-2002.pdf %*Manifold Precis: An Annealing Technique for Diverse Sampling of Manifolds %@Nitesh Shroff,Pavan Turaga,Rama Chellappa %t2011 %cNIPS %f/NIPS/NIPS-2011-2003.pdf %*A Global Structural EM Algorithm for a Model of Cancer Progression %@Ali Tofigh,Erik Sj̦lund,Mattias H̦glund,Jens Lagergren %t2011 %cNIPS %f/NIPS/NIPS-2011-2004.pdf %*Generalized Lasso based Approximation of Sparse Coding for Visual Recognition %@Nobuyuki Morioka,Shin'ichi Satoh %t2011 %cNIPS %f/NIPS/NIPS-2011-2005.pdf %*Matrix Completion for Multi-label Image Classification %@Ricardo S. Cabral,Fernando Torre,Joao P. Costeira,Alexandre Bernardino %t2011 %cNIPS %f/NIPS/NIPS-2011-2006.pdf %*Multi-View Learning of Word Embeddings via CCA %@Paramveer Dhillon,Dean P. Foster,Lyle H. Ungar %t2011 %cNIPS %f/NIPS/NIPS-2011-2007.pdf %*Global Solution of Fully-Observed Variational Bayesian Matrix Factorization is Column-Wise Independent %@Shinichi Nakajima,Masashi Sugiyama,S. D. Babacan %t2011 %cNIPS %f/NIPS/NIPS-2011-2008.pdf %*Estimating time-varying input signals and ion channel states from a single voltage trace of a neuron %@Ryota Kobayashi,Yasuhiro Tsubo,Petr Lansky,Shigeru Shinomoto %t2011 %cNIPS %f/NIPS/NIPS-2011-2009.pdf %*Additive Gaussian Processes %@David K. Duvenaud,Hannes Nickisch,Carl E. Rasmussen %t2011 %cNIPS %f/NIPS/NIPS-2011-2010.pdf %*Inferring Interaction Networks using the IBP applied to microRNA Target Prediction %@Hai-son P. Le,Ziv Bar-joseph %t2011 %cNIPS %f/NIPS/NIPS-2011-2011.pdf %*Semantic Labeling of 3D Point Clouds for Indoor Scenes %@Hema S. Koppula,Abhishek Anand,Thorsten Joachims,Ashutosh Saxena %t2011 %cNIPS %f/NIPS/NIPS-2011-2012.pdf %*Learning Higher-Order Graph Structure with Features by Structure Penalty %@Shilin Ding,Grace Wahba,Xiaojin Zhu %t2011 %cNIPS %f/NIPS/NIPS-2011-2013.pdf %*Analysis and Improvement of Policy Gradient Estimation %@Tingting Zhao,Hirotaka Hachiya,Gang Niu,Masashi Sugiyama %t2011 %cNIPS %f/NIPS/NIPS-2011-2014.pdf %*Dimensionality Reduction Using the Sparse Linear Model %@Ioannis A. Gkioulekas,Todd Zickler %t2011 %cNIPS %f/NIPS/NIPS-2011-2015.pdf %*Robust Multi-Class Gaussian Process Classification %@Daniel Hernández-lobato,Jose M. Hernández-lobato,Pierre Dupont %t2011 %cNIPS %f/NIPS/NIPS-2011-2016.pdf %*Extracting Speaker-Specific Information with a Regularized Siamese Deep Network %@Ke Chen,Ahmad Salman %t2011 %cNIPS %f/NIPS/NIPS-2011-2017.pdf %*A Denoising View of Matrix Completion %@Weiran Wang,Miguel Á. Carreira-Perpiñán,Zhengdong Lu %t2011 %cNIPS %f/NIPS/NIPS-2011-2018.pdf %*Efficient Online Learning via Randomized Rounding %@Nicolò Cesa-bianchi,Ohad Shamir %t2011 %cNIPS %f/NIPS/NIPS-2011-2019.pdf %*Efficient Methods for Overlapping Group Lasso %@Lei Yuan,Jun Liu,Jieping Ye %t2011 %cNIPS %f/NIPS/NIPS-2011-2020.pdf %*Multiple Instance Filtering %@Kamil A. Wnuk,Stefano Soatto %t2011 %cNIPS %f/NIPS/NIPS-2011-2021.pdf %*Phase transition in the family of p-resistances %@Morteza Alamgir,Ulrike V. Luxburg %t2011 %cNIPS %f/NIPS/NIPS-2011-2022.pdf %*Convergent Bounds on the Euclidean Distance %@Yoonho Hwang,Hee-kap Ahn %t2011 %cNIPS %f/NIPS/NIPS-2011-2023.pdf %*Heavy-tailed Distances for Gradient Based Image Descriptors %@Yangqing Jia,Trevor Darrell %t2011 %cNIPS %f/NIPS/NIPS-2011-2024.pdf %*RTRMC: A Riemannian trust-region method for low-rank matrix completion %@Nicolas Boumal,Pierre-antoine Absil %t2011 %cNIPS %f/NIPS/NIPS-2011-2025.pdf %*Expressive Power and Approximation Errors of Restricted Boltzmann Machines %@Guido F. Montufar,Johannes Rauh,Nihat Ay %t2011 %cNIPS %f/NIPS/NIPS-2011-2026.pdf %*Semi-supervised Regression via Parallel Field Regularization %@Binbin Lin,Chiyuan Zhang,Xiaofei He %t2011 %cNIPS %f/NIPS/NIPS-2011-2027.pdf %*Object Detection with Grammar Models %@Ross B. Girshick,Pedro F. Felzenszwalb,David A. McAllester %t2011 %cNIPS %f/NIPS/NIPS-2011-2028.pdf %*Non-Asymptotic Analysis of Stochastic Approximation Algorithms for Machine Learning %@Eric Moulines,Francis R. Bach %t2011 %cNIPS %f/NIPS/NIPS-2011-2029.pdf %*On fast approximate submodular minimization %@Stefanie Jegelka,Hui Lin,Jeff A. Bilmes %t2011 %cNIPS %f/NIPS/NIPS-2011-2030.pdf %*Efficient anomaly detection using bipartite k-NN graphs %@Kumar Sricharan,Alfred O. Hero %t2011 %cNIPS %f/NIPS/NIPS-2011-2031.pdf %*Projection onto A Nonnegative Max-Heap %@Jun Liu,Liang Sun,Jieping Ye %t2011 %cNIPS %f/NIPS/NIPS-2011-2032.pdf %*Improving Topic Coherence with Regularized Topic Models %@David Newman,Edwin V. Bonilla,Wray Buntine %t2011 %cNIPS %f/NIPS/NIPS-2011-2033.pdf %*A Two-Stage Weighting Framework for Multi-Source Domain Adaptation %@Qian Sun,Rita Chattopadhyay,Sethuraman Panchanathan,Jieping Ye %t2011 %cNIPS %f/NIPS/NIPS-2011-2034.pdf %*An ideal observer model for identifying the reference frame of objects %@Joseph L. Austerweil,Abram L. Friesen,Thomas L. Griffiths %t2011 %cNIPS %f/NIPS/NIPS-2011-2035.pdf %*Generalized Beta Mixtures of Gaussians %@Artin Armagan,Merlise Clyde,David B. Dunson %t2011 %cNIPS %f/NIPS/NIPS-2011-2036.pdf %*Large-Scale Sparse Principal Component Analysis with Application to Text Data %@Youwei Zhang,Laurent E. Ghaoui %t2011 %cNIPS %f/NIPS/NIPS-2011-2037.pdf %*Simultaneous Sampling and Multi-Structure Fitting with Adaptive Reversible Jump MCMC %@Trung T. Pham,Tat-jun Chin,Jin Yu,David Suter %t2011 %cNIPS %f/NIPS/NIPS-2011-2038.pdf %*\theta-MRF: Capturing Spatial and Semantic Structure in the Parameters for Scene Understanding %@Congcong Li,Ashutosh Saxena,Tsuhan Chen %t2011 %cNIPS %f/NIPS/NIPS-2011-2039.pdf %*Crowdclustering %@Ryan G. Gomes,Peter Welinder,Andreas Krause,Pietro Perona %t2011 %cNIPS %f/NIPS/NIPS-2011-2040.pdf %*Fast and Balanced: Efficient Label Tree Learning for Large Scale Object Recognition %@Jia Deng,Sanjeev Satheesh,Alexander C. Berg,Fei Li %t2011 %cNIPS %f/NIPS/NIPS-2011-2041.pdf %*Target Neighbor Consistent Feature Weighting for Nearest Neighbor Classification %@Ichiro Takeuchi,Masashi Sugiyama %t2011 %cNIPS %f/NIPS/NIPS-2011-2042.pdf %*The Impact of Unlabeled Patterns in Rademacher Complexity Theory for Kernel Classifiers %@Luca Oneto,Davide Anguita,Alessandro Ghio,Sandro Ridella %t2011 %cNIPS %f/NIPS/NIPS-2011-2043.pdf %*Relative Density-Ratio Estimation for Robust Distribution Comparison %@Makoto Yamada,Taiji Suzuki,Takafumi Kanamori,Hirotaka Hachiya,Masashi Sugiyama %t2011 %cNIPS %f/NIPS/NIPS-2011-2044.pdf %*Solving Decision Problems with Limited Information %@Denis D. Maua,Cassio Campos %t2011 %cNIPS %f/NIPS/NIPS-2011-2045.pdf %*Linearized Alternating Direction Method with Adaptive Penalty for Low-Rank Representation %@Zhouchen Lin,Risheng Liu,Zhixun Su %t2011 %cNIPS %f/NIPS/NIPS-2011-2046.pdf %*Learning a Tree of Metrics with Disjoint Visual Features %@Kristen Grauman,Fei Sha,Sung Ju Hwang %t2011 %cNIPS %f/NIPS/NIPS-2011-2047.pdf %*Efficient inference in matrix-variate Gaussian models with \iid observation noise %@Oliver Stegle,Christoph Lippert,Joris M. Mooij,Neil D. Lawrence,Karsten M. Borgwardt %t2011 %cNIPS %f/NIPS/NIPS-2011-2048.pdf %*On Causal Discovery with Cyclic Additive Noise Models %@Joris M. Mooij,Dominik Janzing,Tom Heskes,Bernhard Schölkopf %t2011 %cNIPS %f/NIPS/NIPS-2011-2049.pdf %*Learning to Agglomerate Superpixel Hierarchies %@Viren Jain,Srinivas C. Turaga,K Briggman,Moritz N. Helmstaedter,Winfried Denk,H. S. Seung %t2011 %cNIPS %f/NIPS/NIPS-2011-2050.pdf %*A Convergence Analysis of Log-Linear Training %@Simon Wiesler,Hermann Ney %t2011 %cNIPS %f/NIPS/NIPS-2011-2051.pdf %*Shallow vs. Deep Sum-Product Networks %@Olivier Delalleau,Yoshua Bengio %t2011 %cNIPS %f/NIPS/NIPS-2011-2052.pdf %*Signal Estimation Under Random Time-Warpings and Nonlinear Signal Alignment %@Sebastian A. Kurtek,Anuj Srivastava,Wei Wu %t2011 %cNIPS %f/NIPS/NIPS-2011-2053.pdf %*From Bandits to Experts: On the Value of Side-Observations %@Shie Mannor,Ohad Shamir %t2011 %cNIPS %f/NIPS/NIPS-2011-2054.pdf %*Hogwild: A Lock-Free Approach to Parallelizing Stochastic Gradient Descent %@Benjamin Recht,Christopher Re,Stephen Wright,Feng Niu %t2011 %cNIPS %f/NIPS/NIPS-2011-2055.pdf %*Clustered Multi-Task Learning Via Alternating Structure Optimization %@Jiayu Zhou,Jianhui Chen,Jieping Ye %t2011 %cNIPS %f/NIPS/NIPS-2011-2056.pdf %*Why The Brain Separates Face Recognition From Object Recognition %@Joel Z. Leibo,Jim Mutch,Tomaso Poggio %t2011 %cNIPS %f/NIPS/NIPS-2011-2057.pdf %*Reinforcement Learning using Kernel-Based Stochastic Factorization %@Andre S. Barreto,Doina Precup,Joelle Pineau %t2011 %cNIPS %f/NIPS/NIPS-2011-2058.pdf %*Learning unbelievable probabilities %@Xaq Pitkow,Yashar Ahmadian,Ken D. Miller %t2011 %cNIPS %f/NIPS/NIPS-2011-2059.pdf %*A Machine Learning Approach to Predict Chemical Reactions %@Matthew A. Kayala,Pierre F. Baldi %t2011 %cNIPS %f/NIPS/NIPS-2011-2060.pdf %*Dynamical segmentation of single trials from population neural data %@Biljana Petreska,Byron M. Yu,John P. Cunningham,Gopal Santhanam,Stephen I. Ryu,Krishna V. Shenoy,Maneesh Sahani %t2011 %cNIPS %f/NIPS/NIPS-2011-2061.pdf %*Recovering Intrinsic Images with a Global Sparsity Prior on Reflectance %@Carsten Rother,Martin Kiefel,Lumin Zhang,Bernhard Schölkopf,Peter V. Gehler %t2011 %cNIPS %f/NIPS/NIPS-2011-2062.pdf %*Probabilistic Modeling of Dependencies Among Visual Short-Term Memory Representations %@Emin Orhan,Robert A. Jacobs %t2011 %cNIPS %f/NIPS/NIPS-2011-2063.pdf %*Reconstructing Patterns of Information Diffusion from Incomplete Observations %@Flavio Chierichetti,David Liben-nowell,Jon M. Kleinberg %t2011 %cNIPS %f/NIPS/NIPS-2011-2064.pdf %*Dynamic Pooling and Unfolding Recursive Autoencoders for Paraphrase Detection %@Richard Socher,Eric H. Huang,Jeffrey Pennin,Christopher D. Manning,Andrew Y. Ng %t2011 %cNIPS %f/NIPS/NIPS-2011-2065.pdf %*Modelling Genetic Variations using Fragmentation-Coagulation Processes %@Yee W. Teh,Charles Blundell,Lloyd Elliott %t2011 %cNIPS %f/NIPS/NIPS-2011-2066.pdf %*Prediction strategies without loss %@Michael Kapralov,Rina Panigrahy %t2011 %cNIPS %f/NIPS/NIPS-2011-2067.pdf %*Data Skeletonization via Reeb Graphs %@Xiaoyin Ge,Issam I. Safa,Mikhail Belkin,Yusu Wang %t2011 %cNIPS %f/NIPS/NIPS-2011-2068.pdf %*Information Rates and Optimal Decoding in Large Neural Populations %@Kamiar R. Rad,Liam Paninski %t2011 %cNIPS %f/NIPS/NIPS-2011-2069.pdf %*Selective Prediction of Financial Trends with Hidden Markov Models %@Dmitry Pidan,Ran El-Yaniv %t2011 %cNIPS %f/NIPS/NIPS-2011-2070.pdf %*Maximal Cliques that Satisfy Hard Constraints with Application to Deformable Object Model Learning %@Xinggang Wang,Xiang Bai,Xingwei Yang,Wenyu Liu,Longin J. Latecki %t2011 %cNIPS %f/NIPS/NIPS-2011-2071.pdf %*Distributed Delayed Stochastic Optimization %@Alekh Agarwal,John C. Duchi %t2011 %cNIPS %f/NIPS/NIPS-2011-2072.pdf %*Greedy Algorithms for Structurally Constrained High Dimensional Problems %@Ambuj Tewari,Pradeep K. Ravikumar,Inderjit S. Dhillon %t2011 %cNIPS %f/NIPS/NIPS-2011-2073.pdf %*Newtron: an Efficient Bandit algorithm for Online Multiclass Prediction %@Elad Hazan,Satyen Kale %t2011 %cNIPS %f/NIPS/NIPS-2011-2074.pdf %*Learning Sparse Representations of High Dimensional Data on Large Scale Dictionaries %@Zhen J. Xiang,Hao Xu,Peter J. Ramadge %t2011 %cNIPS %f/NIPS/NIPS-2011-2075.pdf %*Minimax Localization of Structural Information in Large Noisy Matrices %@Mladen Kolar,Sivaraman Balakrishnan,Alessandro Rinaldo,Aarti Singh %t2011 %cNIPS %f/NIPS/NIPS-2011-2076.pdf %*Maximum Covariance Unfolding : Manifold Learning for Bimodal Data %@Vijay Mahadevan,Chi W. Wong,Jose C. Pereira,Tom Liu,Nuno Vasconcelos,Lawrence K. Saul %t2011 %cNIPS %f/NIPS/NIPS-2011-2077.pdf %*Efficient Learning of Generalized Linear and Single Index Models with Isotonic Regression %@Sham M. Kakade,Varun Kanade,Ohad Shamir,Adam Kalai %t2011 %cNIPS %f/NIPS/NIPS-2011-2078.pdf %*On the Analysis of Multi-Channel Neural Spike Data %@Bo Chen,David E. Carlson,Lawrence Carin %t2011 %cNIPS %f/NIPS/NIPS-2011-2079.pdf %*Learning Eigenvectors for Free %@Wouter M. Koolen,Wojciech Kotlowski,Manfred K. Warmuth %t2011 %cNIPS %f/NIPS/NIPS-2011-2080.pdf %*Noise Thresholds for Spectral Clustering %@Sivaraman Balakrishnan,Min Xu,Akshay Krishnamurthy,Aarti Singh %t2011 %cNIPS %f/NIPS/NIPS-2011-2081.pdf %*The Kernel Beta Process %@Lu Ren,Yingjian Wang,Lawrence Carin,David B. Dunson %t2011 %cNIPS %f/NIPS/NIPS-2011-2082.pdf %*Statistical Performance of Convex Tensor Decomposition %@Ryota Tomioka,Taiji Suzuki,Kohei Hayashi,Hisashi Kashima %t2011 %cNIPS %f/NIPS/NIPS-2011-2083.pdf %*Probabilistic amplitude and frequency demodulation %@Richard Turner,Maneesh Sahani %t2011 %cNIPS %f/NIPS/NIPS-2011-2084.pdf %*Directed Graph Embedding: an Algorithm based on Continuous Limits of Laplacian-type Operators %@Dominique C. Perrault-joncas,Marina Meila %t2011 %cNIPS %f/NIPS/NIPS-2011-2085.pdf %*Efficient coding of natural images with a population of noisy Linear-Nonlinear neurons %@Yan Karklin,Eero P. Simoncelli %t2011 %cNIPS %f/NIPS/NIPS-2011-2086.pdf %*Complexity of Inference in Latent Dirichlet Allocation %@David Sontag,Dan Roy %t2011 %cNIPS %f/NIPS/NIPS-2011-2087.pdf %*ICA with Reconstruction Cost for Efficient Overcomplete Feature Learning %@Quoc V. Le,Alexandre Karpenko,Jiquan Ngiam,Andrew Y. Ng %t2011 %cNIPS %f/NIPS/NIPS-2011-2088.pdf %*Lower Bounds for Passive and Active Learning %@Maxim Raginsky,Alexander Rakhlin %t2011 %cNIPS %f/NIPS/NIPS-2011-2089.pdf %*Stochastic convex optimization with bandit feedback %@Alekh Agarwal,Dean P. Foster,Daniel J. Hsu,Sham M. Kakade,Alexander Rakhlin %t2011 %cNIPS %f/NIPS/NIPS-2011-2090.pdf %*Structure Learning for Optimization %@Shulin Yang,Ali Rahimi %t2011 %cNIPS %f/NIPS/NIPS-2011-2091.pdf %*Inverting Grice's Maxims to Learn Rules from Natural Language Extractions %@Mohammad S. Sorower,Janardhan R. Doppa,Walker Orr,Prasad Tadepalli,Thomas G. Dietterich,Xiaoli Z. Fern %t2011 %cNIPS %f/NIPS/NIPS-2011-2092.pdf %*Active Classification based on Value of Classifier %@Tianshi Gao,Daphne Koller %t2011 %cNIPS %f/NIPS/NIPS-2011-2093.pdf %*Group Anomaly Detection using Flexible Genre Models %@Liang Xiong,Barnabás Póczos,Jeff G. Schneider %t2011 %cNIPS %f/NIPS/NIPS-2011-2094.pdf %*Approximating Semidefinite Programs in Sublinear Time %@Dan Garber,Elad Hazan %t2011 %cNIPS %f/NIPS/NIPS-2011-2095.pdf %*SpaRCS: Recovering low-rank and sparse matrices from compressive measurements %@Andrew E. Waters,Aswin C. Sankaranarayanan,Richard Baraniuk %t2011 %cNIPS %f/NIPS/NIPS-2011-2096.pdf %*Budgeted Optimization with Concurrent Stochastic-Duration Experiments %@Javad Azimi,Alan Fern,Xiaoli Z. Fern %t2011 %cNIPS %f/NIPS/NIPS-2011-2097.pdf %*Online Submodular Set Cover, Ranking, and Repeated Active Learning %@Andrew Guillory,Jeff A. Bilmes %t2011 %cNIPS %f/NIPS/NIPS-2011-2098.pdf %*Structured sparse coding via lateral inhibition %@Arthur D. Szlam,Karol Gregor,Yann L. Cun %t2011 %cNIPS %f/NIPS/NIPS-2011-2099.pdf %*Sparse Filtering %@Jiquan Ngiam,Zhenghao Chen,Sonia A. Bhaskar,Pang W. Koh,Andrew Y. Ng %t2011 %cNIPS %f/NIPS/NIPS-2011-2100.pdf %*Divide-and-Conquer Matrix Factorization %@Lester W. Mackey,Michael I. Jordan,Ameet Talwalkar %t2011 %cNIPS %f/NIPS/NIPS-2011-2101.pdf %*Im2Text: Describing Images Using 1 Million Captioned Photographs %@Vicente Ordonez,Girish Kulkarni,Tamara L. Berg %t2011 %cNIPS %f/NIPS/NIPS-2011-2102.pdf %*Nonstandard Interpretations of Probabilistic Programs for Efficient Inference %@David Wingate,Noah Goodman,Andreas Stuhlmueller,Jeffrey M. Siskind %t2011 %cNIPS %f/NIPS/NIPS-2011-2103.pdf %*Collective Graphical Models %@Daniel R. Sheldon,Thomas G. Dietterich %t2011 %cNIPS %f/NIPS/NIPS-2011-2104.pdf %*Metric Learning with Multiple Kernels %@Jun Wang,Huyen T. Do,Adam Woznica,Alexandros Kalousis %t2011 %cNIPS %f/NIPS/NIPS-2011-2105.pdf %*ShareBoost: Efficient multiclass learning with feature sharing %@Shai Shalev-shwartz,Yonatan Wexler,Amnon Shashua %t2011 %cNIPS %f/NIPS/NIPS-2011-2106.pdf %*Active dendrites: adaptation to spike-based communication %@Balazs B. Ujfalussy,Máté Lengyel %t2011 %cNIPS %f/NIPS/NIPS-2011-2107.pdf %*Message-Passing for Approximate MAP Inference with Latent Variables %@Jiarong Jiang,Piyush Rai,Hal Daume %t2011 %cNIPS %f/NIPS/NIPS-2011-2108.pdf %*A More Powerful Two-Sample Test in High Dimensions using Random Projection %@Miles Lopes,Laurent Jacob,Martin J. Wainwright %t2011 %cNIPS %f/NIPS/NIPS-2011-2109.pdf %*Orthogonal Matching Pursuit with Replacement %@Prateek Jain,Ambuj Tewari,Inderjit S. Dhillon %t2011 %cNIPS %f/NIPS/NIPS-2011-2110.pdf %*Composite Multiclass Losses %@Elodie Vernet,Mark D. Reid,Robert C. Williamson %t2011 %cNIPS %f/NIPS/NIPS-2011-2111.pdf %*Beating SGD: Learning SVMs in Sublinear Time %@Elad Hazan,Tomer Koren,Nati Srebro %t2011 %cNIPS %f/NIPS/NIPS-2011-2112.pdf %*Greedy Model Averaging %@Dong Dai,Tong Zhang %t2011 %cNIPS %f/NIPS/NIPS-2011-2113.pdf %*Large-Scale Category Structure Aware Image Categorization %@Bin Zhao,Fei Li,Eric P. Xing %t2011 %cNIPS %f/NIPS/NIPS-2011-2114.pdf %*On the accuracy of l1-filtering of signals with block-sparse structure %@Fatma K. Karzan,Arkadi S. Nemirovski,Boris T. Polyak,Anatoli Juditsky %t2011 %cNIPS %f/NIPS/NIPS-2011-2115.pdf %*Multilinear Subspace Regression: An Orthogonal Tensor Decomposition Approach %@Qibin Zhao,Cesar F. Caiafa,Danilo P. Mandic,Liqing Zhang,Tonio Ball,Andreas Schulze-bonhage,Andrzej S. Cichocki %t2011 %cNIPS %f/NIPS/NIPS-2011-2116.pdf %*Finite Time Analysis of Stratified Sampling for Monte Carlo %@Alexandra Carpentier,Rémi Munos %t2011 %cNIPS %f/NIPS/NIPS-2011-2117.pdf %*Monte Carlo Value Iteration with Macro-Actions %@Zhan Lim,Lee Sun,David Hsu %t2011 %cNIPS %f/NIPS/NIPS-2011-2118.pdf %*Structured Learning for Cell Tracking %@Xinghua Lou,Fred A. Hamprecht %t2011 %cNIPS %f/NIPS/NIPS-2011-2119.pdf %*Two is better than one: distinct roles for familiarity and recollection in retrieving palimpsest memories %@Cristina Savin,Peter Dayan,Máté Lengyel %t2011 %cNIPS %f/NIPS/NIPS-2011-2120.pdf %*Algorithms and hardness results for parallel large margin learning %@Phil Long,Rocco Servedio %t2011 %cNIPS %f/NIPS/NIPS-2011-2121.pdf %*Portmanteau Vocabularies for Multi-Cue Image Representation %@Fahad S. Khan,Joost Weijer,Andrew D. Bagdanov,Maria Vanrell %t2011 %cNIPS %f/NIPS/NIPS-2011-2122.pdf %*Boosting with Maximum Adaptive Sampling %@Charles Dubout,Francois Fleuret %t2011 %cNIPS %f/NIPS/NIPS-2011-2123.pdf %*Gaussian Process Training with Input Noise %@Andrew Mchutchon,Carl E. Rasmussen %t2011 %cNIPS %f/NIPS/NIPS-2011-2124.pdf %*Empirical models of spiking in neural populations %@Jakob H. Macke,Lars Buesing,John P. Cunningham,Byron M. Yu,Krishna V. Shenoy,Maneesh Sahani %t2011 %cNIPS %f/NIPS/NIPS-2011-2125.pdf %*Learning Probabilistic Non-Linear Latent Variable Models for Tracking Complex Activities %@Angela Yao,Juergen Gall,Luc V. Gool,Raquel Urtasun %t2011 %cNIPS %f/NIPS/NIPS-2011-2126.pdf %*Bayesian Partitioning of Large-Scale Distance Data %@David Adametz,Volker Roth %t2011 %cNIPS %f/NIPS/NIPS-2011-2127.pdf %*From Stochastic Nonlinear Integrate-and-Fire to Generalized Linear Models %@Skander Mensi,Richard Naud,Wulfram Gerstner %t2011 %cNIPS %f/NIPS/NIPS-2011-2128.pdf %*Hierarchical Topic Modeling for Analysis of Time-Evolving Personal Choices %@Xianxing Zhang,Lawrence Carin,David B. Dunson %t2011 %cNIPS %f/NIPS/NIPS-2011-2129.pdf %*An Exact Algorithm for F-Measure Maximization %@Krzysztof J. Dembczynski,Willem Waegeman,Weiwei Cheng,Eyke Hüllermeier %t2011 %cNIPS %f/NIPS/NIPS-2011-2130.pdf %*Co-regularized Multi-view Spectral Clustering %@Abhishek Kumar,Piyush Rai,Hal Daume %t2011 %cNIPS %f/NIPS/NIPS-2011-2131.pdf %*Sequence learning with hidden units in spiking neural networks %@Johanni Brea,Walter Senn,Jean-pascal Pfister %t2011 %cNIPS %f/NIPS/NIPS-2011-2132.pdf %*Identifying Alzheimer's Disease-Related Brain Regions from Multi-Modality Neuroimaging Data using Sparse Composite Linear Discrimination Analysis %@Shuai Huang,Jing Li,Jieping Ye,Teresa Wu,Kewei Chen,Adam Fleisher,Eric Reiman %t2011 %cNIPS %f/NIPS/NIPS-2011-2133.pdf %*A blind sparse deconvolution method for neural spike identification %@Chaitanya Ekanadham,Daniel Tranchina,Eero P. Simoncelli %t2011 %cNIPS %f/NIPS/NIPS-2011-2134.pdf %*How Do Humans Teach: On Curriculum Learning and Teaching Dimension %@Faisal Khan,Bilge Mutlu,Xiaojin Zhu %t2011 %cNIPS %f/NIPS/NIPS-2011-2135.pdf %*Convergence Rates of Inexact Proximal-Gradient Methods for Convex Optimization %@Mark Schmidt,Nicolas L. Roux,Francis R. Bach %t2011 %cNIPS %f/NIPS/NIPS-2011-2136.pdf %*Joint 3D Estimation of Objects and Scene Layout %@Andreas Geiger,Christian Wojek,Raquel Urtasun %t2011 %cNIPS %f/NIPS/NIPS-2011-2137.pdf %*Spatial distance dependent Chinese restaurant processes for image segmentation %@Soumya Ghosh,Andrei B. Ungureanu,Erik B. Sudderth,David M. Blei %t2011 %cNIPS %f/NIPS/NIPS-2011-2138.pdf %*Pylon Model for Semantic Segmentation %@Victor Lempitsky,Andrea Vedaldi,Andrew Zisserman %t2011 %cNIPS %f/NIPS/NIPS-2011-2139.pdf %*t-divergence Based Approximate Inference %@Nan Ding,Yuan Qi,S.v.n. Vishwanathan %t2011 %cNIPS %f/NIPS/NIPS-2011-2140.pdf %*Learning person-object interactions for action recognition in still images %@Vincent Delaitre,Josef Sivic,Ivan Laptev %t2011 %cNIPS %f/NIPS/NIPS-2011-2141.pdf %*Submodular Multi-Label Learning %@James Petterson,Tibério S. Caetano %t2011 %cNIPS %f/NIPS/NIPS-2011-2142.pdf %*Higher-Order Correlation Clustering for Image Segmentation %@Sungwoong Kim,Sebastian Nowozin,Pushmeet Kohli,Chang D. Yoo %t2011 %cNIPS %f/NIPS/NIPS-2011-2143.pdf %*Optimal learning rates for least squares SVMs using Gaussian kernels %@Mona Eberts,Ingo Steinwart %t2011 %cNIPS %f/NIPS/NIPS-2011-2144.pdf %*Learning Auto-regressive Models from Sequence and Non-sequence Data %@Tzu-kuo Huang,Jeff G. Schneider %t2011 %cNIPS %f/NIPS/NIPS-2011-2145.pdf %*Committing Bandits %@Loc X. Bui,Ramesh Johari,Shie Mannor %t2011 %cNIPS %f/NIPS/NIPS-2011-2146.pdf %*Energetically Optimal Action Potentials %@Martin B. Stemmler,Biswa Sengupta,Simon Laughlin,Jeremy Niven %t2011 %cNIPS %f/NIPS/NIPS-2011-2147.pdf %*See the Tree Through the Lines: The Shazoo Algorithm %@Fabio Vitale,Nicolò Cesa-bianchi,Claudio Gentile,Giovanni Zappella %t2011 %cNIPS %f/NIPS/NIPS-2011-2148.pdf %*Learning Anchor Planes for Classification %@Ziming Zhang,Lubor Ladicky,Philip Torr,Amir Saffari %t2011 %cNIPS %f/NIPS/NIPS-2011-2149.pdf %*Infinite Latent SVM for Classification and Multi-task Learning %@Jun Zhu,Ning Chen,Eric P. Xing %t2011 %cNIPS %f/NIPS/NIPS-2011-2150.pdf %*Facial Expression Transfer with Input-Output Temporal Restricted Boltzmann Machines %@Matthew D. Zeiler,Graham W. Taylor,Leonid Sigal,Iain Matthews,Rob Fergus %t2011 %cNIPS %f/NIPS/NIPS-2011-2151.pdf %*Better Mini-Batch Algorithms via Accelerated Gradient Methods %@Andrew Cotter,Ohad Shamir,Nati Srebro,Karthik Sridharan %t2011 %cNIPS %f/NIPS/NIPS-2011-2152.pdf %*Adaptive Hedge %@Tim V. Erven,Wouter M. Koolen,Steven D. Rooij,Peter Grünwald %t2011 %cNIPS %f/NIPS/NIPS-2011-2153.pdf %*Agnostic Selective Classification %@Yair Wiener,Ran El-Yaniv %t2011 %cNIPS %f/NIPS/NIPS-2011-2154.pdf %*Comparative Analysis of Viterbi Training and Maximum Likelihood Estimation for HMMs %@Armen Allahverdyan,Aram Galstyan %t2011 %cNIPS %f/NIPS/NIPS-2011-2155.pdf %*PAC-Bayesian Analysis of Contextual Bandits %@Yevgeny Seldin,Peter Auer,John S. Shawe-taylor,Ronald Ortner,François Laviolette %t2011 %cNIPS %f/NIPS/NIPS-2011-2156.pdf %*Bayesian Spike-Triggered Covariance Analysis %@Il Memming Park,Jonathan W. Pillow %t2011 %cNIPS %f/NIPS/NIPS-2011-2157.pdf %*Non-conjugate Variational Message Passing for Multinomial and Binary Regression %@David A. Knowles,Tom Minka %t2011 %cNIPS %f/NIPS/NIPS-2011-2158.pdf %*Learning to Search Efficiently in High Dimensions %@Zhen Li,Huazhong Ning,Liangliang Cao,Tong Zhang,Yihong Gong,Thomas S. Huang %t2011 %cNIPS %f/NIPS/NIPS-2011-2159.pdf %*A Non-Parametric Approach to Dynamic Programming %@Oliver B. Kroemer,Jan R. Peters %t2011 %cNIPS %f/NIPS/NIPS-2011-2160.pdf %*Advice Refinement in Knowledge-Based SVMs %@Gautam Kunapuli,Richard Maclin,Jude W. Shavlik %t2011 %cNIPS %f/NIPS/NIPS-2011-2161.pdf %*Kernel Bayes' Rule %@Kenji Fukumizu,Le Song,Arthur Gretton %t2011 %cNIPS %f/NIPS/NIPS-2011-2162.pdf %*Transfer from Multiple MDPs %@Alessandro Lazaric,Marcello Restelli %t2011 %cNIPS %f/NIPS/NIPS-2011-2163.pdf %*Sparse Bayesian Multi-Task Learning %@Shengbo Guo,Onno Zoeter,Cédric Archambeau %t2011 %cNIPS %f/NIPS/NIPS-2011-2164.pdf %*Online Learning: Stochastic, Constrained, and Smoothed Adversaries %@Alexander Rakhlin,Karthik Sridharan,Ambuj Tewari %t2011 %cNIPS %f/NIPS/NIPS-2011-2165.pdf %*Learning in Hilbert vs. Banach Spaces: A Measure Embedding Viewpoint %@Kenji Fukumizu,Gert R. Lanckriet,Bharath K. Sriperumbudur %t2011 %cNIPS %f/NIPS/NIPS-2011-2166.pdf %*Sparse Recovery with Brownian Sensing %@Alexandra Carpentier,Odalric-ambrym Maillard,Rémi Munos %t2011 %cNIPS %f/NIPS/NIPS-2011-2167.pdf %*An Unsupervised Decontamination Procedure For Improving The Reliability Of Human Judgments %@Michael C. Mozer,Benjamin Link,Harold Pashler %t2011 %cNIPS %f/NIPS/NIPS-2011-2168.pdf %*Bayesian Bias Mitigation for Crowdsourcing %@Fabian L. Wauthier,Michael I. Jordan %t2011 %cNIPS %f/NIPS/NIPS-2011-2169.pdf %*Ranking annotators for crowdsourced labeling tasks %@Vikas C. Raykar,Shipeng Yu %t2011 %cNIPS %f/NIPS/NIPS-2011-2170.pdf %*Clustering via Dirichlet Process Mixture Models for Portable Skill Discovery %@Scott Niekum,Andrew G. Barto %t2011 %cNIPS %f/NIPS/NIPS-2011-2171.pdf %*Probabilistic Joint Image Segmentation and Labeling %@Adrian Ion,Joao Carreira,Cristian Sminchisescu %t2011 %cNIPS %f/NIPS/NIPS-2011-2172.pdf %*Variance Reduction in Monte-Carlo Tree Search %@Joel Veness,Marc Lanctot,Michael Bowling %t2011 %cNIPS %f/NIPS/NIPS-2011-2173.pdf %*Learning Patient-Specific Cancer Survival Distributions as a Sequence of Dependent Regressors %@Chun-Nam Yu,Russell Greiner,Hsiu-Chin Lin,Vickie Baracos %t2011 %cNIPS %f/NIPS/NIPS-2011-2174.pdf %*An Application of Tree-Structured Expectation Propagation for Channel Decoding %@Pablo M. Olmos,Luis Salamanca,Juan Fuentes,Fernando Pérez-Cruz %t2011 %cNIPS %f/NIPS/NIPS-2011-2175.pdf %*High-Dimensional Graphical Model Selection: Tractable Graph Families and Necessary Conditions %@Animashree Anandkumar,Vincent Tan,Alan S. Willsky %t2011 %cNIPS %f/NIPS/NIPS-2011-2176.pdf %*Structural equations and divisive normalization for energy-dependent component analysis %@Jun-ichiro Hirayama,Aapo Hyvärinen %t2011 %cNIPS %f/NIPS/NIPS-2011-2177.pdf %*Robust Lasso with missing and grossly corrupted observations %@Nasser M. Nasrabadi,Trac D. Tran,Nam Nguyen %t2011 %cNIPS %f/NIPS/NIPS-2011-2178.pdf %*A concave regularization technique for sparse mixture models %@Martin O. Larsson,Johan Ugander %t2011 %cNIPS %f/NIPS/NIPS-2011-2179.pdf %*Learning a Distance Metric from a Network %@Blake Shaw,Bert Huang,Tony Jebara %t2011 %cNIPS %f/NIPS/NIPS-2011-2180.pdf %*Variance Penalizing AdaBoost %@Pannagadatta K. Shivaswamy,Tony Jebara %t2011 %cNIPS %f/NIPS/NIPS-2011-2181.pdf %*Efficient Offline Communication Policies for Factored Multiagent POMDPs %@João V. Messias,Matthijs Spaan,Pedro U. Lima %t2011 %cNIPS %f/NIPS/NIPS-2011-2182.pdf %*Sparse recovery by thresholded non-negative least squares %@Martin Slawski,Matthias Hein %t2011 %cNIPS %f/NIPS/NIPS-2011-2183.pdf %*On Learning Discrete Graphical Models using Greedy Methods %@Ali Jalali,Christopher C. Johnson,Pradeep K. Ravikumar %t2011 %cNIPS %f/NIPS/NIPS-2011-2184.pdf %*Iterative Learning for Reliable Crowdsourcing Systems %@David R. Karger,Sewoong Oh,Devavrat Shah %t2011 %cNIPS %f/NIPS/NIPS-2011-2185.pdf %*A Model for Temporal Dependencies in Event Streams %@Asela Gunawardana,Christopher Meek,Puyang Xu %t2011 %cNIPS %f/NIPS/NIPS-2011-2186.pdf %*Unsupervised learning models of primary cortical receptive fields and receptive field plasticity %@Maneesh Bhand,Ritvik Mudur,Bipin Suresh,Andrew Saxe,Andrew Y. Ng %t2011 %cNIPS %f/NIPS/NIPS-2011-2187.pdf %*The Doubly Correlated Nonparametric Topic Model %@Dae I. Kim,Erik B. Sudderth %t2011 %cNIPS %f/NIPS/NIPS-2011-2188.pdf %*MAP Inference for Bayesian Inverse Reinforcement Learning %@Jaedeug Choi,Kee-eung Kim %t2011 %cNIPS %f/NIPS/NIPS-2011-2189.pdf %*Similarity-based Learning via Data Driven Embeddings %@Purushottam Kar,Prateek Jain %t2011 %cNIPS %f/NIPS/NIPS-2011-2190.pdf %*Predicting Dynamic Difficulty %@Olana Missura,Thomas Gärtner %t2011 %cNIPS %f/NIPS/NIPS-2011-2191.pdf %*Spectral Methods for Learning Multivariate Latent Tree Structure %@Animashree Anandkumar,Kamalika Chaudhuri,Daniel J. Hsu,Sham M. Kakade,Le Song,Tong Zhang %t2011 %cNIPS %f/NIPS/NIPS-2011-2192.pdf %*How biased are maximum entropy models? %@Jakob H. Macke,Iain Murray,Peter E. Latham %t2011 %cNIPS %f/NIPS/NIPS-2011-2193.pdf %*Active learning of neural response functions with Gaussian processes %@Mijung Park,Greg Horwitz,Jonathan W. Pillow %t2011 %cNIPS %f/NIPS/NIPS-2011-2194.pdf %*Priors over Recurrent Continuous Time Processes %@Ardavan Saeedi,Alexandre Bouchard-côté %t2011 %cNIPS %f/NIPS/NIPS-2011-2195.pdf %*Learning to Learn with Compound HD Models %@Antonio Torralba,Joshua B. Tenenbaum,Ruslan R. Salakhutdinov %t2011 %cNIPS %f/NIPS/NIPS-2011-2196.pdf %*Anatomically Constrained Decoding of Finger Flexion from Electrocorticographic Signals %@Zuoguan Wang,Gerwin Schalk,Qiang Ji %t2011 %cNIPS %f/NIPS/NIPS-2011-2197.pdf %*PiCoDes: Learning a Compact Code for Novel-Category Recognition %@Alessandro Bergamo,Lorenzo Torresani,Andrew W. Fitzgibbon %t2011 %cNIPS %f/NIPS/NIPS-2011-2198.pdf %*Confidence Sets for Network Structure %@David S. Choi,Patrick J. Wolfe,Edo M. Airoldi %t2011 %cNIPS %f/NIPS/NIPS-2011-2199.pdf %*Prismatic Algorithm for Discrete D.C. Programming Problem %@Yoshinobu Kawahara,Takashi Washio %t2011 %cNIPS %f/NIPS/NIPS-2011-2200.pdf %*Hierarchical Matching Pursuit for Image Classification: Architecture and Fast Algorithms %@Liefeng Bo,Xiaofeng Ren,Dieter Fox %t2011 %cNIPS %f/NIPS/NIPS-2011-2201.pdf %*Multiclass Boosting: Theory and Algorithms %@Mohammad J. Saberian,Nuno Vasconcelos %t2011 %cNIPS %f/NIPS/NIPS-2011-2202.pdf %*Learning with the weighted trace-norm under arbitrary sampling distributions %@Rina Foygel,Ohad Shamir,Nati Srebro,Ruslan R. Salakhutdinov %t2011 %cNIPS %f/NIPS/NIPS-2011-2203.pdf %*Scalable Training of Mixture Models via Coresets %@Dan Feldman,Matthew Faulkner,Andreas Krause %t2011 %cNIPS %f/NIPS/NIPS-2011-2204.pdf %*Generalised Coupled Tensor Factorisation %@Kenan Y. Yılmaz,Ali T. Cemgil,Umut Simsekli %t2011 %cNIPS %f/NIPS/NIPS-2011-2205.pdf %*Nearest Neighbor based Greedy Coordinate Descent %@Inderjit S. Dhillon,Pradeep K. Ravikumar,Ambuj Tewari %t2011 %cNIPS %f/NIPS/NIPS-2011-2206.pdf %*Generalizing from Several Related Classification Tasks to a New Unlabeled Sample %@Gilles Blanchard,Gyemin Lee,Clayton Scott %t2011 %cNIPS %f/NIPS/NIPS-2011-2207.pdf %*Trace Lasso: a trace norm regularization for correlated designs %@Edouard Grave,Guillaume R. Obozinski,Francis R. Bach %t2011 %cNIPS %f/NIPS/NIPS-2011-2208.pdf %*Statistical Tests for Optimization Efficiency %@Levi Boyles,Anoop Korattikara,Deva Ramanan,Max Welling %t2011 %cNIPS %f/NIPS/NIPS-2011-2209.pdf %*Generalization Bounds and Consistency for Latent Structural Probit and Ramp Loss %@Joseph Keshet,David A. McAllester %t2011 %cNIPS %f/NIPS/NIPS-2011-2210.pdf %*A Brain-Machine Interface Operating with a Real-Time Spiking Neural Network Control Algorithm %@Julie Dethier,Paul Nuyujukian,Chris Eliasmith,Terrence C. Stewart,Shauki A. Elasaad,Krishna V. Shenoy,Kwabena A. Boahen %t2011 %cNIPS %f/NIPS/NIPS-2011-2211.pdf %*Multi-Bandit Best Arm Identification %@Victor Gabillon,Mohammad Ghavamzadeh,Alessandro Lazaric,Sébastien Bubeck %t2011 %cNIPS %f/NIPS/NIPS-2011-2212.pdf %*Randomized Algorithms for Comparison-based Search %@Dominique Tschopp,Suhas Diggavi,Payam Delgosha,Soheil Mohajer %t2011 %cNIPS %f/NIPS/NIPS-2011-2213.pdf %*Active Ranking using Pairwise Comparisons %@Kevin G. Jamieson,Robert Nowak %t2011 %cNIPS %f/NIPS/NIPS-2011-2214.pdf %*An Empirical Evaluation of Thompson Sampling %@Olivier Chapelle,Lihong Li %t2011 %cNIPS %f/NIPS/NIPS-2011-2215.pdf %*Blending Autonomous Exploration and Apprenticeship Learning %@Thomas J. Walsh,Daniel K. Hewlett,Clayton T. Morrison %t2011 %cNIPS %f/NIPS/NIPS-2011-2216.pdf %*Nonnegative dictionary learning in the exponential noise model for adaptive music signal representation %@Onur Dikmen,Cédric Févotte %t2011 %cNIPS %f/NIPS/NIPS-2011-2217.pdf %*Evaluating the inverse decision-making approach to preference learning %@Alan Jern,Christopher G. Lucas,Charles Kemp %t2011 %cNIPS %f/NIPS/NIPS-2011-2218.pdf %*Sparse Features for PCA-Like Linear Regression %@Christos Boutsidis,Petros Drineas,Malik Magdon-Ismail %t2011 %cNIPS %f/NIPS/NIPS-2011-2219.pdf %*The Manifold Tangent Classifier %@Salah Rifai,Yann N. Dauphin,Pascal Vincent,Yoshua Bengio,Xavier Muller %t2011 %cNIPS %f/NIPS/NIPS-2011-2220.pdf %*Analytical Results for the Error in Filtering of Gaussian Processes %@Alex K. Susemihl,Ron Meir,Manfred Opper %t2011 %cNIPS %f/NIPS/NIPS-2011-2221.pdf %*Improved Algorithms for Linear Stochastic Bandits %@Yasin Abbasi-yadkori,Dávid Pál,Csaba Szepesvári %t2011 %cNIPS %f/NIPS/NIPS-2011-2222.pdf %*Testing a Bayesian Measure of Representativeness Using a Large Image Database %@Joshua T. Abbott,Katherine A. Heller,Zoubin Ghahramani,Thomas L. Griffiths %t2011 %cNIPS %f/NIPS/NIPS-2011-2223.pdf %*Sparse Inverse Covariance Matrix Estimation Using Quadratic Approximation %@Cho-jui Hsieh,Inderjit S. Dhillon,Pradeep K. Ravikumar,Mátyás A. Sustik %t2011 %cNIPS %f/NIPS/NIPS-2011-2224.pdf %*Spike and Slab Variational Inference for Multi-Task and Multiple Kernel Learning %@Michalis K. Titsias,Miguel Lázaro-Gredilla %t2011 %cNIPS %f/NIPS/NIPS-2011-2225.pdf %*Neuronal Adaptation for Sampling-Based Probabilistic Inference in Perceptual Bistability %@David P. Reichert,Peggy Series,Amos J. Storkey %t2011 %cNIPS %f/NIPS/NIPS-2011-2226.pdf %*Beyond Spectral Clustering - Tight Relaxations of Balanced Graph Cuts %@Matthias Hein,Simon Setzer %t2011 %cNIPS %f/NIPS/NIPS-2011-2227.pdf %*Fast and Accurate k-means For Large Datasets %@Michael Shindler,Alex Wong,Adam W. Meyerson %t2011 %cNIPS %f/NIPS/NIPS-2011-2228.pdf %*A rational model of causal inference with continuous causes %@Thomas L. Griffiths,Michael James %t2011 %cNIPS %f/NIPS/NIPS-2011-2229.pdf %*Quasi-Newton Methods for Markov Chain Monte Carlo %@Yichuan Zhang,Charles A. Sutton %t2011 %cNIPS %f/NIPS/NIPS-2011-2230.pdf %*TD_gamma: Re-evaluating Complex Backups in Temporal Difference Learning %@George Konidaris,Scott Niekum,Philip S. Thomas %t2011 %cNIPS %f/NIPS/NIPS-2011-2231.pdf %*Speedy Q-Learning %@Mohammad Ghavamzadeh,Hilbert J. Kappen,Mohammad G. Azar,Rémi Munos %t2011 %cNIPS %f/NIPS/NIPS-2011-2232.pdf %*Regularized Laplacian Estimation and Fast Eigenvector Approximation %@Patrick O. Perry,Michael W. Mahoney %t2011 %cNIPS %f/NIPS/NIPS-2011-2233.pdf %*Understanding the Intrinsic Memorability of Images %@Phillip Isola,Devi Parikh,Antonio Torralba,Aude Oliva %t2011 %cNIPS %f/NIPS/NIPS-2011-2234.pdf %*The Local Rademacher Complexity of Lp-Norm Multiple Kernel Learning %@Marius Kloft,Gilles Blanchard %t2011 %cNIPS %f/NIPS/NIPS-2011-2235.pdf %*Contextual Gaussian Process Bandit Optimization %@Andreas Krause,Cheng S. Ong %t2011 %cNIPS %f/NIPS/NIPS-2011-2236.pdf %*Co-Training for Domain Adaptation %@Minmin Chen,Kilian Q. Weinberger,John Blitzer %t2011 %cNIPS %f/NIPS/NIPS-2011-2237.pdf %*Autonomous Learning of Action Models for Planning %@Neville Mehta,Prasad Tadepalli,Alan Fern %t2011 %cNIPS %f/NIPS/NIPS-2011-2238.pdf %*Gaussian process modulated renewal processes %@Yee W. Teh,Vinayak Rao %t2011 %cNIPS %f/NIPS/NIPS-2011-2239.pdf %*Linear Submodular Bandits and their Application to Diversified Retrieval %@Yisong Yue,Carlos Guestrin %t2011 %cNIPS %f/NIPS/NIPS-2011-2240.pdf %*Continuous-Time Regression Models for Longitudinal Networks %@Duy Q. Vu,David Hunter,Padhraic Smyth,Arthur U. Asuncion %t2011 %cNIPS %f/NIPS/NIPS-2011-2241.pdf %*On Tracking The Partition Function %@Guillaume Desjardins,Yoshua Bengio,Aaron C. Courville %t2011 %cNIPS %f/NIPS/NIPS-2011-2242.pdf %*Variational Gaussian Process Dynamical Systems %@Andreas Damianou,Michalis K. Titsias,Neil D. Lawrence %t2011 %cNIPS %f/NIPS/NIPS-2011-2243.pdf %*Non-parametric Group Orthogonal Matching Pursuit for Sparse Learning with Multiple Kernels %@Vikas Sindhwani,Aurelie C. Lozano %t2011 %cNIPS %f/NIPS/NIPS-2011-2244.pdf %*Selecting Receptive Fields in Deep Networks %@Adam Coates,Andrew Y. Ng %t2011 %cNIPS %f/NIPS/NIPS-2011-2245.pdf %*Algorithms for Hyper-Parameter Optimization %@James S. Bergstra,Rémi Bardenet,Yoshua Bengio,Balázs Kégl %t2011 %cNIPS %f/NIPS/NIPS-2011-2246.pdf %*Neural Reconstruction with Approximate Message Passing (NeuRAMP) %@Alyson K. Fletcher,Sundeep Rangan,Lav R. Varshney,Aniruddha Bhargava %t2011 %cNIPS %f/NIPS/NIPS-2011-2247.pdf %*Query-Aware MCMC %@Michael L. Wick,Andrew McCallum %t2011 %cNIPS %f/NIPS/NIPS-2011-2248.pdf %*Inferring spike-timing-dependent plasticity from spike train data %@Ian Stevenson,Konrad Koerding %t2011 %cNIPS %f/NIPS/NIPS-2011-2249.pdf %*Automated Refinement of Bayes Networks' Parameters based on Test Ordering Constraints %@Omar Z. Khan,Pascal Poupart,John-mark M. Agosta %t2011 %cNIPS %f/NIPS/NIPS-2011-2250.pdf %*A Collaborative Mechanism for Crowdsourcing Prediction Problems %@Jacob D. Abernethy,Rafael M. Frongillo %t2011 %cNIPS %f/NIPS/NIPS-2011-2251.pdf %*Hierarchically Supervised Latent Dirichlet Allocation %@Adler J. Perotte,Frank Wood,Noemie Elhadad,Nicholas Bartlett %t2011 %cNIPS %f/NIPS/NIPS-2011-2252.pdf %*Select and Sample - A Model of Efficient Neural Inference and Learning %@Jacquelyn A. Shelton,Abdul S. Sheikh,Pietro Berkes,Joerg Bornschein,Joerg Luecke %t2011 %cNIPS %f/NIPS/NIPS-2011-2253.pdf %*Selecting the State-Representation in Reinforcement Learning %@Odalric-ambrym Maillard,Daniil Ryabko,Rémi Munos %t2011 %cNIPS %f/NIPS/NIPS-2011-2254.pdf %*Periodic Finite State Controllers for Efficient POMDP and DEC-POMDP Planning %@Joni K. Pajarinen,Jaakko Peltonen %t2011 %cNIPS %f/NIPS/NIPS-2011-2255.pdf %*On the Universality of Online Mirror Descent %@Nati Srebro,Karthik Sridharan,Ambuj Tewari %t2011 %cNIPS %f/NIPS/NIPS-2011-2256.pdf %*Demixed Principal Component Analysis %@Wieland Brendel,Ranulfo Romo,Christian K. Machens %t2011 %cNIPS %f/NIPS/NIPS-2011-2257.pdf %*EigenNet: A Bayesian hybrid of generative and conditional models for sparse learning %@Feng Yan,Yuan Qi %t2011 %cNIPS %f/NIPS/NIPS-2011-2258.pdf %*Hashing Algorithms for Large-Scale Learning %@Ping Li,Anshumali Shrivastava,Joshua L. Moore,Arnd C. König %t2011 %cNIPS %f/NIPS/NIPS-2011-2259.pdf %*Hierarchical Multitask Structured Output Learning for Large-scale Sequence Segmentation %@Nico Goernitz,Christian Widmer,Georg Zeller,Andre Kahles,Gunnar Rätsch,Sören Sonnenburg %t2011 %cNIPS %f/NIPS/NIPS-2011-2260.pdf %*Predicting response time and error rates in visual search %@Bo Chen,Vidhya Navalpakkam,Pietro Perona %t2011 %cNIPS %f/NIPS/NIPS-2011-2261.pdf %*Kernel Embeddings of Latent Tree Graphical Models %@Le Song,Eric P. Xing,Ankur P. Parikh %t2011 %cNIPS %f/NIPS/NIPS-2011-2262.pdf %*Inference in continuous-time change-point models %@Florian Stimberg,Manfred Opper,Guido Sanguinetti,Andreas Ruttor %t2011 %cNIPS %f/NIPS/NIPS-2011-2263.pdf %*High-dimensional regression with noisy and missing data: Provable guarantees with non-convexity %@Po-ling Loh,Martin J. Wainwright %t2011 %cNIPS %f/NIPS/NIPS-2011-2264.pdf %*Exploiting spatial overlap to efficiently compute appearance distances between image windows %@Bogdan Alexe,Viviana Petrescu,Vittorio Ferrari %t2011 %cNIPS %f/NIPS/NIPS-2011-2265.pdf %*Accelerated Adaptive Markov Chain for Partition Function Computation %@Stefano Ermon,Carla P. Gomes,Ashish Sabharwal,Bart Selman %t2011 %cNIPS %f/NIPS/NIPS-2011-2266.pdf %*Locally Uniform Comparison Image Descriptor %@Andrew Ziegler,Eric Christiansen,David Kriegman,Serge J. Belongie %t2012 %cNIPS %f/NIPS/NIPS-2012-2267.pdf %*Learning from Distributions via Support Measure Machines %@Krikamol Muandet,Kenji Fukumizu,Francesco Dinuzzo,Bernhard Schölkopf %t2012 %cNIPS %f/NIPS/NIPS-2012-2268.pdf %*Finding Exemplars from Pairwise Dissimilarities via Simultaneous Sparse Recovery %@Ehsan Elhamifar,Guillermo Sapiro,René Vidal %t2012 %cNIPS %f/NIPS/NIPS-2012-2269.pdf %*Feature Clustering for Accelerating Parallel Coordinate Descent %@Chad Scherrer,Ambuj Tewari,Mahantesh Halappanavar,David Haglin %t2012 %cNIPS %f/NIPS/NIPS-2012-2270.pdf %*Multi-scale Hyper-time Hardware Emulation of Human Motor Nervous System Based on Spiking Neurons using FPGA %@C. M. Niu,Sirish Nandyala,Won J. Sohn,Terence Sanger %t2012 %cNIPS %f/NIPS/NIPS-2012-2271.pdf %*Active Learning of Model Evidence Using Bayesian Quadrature %@Michael Osborne,Roman Garnett,Zoubin Ghahramani,David K. Duvenaud,Stephen J. Roberts,Carl E. Rasmussen %t2012 %cNIPS %f/NIPS/NIPS-2012-2272.pdf %*Coupling Nonparametric Mixtures via Latent Dirichlet Processes %@Dahua Lin,John W. Fisher %t2012 %cNIPS %f/NIPS/NIPS-2012-2273.pdf %*Nonparametric Max-Margin Matrix Factorization for Collaborative Prediction %@Minjie Xu,Jun Zhu,Bo Zhang %t2012 %cNIPS %f/NIPS/NIPS-2012-2274.pdf %*Bayesian Hierarchical Reinforcement Learning %@Feng Cao,Soumya Ray %t2012 %cNIPS %f/NIPS/NIPS-2012-2275.pdf %*Local Supervised Learning through Space Partitioning %@Joseph Wang,Venkatesh Saligrama %t2012 %cNIPS %f/NIPS/NIPS-2012-2276.pdf %*A Generative Model for Parts-based Object Segmentation %@S. Eslami,Christopher Williams %t2012 %cNIPS %f/NIPS/NIPS-2012-2277.pdf %*Super-Bit Locality-Sensitive Hashing %@Jianqiu Ji,Jianmin Li,Shuicheng Yan,Bo Zhang,Qi Tian %t2012 %cNIPS %f/NIPS/NIPS-2012-2278.pdf %*Random Utility Theory for Social Choice %@Hossein Azari,David Parks,Lirong Xia %t2012 %cNIPS %f/NIPS/NIPS-2012-2279.pdf %*Putting Bayes to sleep %@Dmitry Adamskiy,Manfred K. Warmuth,Wouter M. Koolen %t2012 %cNIPS %f/NIPS/NIPS-2012-2280.pdf %*Mandatory Leaf Node Prediction in Hierarchical Multilabel Classification %@Wei Bi,James T. Kwok %t2012 %cNIPS %f/NIPS/NIPS-2012-2281.pdf %*Smooth-projected Neighborhood Pursuit for High-dimensional Nonparanormal Graph Estimation %@Tuo Zhao,Kathryn Roeder,Han Liu %t2012 %cNIPS %f/NIPS/NIPS-2012-2282.pdf %*Semiparametric Principal Component Analysis %@Fang Han,Han Liu %t2012 %cNIPS %f/NIPS/NIPS-2012-2283.pdf %*The representer theorem for Hilbert spaces: a necessary and sufficient condition %@Francesco Dinuzzo,Bernhard Schölkopf %t2012 %cNIPS %f/NIPS/NIPS-2012-2284.pdf %*On the (Non-)existence of Convex, Calibrated Surrogate Losses for Ranking %@Clément Calauzènes,Nicolas Usunier,Patrick Gallinari %t2012 %cNIPS %f/NIPS/NIPS-2012-2285.pdf %*Exploration in Model-based Reinforcement Learning by Empirically Estimating Learning Progress %@Manuel Lopes,Tobias Lang,Marc Toussaint,Pierre-yves Oudeyer %t2012 %cNIPS %f/NIPS/NIPS-2012-2286.pdf %*Supervised Learning with Similarity Functions %@Purushottam Kar,Prateek Jain %t2012 %cNIPS %f/NIPS/NIPS-2012-2287.pdf %*Cocktail Party Processing via Structured Prediction %@Yuxuan Wang,Deliang Wang %t2012 %cNIPS %f/NIPS/NIPS-2012-2288.pdf %*Dynamical And-Or Graph Learning for Object Shape Modeling and Detection %@Xiaolong Wang,Liang Lin %t2012 %cNIPS %f/NIPS/NIPS-2012-2289.pdf %*Adaptive Stratified Sampling for Monte-Carlo integration of Differentiable functions %@Alexandra Carpentier,Rémi Munos %t2012 %cNIPS %f/NIPS/NIPS-2012-2290.pdf %*Distributed Non-Stochastic Experts %@Varun Kanade,Zhenming Liu,Bozidar Radunovic %t2012 %cNIPS %f/NIPS/NIPS-2012-2291.pdf %*Learning Image Descriptors with the Boosting-Trick %@Tomasz Trzcinski,Mario Christoudias,Vincent Lepetit,Pascal Fua %t2012 %cNIPS %f/NIPS/NIPS-2012-2292.pdf %*Fast Resampling Weighted v-Statistics %@Chunxiao Zhou,Jiseong Park,Yun Fu %t2012 %cNIPS %f/NIPS/NIPS-2012-2293.pdf %*Multi-task Vector Field Learning %@Binbin Lin,Sen Yang,Chiyuan Zhang,Jieping Ye,Xiaofei He %t2012 %cNIPS %f/NIPS/NIPS-2012-2294.pdf %*Memorability of Image Regions %@Aditya Khosla,Jianxiong Xiao,Antonio Torralba,Aude Oliva %t2012 %cNIPS %f/NIPS/NIPS-2012-2295.pdf %*Nonparametric Bayesian Inverse Reinforcement Learning for Multiple Reward Functions %@Jaedeug Choi,Kee-eung Kim %t2012 %cNIPS %f/NIPS/NIPS-2012-2296.pdf %*Automatic Feature Induction for Stagewise Collaborative Filtering %@Joonseok Lee,Mingxuan Sun,Seungyeon Kim,Guy Lebanon %t2012 %cNIPS %f/NIPS/NIPS-2012-2297.pdf %*Selective Labeling via Error Bound Minimization %@Quanquan Gu,Tong Zhang,Jiawei Han,Chris H. Ding %t2012 %cNIPS %f/NIPS/NIPS-2012-2298.pdf %*Volume Regularization for Binary Classification %@Koby Crammer,Tal Wagner %t2012 %cNIPS %f/NIPS/NIPS-2012-2299.pdf %*Image Denoising and Inpainting with Deep Neural Networks %@Junyuan Xie,Linli Xu,Enhong Chen %t2012 %cNIPS %f/NIPS/NIPS-2012-2300.pdf %*Max-Margin Structured Output Regression for Spatio-Temporal Action Localization %@Du Tran,Junsong Yuan %t2012 %cNIPS %f/NIPS/NIPS-2012-2301.pdf %*Transelliptical Component Analysis %@Fang Han,Han Liu %t2012 %cNIPS %f/NIPS/NIPS-2012-2302.pdf %*Action-Model Based Multi-agent Plan Recognition %@Hankz H. Zhuo,Qiang Yang,Subbarao Kambhampati %t2012 %cNIPS %f/NIPS/NIPS-2012-2303.pdf %*Visual Recognition using Embedded Feature Selection for Curvature Self-Similarity %@Angela Eigenstetter,Bjorn Ommer %t2012 %cNIPS %f/NIPS/NIPS-2012-2304.pdf %*Non-parametric Approximate Dynamic Programming via the Kernel Method %@Nikhil Bhat,Vivek Farias,Ciamac C. Moallemi %t2012 %cNIPS %f/NIPS/NIPS-2012-2305.pdf %*Optimal Regularized Dual Averaging Methods for Stochastic Optimization %@Xi Chen,Qihang Lin,Javier Pena %t2012 %cNIPS %f/NIPS/NIPS-2012-2306.pdf %*The variational hierarchical EM algorithm for clustering hidden Markov models %@Emanuele Coviello,Gert R. Lanckriet,Antoni B. Chan %t2012 %cNIPS %f/NIPS/NIPS-2012-2307.pdf %*Truncation-free Online Variational Inference for Bayesian Nonparametric Models %@Chong Wang,David M. Blei %t2012 %cNIPS %f/NIPS/NIPS-2012-2308.pdf %*3D Social Saliency from Head-mounted Cameras %@Hyun S. Park,Eakta Jain,Yaser Sheikh %t2012 %cNIPS %f/NIPS/NIPS-2012-2309.pdf %*Context-Sensitive Decision Forests for Object Detection %@Peter Kontschieder,Samuel R. Bulò,Antonio Criminisi,Pushmeet Kohli,Marcello Pelillo,Horst Bischof %t2012 %cNIPS %f/NIPS/NIPS-2012-2310.pdf %*Learning Invariant Representations of Molecules for Atomization Energy Prediction %@Grégoire Montavon,Katja Hansen,Siamac Fazli,Matthias Rupp,Franziska Biegler,Andreas Ziehe,Alexandre Tkatchenko,Anatole V. Lilienfeld,Klaus-Robert Müller %t2012 %cNIPS %f/NIPS/NIPS-2012-2311.pdf %*Bandit Algorithms boost Brain Computer Interfaces for motor-task selection of a brain-controlled button %@Joan Fruitet,Alexandra Carpentier,Maureen Clerc,Rémi Munos %t2012 %cNIPS %f/NIPS/NIPS-2012-2312.pdf %*Multiplicative Forests for Continuous-Time Processes %@Jeremy Weiss,Sriraam Natarajan,David Page %t2012 %cNIPS %f/NIPS/NIPS-2012-2313.pdf %*Patient Risk Stratification for Hospital-Associated C. diff as a Time-Series Classification Task %@Jenna Wiens,Eric Horvitz,John V. Guttag %t2012 %cNIPS %f/NIPS/NIPS-2012-2314.pdf %*Nyström Method vs Random Fourier Features: A Theoretical and Empirical Comparison %@Tianbao Yang,Yu-feng Li,Mehrdad Mahdavi,Rong Jin,Zhi-Hua Zhou %t2012 %cNIPS %f/NIPS/NIPS-2012-2315.pdf %*Multiclass Learning Approaches: A Theoretical Comparison with Implications %@Amit Daniely,Sivan Sabato,Shai S. Shwartz %t2012 %cNIPS %f/NIPS/NIPS-2012-2316.pdf %*Stochastic Gradient Descent with Only One Projection %@Mehrdad Mahdavi,Tianbao Yang,Rong Jin,Shenghuo Zhu,Jinfeng Yi %t2012 %cNIPS %f/NIPS/NIPS-2012-2317.pdf %*Neuronal Spike Generation Mechanism as an Oversampling, Noise-shaping A-to-D converter %@Dmitri B. Chklovskii,Daniel Soudry %t2012 %cNIPS %f/NIPS/NIPS-2012-2318.pdf %*Deep Spatio-Temporal Architectures and Learning for Protein Structure Prediction %@Pietro D. Lena,Ken Nagata,Pierre F. Baldi %t2012 %cNIPS %f/NIPS/NIPS-2012-2319.pdf %*Learning to Discover Social Circles in Ego Networks %@Jure Leskovec,Julian J. Mcauley %t2012 %cNIPS %f/NIPS/NIPS-2012-2320.pdf %*A Conditional Multinomial Mixture Model for Superset Label Learning %@Liping Liu,Thomas G. Dietterich %t2012 %cNIPS %f/NIPS/NIPS-2012-2321.pdf %*Majorization for CRFs and Latent Likelihoods %@Tony Jebara,Anna Choromanska %t2012 %cNIPS %f/NIPS/NIPS-2012-2322.pdf %*Ensemble weighted kernel estimators for multivariate entropy estimation %@Kumar Sricharan,Alfred O. Hero %t2012 %cNIPS %f/NIPS/NIPS-2012-2323.pdf %*Efficient high dimensional maximum entropy modeling via symmetric partition functions %@Paul Vernaza,Drew Bagnell %t2012 %cNIPS %f/NIPS/NIPS-2012-2324.pdf %*Discriminatively Trained Sparse Code Gradients for Contour Detection %@Ren Xiaofeng,Liefeng Bo %t2012 %cNIPS %f/NIPS/NIPS-2012-2325.pdf %*Analyzing 3D Objects in Cluttered Images %@Mohsen Hejrati,Deva Ramanan %t2012 %cNIPS %f/NIPS/NIPS-2012-2326.pdf %*Nonconvex Penalization Using Laplace Exponents and Concave Conjugates %@Zhihua Zhang,Bojun Tu %t2012 %cNIPS %f/NIPS/NIPS-2012-2327.pdf %*3D Object Detection and Viewpoint Estimation with a Deformable 3D Cuboid Model %@Sanja Fidler,Sven Dickinson,Raquel Urtasun %t2012 %cNIPS %f/NIPS/NIPS-2012-2328.pdf %*Structured Learning of Gaussian Graphical Models %@Karthik Mohan,Mike Chung,Seungyeop Han,Daniela Witten,Su-in Lee,Maryam Fazel %t2012 %cNIPS %f/NIPS/NIPS-2012-2329.pdf %*A Polylog Pivot Steps Simplex Algorithm for Classification %@Elad Hazan,Zohar Karnin %t2012 %cNIPS %f/NIPS/NIPS-2012-2330.pdf %*Shifting Weights: Adapting Object Detectors from Image to Video %@Kevin Tang,Vignesh Ramanathan,Li Fei-fei,Daphne Koller %t2012 %cNIPS %f/NIPS/NIPS-2012-2331.pdf %*A Scalable CUR Matrix Decomposition Algorithm: Lower Time Complexity and Tighter Bound %@Shusen Wang,Zhihua Zhang %t2012 %cNIPS %f/NIPS/NIPS-2012-2332.pdf %*Convolutional-Recursive Deep Learning for 3D Object Classification %@Richard Socher,Brody Huval,Bharath Bath,Christopher D. Manning,Andrew Y. Ng %t2012 %cNIPS %f/NIPS/NIPS-2012-2333.pdf %*Semi-Supervised Domain Adaptation with Non-Parametric Copulas %@David Lopez-paz,Jose M. Hernández-lobato,Bernhard Schölkopf %t2012 %cNIPS %f/NIPS/NIPS-2012-2334.pdf %*Identification of Recurrent Patterns in the Activation of Brain Networks %@Firdaus Janoos,Weichang Li,Niranjan Subrahmanya,Istvan Morocz,William Wells %t2012 %cNIPS %f/NIPS/NIPS-2012-2335.pdf %*Density-Difference Estimation %@Masashi Sugiyama,Takafumi Kanamori,Taiji Suzuki,Marthinus D. Plessis,Song Liu,Ichiro Takeuchi %t2012 %cNIPS %f/NIPS/NIPS-2012-2336.pdf %*Variational Inference for Crowdsourcing %@Qiang Liu,Jian Peng,Alexander T. Ihler %t2012 %cNIPS %f/NIPS/NIPS-2012-2337.pdf %*MCMC for continuous-time discrete-state systems %@Vinayak Rao,Yee W. Teh %t2012 %cNIPS %f/NIPS/NIPS-2012-2338.pdf %*A P300 BCI for the Masses: Prior Information Enables Instant Unsupervised Spelling %@Pieter-jan Kindermans,Hannes Verschore,David Verstraeten,Benjamin Schrauwen %t2012 %cNIPS %f/NIPS/NIPS-2012-2339.pdf %*Learning about Canonical Views from Internet Image Collections %@Elad Mezuman,Yair Weiss %t2012 %cNIPS %f/NIPS/NIPS-2012-2340.pdf %*Learning High-Density Regions for a Generalized Kolmogorov-Smirnov Test in High-Dimensional Data %@Assaf Glazer,Michael Lindenbaum,Shaul Markovitch %t2012 %cNIPS %f/NIPS/NIPS-2012-2341.pdf %*Multiresolution Gaussian Processes %@Emily Fox,David B. Dunson %t2012 %cNIPS %f/NIPS/NIPS-2012-2342.pdf %*Localizing 3D cuboids in single-view images %@Jianxiong Xiao,Bryan Russell,Antonio Torralba %t2012 %cNIPS %f/NIPS/NIPS-2012-2343.pdf %*Newton-Like Methods for Sparse Inverse Covariance Estimation %@Figen Oztoprak,Jorge Nocedal,Steven Rennie,Peder A. Olsen %t2012 %cNIPS %f/NIPS/NIPS-2012-2344.pdf %*Learning to Align from Scratch %@Gary Huang,Marwan Mattar,Honglak Lee,Erik G. Learned-miller %t2012 %cNIPS %f/NIPS/NIPS-2012-2345.pdf %*Homeostatic plasticity in Bayesian spiking networks as Expectation Maximization with posterior constraints %@Stefan Habenschuss,Johannes Bill,Bernhard Nessler %t2012 %cNIPS %f/NIPS/NIPS-2012-2346.pdf %*Clustering Aggregation as Maximum-Weight Independent Set %@Nan Li,Longin J. Latecki %t2012 %cNIPS %f/NIPS/NIPS-2012-2347.pdf %*Topology Constraints in Graphical Models %@Marcelo Fiori,Pablo Musé,Guillermo Sapiro %t2012 %cNIPS %f/NIPS/NIPS-2012-2348.pdf %*Transelliptical Graphical Models %@Han Liu,Fang Han,Cun-hui Zhang %t2012 %cNIPS %f/NIPS/NIPS-2012-2349.pdf %*Kernel Latent SVM for Visual Recognition %@Weilong Yang,Yang Wang,Arash Vahdat,Greg Mori %t2012 %cNIPS %f/NIPS/NIPS-2012-2350.pdf %*Proximal Newton-type methods for convex optimization %@Jason D. Lee,Yuekai Sun,Michael Saunders %t2012 %cNIPS %f/NIPS/NIPS-2012-2351.pdf %*Regularized Off-Policy TD-Learning %@Bo Liu,Sridhar Mahadevan,Ji Liu %t2012 %cNIPS %f/NIPS/NIPS-2012-2352.pdf %*Multi-criteria Anomaly Detection using Pareto Depth Analysis %@Ko-jen Hsiao,Kevin Xu,Jeff Calder,Alfred O. Hero %t2012 %cNIPS %f/NIPS/NIPS-2012-2353.pdf %*Synchronization can Control Regularization in Neural Systems via Correlated Noise Processes %@Jake Bouvrie,Jean-jeacques Slotine %t2012 %cNIPS %f/NIPS/NIPS-2012-2354.pdf %*Calibrated Elastic Regularization in Matrix Completion %@Tingni Sun,Cun-hui Zhang %t2012 %cNIPS %f/NIPS/NIPS-2012-2355.pdf %*Predicting Action Content On-Line and in Real Time before Action Onset – an Intracranial Human Study %@Uri Maoz,Shengxuan Ye,Ian Ross,Adam Mamelak,Christof Koch %t2012 %cNIPS %f/NIPS/NIPS-2012-2356.pdf %*Searching for objects driven by context %@Bogdan Alexe,Nicolas Heess,Yee W. Teh,Vittorio Ferrari %t2012 %cNIPS %f/NIPS/NIPS-2012-2357.pdf %*Timely Object Recognition %@Sergey Karayev,Tobias Baumgartner,Mario Fritz,Trevor Darrell %t2012 %cNIPS %f/NIPS/NIPS-2012-2358.pdf %*Nonparanormal Belief Propagation (NPNBP) %@Gal Elidan,Cobi Cario %t2012 %cNIPS %f/NIPS/NIPS-2012-2359.pdf %*Deep Representations and Codes for Image Auto-Annotation %@Ryan Kiros,Csaba Szepesvári %t2012 %cNIPS %f/NIPS/NIPS-2012-2360.pdf %*A Spectral Algorithm for Latent Dirichlet Allocation %@Anima Anandkumar,Dean P. Foster,Daniel J. Hsu,Sham M. Kakade,Yi-kai Liu %t2012 %cNIPS %f/NIPS/NIPS-2012-2361.pdf %*Learning Halfspaces with the Zero-One Loss: Time-Accuracy Tradeoffs %@Aharon Birnbaum,Shai S. Shwartz %t2012 %cNIPS %f/NIPS/NIPS-2012-2362.pdf %*Matrix reconstruction with the local max norm %@Rina Foygel,Nathan Srebro,Ruslan R. Salakhutdinov %t2012 %cNIPS %f/NIPS/NIPS-2012-2363.pdf %*Analog readout for optical reservoir computers %@Anteo Smerieri,François Duport,Yvon Paquot,Benjamin Schrauwen,Marc Haelterman,Serge Massar %t2012 %cNIPS %f/NIPS/NIPS-2012-2364.pdf %*Accuracy at the Top %@Stephen Boyd,Corinna Cortes,Mehryar Mohri,Ana Radovanovic %t2012 %cNIPS %f/NIPS/NIPS-2012-2365.pdf %*Minimizing Sparse High-Order Energies by Submodular Vertex-Cover %@Andrew Delong,Olga Veksler,Anton Osokin,Yuri Boykov %t2012 %cNIPS %f/NIPS/NIPS-2012-2366.pdf %*Perfect Dimensionality Recovery by Variational Bayesian PCA %@Shinichi Nakajima,Ryota Tomioka,Masashi Sugiyama,S. D. Babacan %t2012 %cNIPS %f/NIPS/NIPS-2012-2367.pdf %*Mirror Descent Meets Fixed Share (and feels no regret) %@Nicolò Cesa-bianchi,Pierre Gaillard,Gabor Lugosi,Gilles Stoltz %t2012 %cNIPS %f/NIPS/NIPS-2012-2368.pdf %*Near-optimal Differentially Private Principal Components %@Kamalika Chaudhuri,Anand Sarwate,Kaushik Sinha %t2012 %cNIPS %f/NIPS/NIPS-2012-2369.pdf %*Random function priors for exchangeable arrays with applications to graphs and relational data %@James Lloyd,Peter Orbanz,Zoubin Ghahramani,Daniel M. Roy %t2012 %cNIPS %f/NIPS/NIPS-2012-2370.pdf %*Inverse Reinforcement Learning through Structured Classification %@Edouard Klein,Matthieu Geist,Bilal Piot,Olivier Pietquin %t2012 %cNIPS %f/NIPS/NIPS-2012-2371.pdf %*Augmented-SVM: Automatic space partitioning for combining multiple non-linear dynamics %@Ashwini Shukla,Aude Billard %t2012 %cNIPS %f/NIPS/NIPS-2012-2372.pdf %*Efficient Bayes-Adaptive Reinforcement Learning using Sample-Based Search %@Arthur Guez,David Silver,Peter Dayan %t2012 %cNIPS %f/NIPS/NIPS-2012-2373.pdf %*Dimensionality Dependent PAC-Bayes Margin Bound %@Chi Jin,Liwei Wang %t2012 %cNIPS %f/NIPS/NIPS-2012-2374.pdf %*Latent Graphical Model Selection: Efficient Methods for Locally Tree-like Graphs %@Anima Anandkumar,Ragupathyraj Valluvan %t2012 %cNIPS %f/NIPS/NIPS-2012-2375.pdf %*Learning Mixtures of Tree Graphical Models %@Anima Anandkumar,Daniel J. Hsu,Furong Huang,Sham M. Kakade %t2012 %cNIPS %f/NIPS/NIPS-2012-2376.pdf %*Hamming Distance Metric Learning %@Mohammad Norouzi,David J. Fleet,Ruslan R. Salakhutdinov %t2012 %cNIPS %f/NIPS/NIPS-2012-2377.pdf %*Spiking and saturating dendrites differentially expand single neuron computation capacity %@Romain Cazé,Mark Humphries,Boris S. Gutkin %t2012 %cNIPS %f/NIPS/NIPS-2012-2378.pdf %*Clustering by Nonnegative Matrix Factorization Using Graph Random Walk %@Zhirong Yang,Tele Hao,Onur Dikmen,Xi Chen,Erkki Oja %t2012 %cNIPS %f/NIPS/NIPS-2012-2379.pdf %*Delay Compensation with Dynamical Synapses %@Chi Fung,K. Wong,Si Wu %t2012 %cNIPS %f/NIPS/NIPS-2012-2380.pdf %*ImageNet Classification with Deep Convolutional Neural Networks %@Alex Krizhevsky,Ilya Sutskever,Geoffrey E. Hinton %t2012 %cNIPS %f/NIPS/NIPS-2012-2381.pdf %*Recognizing Activities by Attribute Dynamics %@Weixin Li,Nuno Vasconcelos %t2012 %cNIPS %f/NIPS/NIPS-2012-2382.pdf %*Compressive Sensing MRI with Wavelet Tree Sparsity %@Chen Chen,Junzhou Huang %t2012 %cNIPS %f/NIPS/NIPS-2012-2383.pdf %*Training sparse natural image models with a fast Gibbs sampler of an extended state space %@Lucas Theis,Jascha Sohl-dickstein,Matthias Bethge %t2012 %cNIPS %f/NIPS/NIPS-2012-2384.pdf %*A Bayesian Approach for Policy Learning from Trajectory Preference Queries %@Aaron Wilson,Alan Fern,Prasad Tadepalli %t2012 %cNIPS %f/NIPS/NIPS-2012-2385.pdf %*GenDeR: A Generic Diversified Ranking Algorithm %@Jingrui He,Hanghang Tong,Qiaozhu Mei,Boleslaw Szymanski %t2012 %cNIPS %f/NIPS/NIPS-2012-2386.pdf %*On Multilabel Classification and Ranking with Partial Feedback %@Claudio Gentile,Francesco Orabona %t2012 %cNIPS %f/NIPS/NIPS-2012-2387.pdf %*The Lovász ϑ function, SVMs and finding large dense subgraphs %@Vinay Jethava,Anders Martinsson,Chiranjib Bhattacharyya,Devdatt Dubhashi %t2012 %cNIPS %f/NIPS/NIPS-2012-2388.pdf %*Multi-Task Averaging %@Sergey Feldman,Maya Gupta,Bela Frigyik %t2012 %cNIPS %f/NIPS/NIPS-2012-2389.pdf %*Unsupervised Structure Discovery for Semantic Analysis of Audio %@Sourish Chaudhuri,Bhiksha Raj %t2012 %cNIPS %f/NIPS/NIPS-2012-2390.pdf %*A Marginalized Particle Gaussian Process Regression %@Yali Wang,Brahim Chaib-draa %t2012 %cNIPS %f/NIPS/NIPS-2012-2391.pdf %*Angular Quantization-based Binary Codes for Fast Similarity Search %@Yunchao Gong,Sanjiv Kumar,Vishal Verma,Svetlana Lazebnik %t2012 %cNIPS %f/NIPS/NIPS-2012-2392.pdf %*Optimal kernel choice for large-scale two-sample tests %@Arthur Gretton,Dino Sejdinovic,Heiko Strathmann,Sivaraman Balakrishnan,Massimiliano Pontil,Kenji Fukumizu,Bharath K. Sriperumbudur %t2012 %cNIPS %f/NIPS/NIPS-2012-2393.pdf %*Factoring nonnegative matrices with linear programs %@Ben Recht,Christopher Re,Joel Tropp,Victor Bittorf %t2012 %cNIPS %f/NIPS/NIPS-2012-2394.pdf %*Large Scale Distributed Deep Networks %@Jeffrey Dean,Greg Corrado,Rajat Monga,Kai Chen,Matthieu Devin,Mark Mao,Marc'aurelio Ranzato,Andrew Senior,Paul Tucker,Ke Yang,Quoc V. Le,Andrew Y. Ng %t2012 %cNIPS %f/NIPS/NIPS-2012-2395.pdf %*Statistical Consistency of Ranking Methods in A Rank-Differentiable Probability Space %@Yanyan Lan,Jiafeng Guo,Xueqi Cheng,Tie-yan Liu %t2012 %cNIPS %f/NIPS/NIPS-2012-2396.pdf %*Wavelet based multi-scale shape features on arbitrary surfaces for cortical thickness discrimination %@Won H. Kim,Deepti Pachauri,Charles Hatt,Moo. K. Chung,Sterling Johnson,Vikas Singh %t2012 %cNIPS %f/NIPS/NIPS-2012-2397.pdf %*A Convex Formulation for Learning Scale-Free Networks via Submodular Relaxation %@Aaron Defazio,Tibério S. Caetano %t2012 %cNIPS %f/NIPS/NIPS-2012-2398.pdf %*Fused sparsity and robust estimation for linear models with unknown variance %@Arnak Dalalyan,Yin Chen %t2012 %cNIPS %f/NIPS/NIPS-2012-2399.pdf %*How Prior Probability Influences Decision Making: A Unifying Probabilistic Model %@Yanping Huang,Timothy Hanks,Mike Shadlen,Abram L. Friesen,Rajesh P. Rao %t2012 %cNIPS %f/NIPS/NIPS-2012-2400.pdf %*High-Order Multi-Task Feature Learning to Identify Longitudinal Phenotypic Markers for Alzheimer's Disease Progression Prediction %@Hua Wang,Feiping Nie,Heng Huang,Jingwen Yan,Sungeun Kim,Shannon Risacher,Andrew Saykin,Li Shen %t2012 %cNIPS %f/NIPS/NIPS-2012-2401.pdf %*Symmetric Correspondence Topic Models for Multilingual Text Analysis %@Kosuke Fukumasu,Koji Eguchi,Eric P. Xing %t2012 %cNIPS %f/NIPS/NIPS-2012-2402.pdf %*Effective Split-Merge Monte Carlo Methods for Nonparametric Models of Sequential Data %@Michael C. Hughes,Emily Fox,Erik B. Sudderth %t2012 %cNIPS %f/NIPS/NIPS-2012-2403.pdf %*Efficient coding provides a direct link between prior and likelihood in perceptual Bayesian inference %@Xue-xin Wei,Alan Stocker %t2012 %cNIPS %f/NIPS/NIPS-2012-2404.pdf %*Efficient Sampling for Bipartite Matching Problems %@Maksims Volkovs,Richard S. Zemel %t2012 %cNIPS %f/NIPS/NIPS-2012-2405.pdf %*Learning visual motion in recurrent neural networks %@Marius Pachitariu,Maneesh Sahani %t2012 %cNIPS %f/NIPS/NIPS-2012-2406.pdf %*Learned Prioritization for Trading Off Accuracy and Speed %@Jiarong Jiang,Adam Teichert,Jason Eisner,Hal Daume %t2012 %cNIPS %f/NIPS/NIPS-2012-2407.pdf %*Value Pursuit Iteration %@Amir M. Farahmand,Doina Precup %t2012 %cNIPS %f/NIPS/NIPS-2012-2408.pdf %*Graphical Models via Generalized Linear Models %@Eunho Yang,Genevera Allen,Zhandong Liu,Pradeep K. Ravikumar %t2012 %cNIPS %f/NIPS/NIPS-2012-2409.pdf %*CPRL -- An Extension of Compressive Sensing to the Phase Retrieval Problem %@Henrik Ohlsson,Allen Yang,Roy Dong,Shankar Sastry %t2012 %cNIPS %f/NIPS/NIPS-2012-2410.pdf %*Co-Regularized Hashing for Multimodal Data %@Yi Zhen,Dit-Yan Yeung %t2012 %cNIPS %f/NIPS/NIPS-2012-2411.pdf %*Convergence and Energy Landscape for Cheeger Cut Clustering %@Xavier Bresson,Thomas Laurent,David Uminsky,James V. Brecht %t2012 %cNIPS %f/NIPS/NIPS-2012-2412.pdf %*Symbolic Dynamic Programming for Continuous State and Observation POMDPs %@Zahra Zamani,Scott Sanner,Pascal Poupart,Kristian Kersting %t2012 %cNIPS %f/NIPS/NIPS-2012-2413.pdf %*Scaled Gradients on Grassmann Manifolds for Matrix Completion %@Thanh Ngo,Yousef Saad %t2012 %cNIPS %f/NIPS/NIPS-2012-2414.pdf %*Q-MKL: Matrix-induced Regularization in Multi-Kernel Learning with Applications to Neuroimaging %@Chris Hinrichs,Vikas Singh,Jiming Peng,Sterling Johnson %t2012 %cNIPS %f/NIPS/NIPS-2012-2415.pdf %*Privacy Aware Learning %@Martin J. Wainwright,Michael I. Jordan,John C. Duchi %t2012 %cNIPS %f/NIPS/NIPS-2012-2416.pdf %*Finite Sample Convergence Rates of Zero-Order Stochastic Optimization Methods %@Andre Wibisono,Martin J. Wainwright,Michael I. Jordan,John C. Duchi %t2012 %cNIPS %f/NIPS/NIPS-2012-2417.pdf %*Sparse Prediction with the k-Support Norm %@Andreas Argyriou,Rina Foygel,Nathan Srebro %t2012 %cNIPS %f/NIPS/NIPS-2012-2418.pdf %*Active Learning of Multi-Index Function Models %@Tyagi Hemant,Volkan Cevher %t2012 %cNIPS %f/NIPS/NIPS-2012-2419.pdf %*Learning Multiple Tasks using Shared Hypotheses %@Koby Crammer,Yishay Mansour %t2012 %cNIPS %f/NIPS/NIPS-2012-2420.pdf %*On-line Reinforcement Learning Using Incremental Kernel-Based Stochastic Factorization %@Doina Precup,Joelle Pineau,Andre S. Barreto %t2012 %cNIPS %f/NIPS/NIPS-2012-2421.pdf %*Forward-Backward Activation Algorithm for Hierarchical Hidden Markov Models %@Kei Wakabayashi,Takao Miura %t2012 %cNIPS %f/NIPS/NIPS-2012-2422.pdf %*Communication-Efficient Algorithms for Statistical Optimization %@Yuchen Zhang,Martin J. Wainwright,John C. Duchi %t2012 %cNIPS %f/NIPS/NIPS-2012-2423.pdf %*Identifiability and Unmixing of Latent Parse Trees %@Daniel J. Hsu,Sham M. Kakade,Percy S. Liang %t2012 %cNIPS %f/NIPS/NIPS-2012-2424.pdf %*Bayesian nonparametric models for ranked data %@Francois Caron,Yee W. Teh %t2012 %cNIPS %f/NIPS/NIPS-2012-2425.pdf %*Feature-aware Label Space Dimension Reduction for Multi-label Classification %@Yao-nan Chen,Hsuan-tien Lin %t2012 %cNIPS %f/NIPS/NIPS-2012-2426.pdf %*Stochastic optimization and sparse statistical recovery: Optimal algorithms for high dimensions %@Alekh Agarwal,Sahand Negahban,Martin J. Wainwright %t2012 %cNIPS %f/NIPS/NIPS-2012-2427.pdf %*Graphical Gaussian Vector for Image Categorization %@Tatsuya Harada,Yasuo Kuniyoshi %t2012 %cNIPS %f/NIPS/NIPS-2012-2428.pdf %*Joint Modeling of a Matrix with Associated Text via Latent Binary Features %@Xianxing Zhang,Lawrence Carin %t2012 %cNIPS %f/NIPS/NIPS-2012-2429.pdf %*Iterative Thresholding Algorithm for Sparse Inverse Covariance Estimation %@Benjamin Rolfs,Bala Rajaratnam,Dominique Guillot,Ian Wong,Arian Maleki %t2012 %cNIPS %f/NIPS/NIPS-2012-2430.pdf %*Selecting Diverse Features via Spectral Regularization %@Abhimanyu Das,Anirban Dasgupta,Ravi Kumar %t2012 %cNIPS %f/NIPS/NIPS-2012-2431.pdf %*Monte Carlo Methods for Maximum Margin Supervised Topic Models %@Qixia Jiang,Jun Zhu,Maosong Sun,Eric P. Xing %t2012 %cNIPS %f/NIPS/NIPS-2012-2432.pdf %*Parametric Local Metric Learning for Nearest Neighbor Classification %@Jun Wang,Alexandros Kalousis,Adam Woznica %t2012 %cNIPS %f/NIPS/NIPS-2012-2433.pdf %*A Linear Time Active Learning Algorithm for Link Classification %@Nicolò Cesa-bianchi,Claudio Gentile,Fabio Vitale,Giovanni Zappella %t2012 %cNIPS %f/NIPS/NIPS-2012-2434.pdf %*Nonparametric Reduced Rank Regression %@Rina Foygel,Michael Horrell,Mathias Drton,John D. Lafferty %t2012 %cNIPS %f/NIPS/NIPS-2012-2435.pdf %*Multiresolution analysis on the symmetric group %@Risi Kondor,Walter Dempsey %t2012 %cNIPS %f/NIPS/NIPS-2012-2436.pdf %*Isotropic Hashing %@Weihao Kong,Wu-jun Li %t2012 %cNIPS %f/NIPS/NIPS-2012-2437.pdf %*On Lifting the Gibbs Sampling Algorithm %@Deepak Venugopal,Vibhav Gogate %t2012 %cNIPS %f/NIPS/NIPS-2012-2438.pdf %*On the connections between saliency and tracking %@Vijay Mahadevan,Nuno Vasconcelos %t2012 %cNIPS %f/NIPS/NIPS-2012-2439.pdf %*Convex Multi-view Subspace Learning %@Martha White,Xinhua Zhang,Dale Schuurmans,Yao-liang Yu %t2012 %cNIPS %f/NIPS/NIPS-2012-2440.pdf %*Spectral learning of linear dynamics from generalised-linear observations with application to neural population data %@Lars Buesing,Jakob H. Macke,Maneesh Sahani %t2012 %cNIPS %f/NIPS/NIPS-2012-2441.pdf %*Mixability in Statistical Learning %@Tim V. Erven,Peter Grünwald,Mark D. Reid,Robert C. Williamson %t2012 %cNIPS %f/NIPS/NIPS-2012-2442.pdf %*Waveform Driven Plasticity in BiFeO3 Memristive Devices: Model and Implementation %@Christian Mayr,Paul Stärke,Johannes Partzsch,Love Cederstroem,Rene Schüffny,Yao Shuai,Nan Du,Heidemarie Schmidt %t2012 %cNIPS %f/NIPS/NIPS-2012-2443.pdf %*A lattice filter model of the visual pathway %@Karol Gregor,Dmitri B. Chklovskii %t2012 %cNIPS %f/NIPS/NIPS-2012-2444.pdf %*Semantic Kernel Forests from Multiple Taxonomies %@Sung Ju Hwang,Kristen Grauman,Fei Sha %t2012 %cNIPS %f/NIPS/NIPS-2012-2445.pdf %*Causal discovery with scale-mixture model for spatiotemporal variance dependencies %@Zhitang Chen,Kun Zhang,Laiwan Chan %t2012 %cNIPS %f/NIPS/NIPS-2012-2446.pdf %*Natural Images, Gaussian Mixtures and Dead Leaves %@Daniel Zoran,Yair Weiss %t2012 %cNIPS %f/NIPS/NIPS-2012-2447.pdf %*Dual-Space Analysis of the Sparse Linear Model %@Yi Wu,David P. Wipf %t2012 %cNIPS %f/NIPS/NIPS-2012-2448.pdf %*Active Comparison of Prediction Models %@Christoph Sawade,Niels Landwehr,Tobias Scheffer %t2012 %cNIPS %f/NIPS/NIPS-2012-2449.pdf %*Online Regret Bounds for Undiscounted Continuous Reinforcement Learning %@Ronald Ortner,Daniil Ryabko %t2012 %cNIPS %f/NIPS/NIPS-2012-2450.pdf %*Semi-Crowdsourced Clustering: Generalizing Crowd Labeling by Robust Distance Metric Learning %@Jinfeng Yi,Rong Jin,Shaili Jain,Tianbao Yang,Anil K. Jain %t2012 %cNIPS %f/NIPS/NIPS-2012-2451.pdf %*Learning curves for multi-task Gaussian process regression %@Peter Sollich,Simon Ashton %t2012 %cNIPS %f/NIPS/NIPS-2012-2452.pdf %*Kernel Hyperalignment %@Alexander Lorbert,Peter J. Ramadge %t2012 %cNIPS %f/NIPS/NIPS-2012-2453.pdf %*Multiple Choice Learning: Learning to Produce Multiple Structured Outputs %@Abner Guzmán-rivera,Dhruv Batra,Pushmeet Kohli %t2012 %cNIPS %f/NIPS/NIPS-2012-2454.pdf %*Mixing Properties of Conditional Markov Chains with Unbounded Feature Functions %@Mathieu Sinn,Bei Chen %t2012 %cNIPS %f/NIPS/NIPS-2012-2455.pdf %*Persistent Homology for Learning Densities with Bounded Support %@Florian T. Pokorny,Hedvig Kjellström,Danica Kragic,Carl Ek %t2012 %cNIPS %f/NIPS/NIPS-2012-2456.pdf %*On the Use of Non-Stationary Policies for Stationary Infinite-Horizon Markov Decision Processes %@Bruno Scherrer,Boris Lesner %t2012 %cNIPS %f/NIPS/NIPS-2012-2457.pdf %*MAP Inference in Chains using Column Generation %@David Belanger,Alexandre Passos,Sebastian Riedel,Andrew McCallum %t2012 %cNIPS %f/NIPS/NIPS-2012-2458.pdf %*Bayesian Nonparametric Modeling of Suicide Attempts %@Francisco Ruiz,Isabel Valera,Carlos Blanco,Fernando Pérez-Cruz %t2012 %cNIPS %f/NIPS/NIPS-2012-2459.pdf %*Fiedler Random Fields: A Large-Scale Spectral Approach to Statistical Network Modeling %@Antonino Freno,Mikaela Keller,Marc Tommasi %t2012 %cNIPS %f/NIPS/NIPS-2012-2460.pdf %*Neurally Plausible Reinforcement Learning of Working Memory Tasks %@Jaldert Rombouts,Pieter Roelfsema,Sander M. Bohte %t2012 %cNIPS %f/NIPS/NIPS-2012-2461.pdf %*Efficient Monte Carlo Counterfactual Regret Minimization in Games with Many Player Actions %@Neil Burch,Marc Lanctot,Duane Szafron,Richard G. Gibson %t2012 %cNIPS %f/NIPS/NIPS-2012-2462.pdf %*Repulsive Mixtures %@Francesca Petralia,Vinayak Rao,David B. Dunson %t2012 %cNIPS %f/NIPS/NIPS-2012-2463.pdf %*Fully Bayesian inference for neural models with negative-binomial spiking %@James Scott,Jonathan W. Pillow %t2012 %cNIPS %f/NIPS/NIPS-2012-2464.pdf %*Slice Normalized Dynamic Markov Logic Networks %@Tivadar Papai,Henry Kautz,Daniel Stefankovic %t2012 %cNIPS %f/NIPS/NIPS-2012-2465.pdf %*Meta-Gaussian Information Bottleneck %@Melanie Rey,Volker Roth %t2012 %cNIPS %f/NIPS/NIPS-2012-2466.pdf %*Diffusion Decision Making for Adaptive k-Nearest Neighbor Classification %@Yung-kyun Noh,Frank Park,Daniel D. Lee %t2012 %cNIPS %f/NIPS/NIPS-2012-2467.pdf %*The Perturbed Variation %@Maayan Harel,Shie Mannor %t2012 %cNIPS %f/NIPS/NIPS-2012-2468.pdf %*Communication/Computation Tradeoffs in Consensus-Based Distributed Optimization %@Konstantinos Tsianos,Sean Lawlor,Michael G. Rabbat %t2012 %cNIPS %f/NIPS/NIPS-2012-2469.pdf %*The Coloured Noise Expansion and Parameter Estimation of Diffusion Processes %@Simon Lyons,Amos J. Storkey,Simo Särkkä %t2012 %cNIPS %f/NIPS/NIPS-2012-2470.pdf %*Online allocation and homogeneous partitioning for piecewise constant mean-approximation %@Alexandra Carpentier,Odalric-ambrym Maillard %t2012 %cNIPS %f/NIPS/NIPS-2012-2471.pdf %*Learning as MAP Inference in Discrete Graphical Models %@Xianghang Liu,James Petterson,Tibério S. Caetano %t2012 %cNIPS %f/NIPS/NIPS-2012-2472.pdf %*A mechanistic model of early sensory processing based on subtracting sparse representations %@Shaul Druckmann,Tao Hu,Dmitri B. Chklovskii %t2012 %cNIPS %f/NIPS/NIPS-2012-2473.pdf %*Multi-Stage Multi-Task Feature Learning %@Pinghua Gong,Jieping Ye,Chang-shui Zhang %t2012 %cNIPS %f/NIPS/NIPS-2012-2474.pdf %*From Deformations to Parts: Motion-based Segmentation of 3D Objects %@Soumya Ghosh,Matthew Loper,Erik B. Sudderth,Michael J. Black %t2012 %cNIPS %f/NIPS/NIPS-2012-2475.pdf %*Phoneme Classification using Constrained Variational Gaussian Process Dynamical System %@Hyunsin Park,Sungrack Yun,Sanghyuk Park,Jongmin Kim,Chang D. Yoo %t2012 %cNIPS %f/NIPS/NIPS-2012-2476.pdf %*Bayesian estimation of discrete entropy with mixtures of stick-breaking priors %@Evan Archer,Il Memming Park,Jonathan W. Pillow %t2012 %cNIPS %f/NIPS/NIPS-2012-2477.pdf %*A Geometric take on Metric Learning %@Søren Hauberg,Oren Freifeld,Michael J. Black %t2012 %cNIPS %f/NIPS/NIPS-2012-2478.pdf %*Learning the Architecture of Sum-Product Networks Using Clustering on Variables %@Aaron Dennis,Dan Ventura %t2012 %cNIPS %f/NIPS/NIPS-2012-2479.pdf %*Pointwise Tracking the Optimal Regression Function %@Yair Wiener,Ran El-Yaniv %t2012 %cNIPS %f/NIPS/NIPS-2012-2480.pdf %*Reducing statistical time-series problems to binary classification %@Daniil Ryabko,Jeremie Mary %t2012 %cNIPS %f/NIPS/NIPS-2012-2481.pdf %*Tractable Objectives for Robust Policy Optimization %@Katherine Chen,Michael Bowling %t2012 %cNIPS %f/NIPS/NIPS-2012-2482.pdf %*Classification Calibration Dimension for General Multiclass Losses %@Harish G. Ramaswamy,Shivani Agarwal %t2012 %cNIPS %f/NIPS/NIPS-2012-2483.pdf %*Structure estimation for discrete graphical models: Generalized covariance matrices and their inverses %@Po-ling Loh,Martin J. Wainwright %t2012 %cNIPS %f/NIPS/NIPS-2012-2484.pdf %*Collaborative Gaussian Processes for Preference Learning %@Neil Houlsby,Ferenc Huszar,Zoubin Ghahramani,Jose M. Hernández-lobato %t2012 %cNIPS %f/NIPS/NIPS-2012-2485.pdf %*Approximating Concavely Parameterized Optimization Problems %@Joachim Giesen,Jens Mueller,Soeren Laue,Sascha Swiercy %t2012 %cNIPS %f/NIPS/NIPS-2012-2486.pdf %*Gradient-based kernel method for feature extraction and variable selection %@Kenji Fukumizu,Chenlei Leng %t2012 %cNIPS %f/NIPS/NIPS-2012-2487.pdf %*Strategic Impatience in Go/NoGo versus Forced-Choice Decision-Making %@Pradeep Shenoy,Angela J. Yu %t2012 %cNIPS %f/NIPS/NIPS-2012-2488.pdf %*On Triangular versus Edge Representations --- Towards Scalable Modeling of Networks %@Qirong Ho,Junming Yin,Eric P. Xing %t2012 %cNIPS %f/NIPS/NIPS-2012-2489.pdf %*Relax and Randomize : From Value to Algorithms %@Sasha Rakhlin,Ohad Shamir,Karthik Sridharan %t2012 %cNIPS %f/NIPS/NIPS-2012-2490.pdf %*Minimax Multi-Task Learning and a Generalized Loss-Compositional Paradigm for MTL %@Nishant Mehta,Dongryeol Lee,Alexander G. Gray %t2012 %cNIPS %f/NIPS/NIPS-2012-2491.pdf %*Spectral Learning of General Weighted Automata via Constrained Matrix Completion %@Borja Balle,Mehryar Mohri %t2012 %cNIPS %f/NIPS/NIPS-2012-2492.pdf %*Optimal Neural Tuning Curves for Arbitrary Stimulus Distributions: Discrimax, Infomax and Minimum L_p Loss %@Zhuo Wang,Alan Stocker,Daniel Lee %t2012 %cNIPS %f/NIPS/NIPS-2012-2493.pdf %*Algorithms for Learning Markov Field Policies %@Abdeslam Boularias,Jan R. Peters,Oliver B. Kroemer %t2012 %cNIPS %f/NIPS/NIPS-2012-2494.pdf %*Affine Independent Variational Inference %@Edward Challis,David Barber %t2012 %cNIPS %f/NIPS/NIPS-2012-2495.pdf %*Learning from the Wisdom of Crowds by Minimax Entropy %@Denny Zhou,Sumit Basu,Yi Mao,John C. Platt %t2012 %cNIPS %f/NIPS/NIPS-2012-2496.pdf %*Clustering Sparse Graphs %@Yudong Chen,Sujay Sanghavi,Huan Xu %t2012 %cNIPS %f/NIPS/NIPS-2012-2497.pdf %*Sketch-Based Linear Value Function Approximation %@Marc Bellemare,Joel Veness,Michael Bowling %t2012 %cNIPS %f/NIPS/NIPS-2012-2498.pdf %*Multimodal Learning with Deep Boltzmann Machines %@Nitish Srivastava,Ruslan R. Salakhutdinov %t2012 %cNIPS %f/NIPS/NIPS-2012-2499.pdf %*Learning with Target Prior %@Zuoguan Wang,Siwei Lyu,Gerwin Schalk,Qiang Ji %t2012 %cNIPS %f/NIPS/NIPS-2012-2500.pdf %*Slice sampling normalized kernel-weighted completely random measure mixture models %@Nicholas Foti,Sinead Williamson %t2012 %cNIPS %f/NIPS/NIPS-2012-2501.pdf %*Scalable Inference of Overlapping Communities %@Prem K. Gopalan,Sean Gerrish,Michael Freedman,David M. Blei,David M. Mimno %t2012 %cNIPS %f/NIPS/NIPS-2012-2502.pdf %*Online L1-Dictionary Learning with Application to Novel Document Detection %@Shiva P. Kasiviswanathan,Huahua Wang,Arindam Banerjee,Prem Melville %t2012 %cNIPS %f/NIPS/NIPS-2012-2503.pdf %*A systematic approach to extracting semantic information from functional MRI data %@Francisco Pereira,Matthew Botvinick %t2012 %cNIPS %f/NIPS/NIPS-2012-2504.pdf %*Why MCA? Nonlinear sparse coding with spike-and-slab prior for neurally plausible image encoding %@Philip Sterne,Joerg Bornschein,Abdul-saboor Sheikh,Joerg Luecke,Jacquelyn A. Shelton %t2012 %cNIPS %f/NIPS/NIPS-2012-2505.pdf %*Learning optimal spike-based representations %@Ralph Bourdoukan,David Barrett,Sophie Deneve,Christian K. Machens %t2012 %cNIPS %f/NIPS/NIPS-2012-2506.pdf %*Collaborative Ranking With 17 Parameters %@Maksims Volkovs,Richard S. Zemel %t2012 %cNIPS %f/NIPS/NIPS-2012-2507.pdf %*Rational inference of relative preferences %@Nisheeth Srivastava,Paul R. Schrater %t2012 %cNIPS %f/NIPS/NIPS-2012-2508.pdf %*The topographic unsupervised learning of natural sounds in the auditory cortex %@Hiroki Terashima,Masato Okada %t2012 %cNIPS %f/NIPS/NIPS-2012-2509.pdf %*Approximating Equilibria in Sequential Auctions with Incomplete Information and Multi-Unit Demand %@Amy Greenwald,Jiacui Li,Eric Sodomka %t2012 %cNIPS %f/NIPS/NIPS-2012-2510.pdf %*A Divide-and-Conquer Method for Sparse Inverse Covariance Estimation %@Cho-jui Hsieh,Arindam Banerjee,Inderjit S. Dhillon,Pradeep K. Ravikumar %t2012 %cNIPS %f/NIPS/NIPS-2012-2511.pdf %*A Simple and Practical Algorithm for Differentially Private Data Release %@Moritz Hardt,Katrina Ligett,Frank Mcsherry %t2012 %cNIPS %f/NIPS/NIPS-2012-2512.pdf %*Bayesian active learning with localized priors for fast receptive field characterization %@Mijung Park,Jonathan W. Pillow %t2012 %cNIPS %f/NIPS/NIPS-2012-2513.pdf %*Weighted Likelihood Policy Search with Model Selection %@Tsuyoshi Ueno,Kohei Hayashi,Takashi Washio,Yoshinobu Kawahara %t2012 %cNIPS %f/NIPS/NIPS-2012-2514.pdf %*Learning the Dependency Structure of Latent Factors %@Yunlong He,Yanjun Qi,Koray Kavukcuoglu,Haesun Park %t2012 %cNIPS %f/NIPS/NIPS-2012-2515.pdf %*Provable ICA with Unknown Gaussian Noise, with Implications for Gaussian Mixtures and Autoencoders %@Sanjeev Arora,Rong Ge,Ankur Moitra,Sushant Sachdeva %t2012 %cNIPS %f/NIPS/NIPS-2012-2516.pdf %*Globally Convergent Dual MAP LP Relaxation Solvers using Fenchel-Young Margins %@Alex Schwing,Tamir Hazan,Marc Pollefeys,Raquel Urtasun %t2012 %cNIPS %f/NIPS/NIPS-2012-2517.pdf %*Dip-means: an incremental clustering method for estimating the number of clusters %@Argyris Kalogeratos,Aristidis Likas %t2012 %cNIPS %f/NIPS/NIPS-2012-2518.pdf %*No-Regret Algorithms for Unconstrained Online Convex Optimization %@Brendan Mcmahan,Matthew Streeter %t2012 %cNIPS %f/NIPS/NIPS-2012-2519.pdf %*Bayesian models for Large-scale Hierarchical Classification %@Siddharth Gopal,Yiming Yang,Bing Bai,Alexandru Niculescu-mizil %t2012 %cNIPS %f/NIPS/NIPS-2012-2520.pdf %*Recovery of Sparse Probability Measures via Convex Programming %@Mert Pilanci,Laurent E. Ghaoui,Venkat Chandrasekaran %t2012 %cNIPS %f/NIPS/NIPS-2012-2521.pdf %*Multiple Operator-valued Kernel Learning %@Hachem Kadri,Alain Rakotomamonjy,Philippe Preux,Francis R. Bach %t2012 %cNIPS %f/NIPS/NIPS-2012-2522.pdf %*Approximate Message Passing with Consistent Parameter Estimation and Applications to Sparse Learning %@Ulugbek Kamilov,Sundeep Rangan,Michael Unser,Alyson K. Fletcher %t2012 %cNIPS %f/NIPS/NIPS-2012-2523.pdf %*A Better Way to Pretrain Deep Boltzmann Machines %@Geoffrey E. Hinton,Ruslan R. Salakhutdinov %t2012 %cNIPS %f/NIPS/NIPS-2012-2524.pdf %*Towards a learning-theoretic analysis of spike-timing dependent plasticity %@David Balduzzi,Michel Besserve %t2012 %cNIPS %f/NIPS/NIPS-2012-2525.pdf %*Learning Manifolds with K-Means and K-Flats %@Guillermo Canas,Tomaso Poggio,Lorenzo Rosasco %t2012 %cNIPS %f/NIPS/NIPS-2012-2526.pdf %*Iterative ranking from pair-wise comparisons %@Sahand Negahban,Sewoong Oh,Devavrat Shah %t2012 %cNIPS %f/NIPS/NIPS-2012-2527.pdf %*A Polynomial-time Form of Robust Regression %@Yao-liang Yu,Özlem Aslan,Dale Schuurmans %t2012 %cNIPS %f/NIPS/NIPS-2012-2528.pdf %*Learning Probability Measures with respect to Optimal Transport Metrics %@Guillermo Canas,Lorenzo Rosasco %t2012 %cNIPS %f/NIPS/NIPS-2012-2529.pdf %*Label Ranking with Partial Abstention based on Thresholded Probabilistic Models %@Weiwei Cheng,Eyke Hüllermeier,Willem Waegeman,Volkmar Welker %t2012 %cNIPS %f/NIPS/NIPS-2012-2530.pdf %*Adaptive Learning of Smoothing Functions: Application to Electricity Load Forecasting %@Amadou Ba,Mathieu Sinn,Yannig Goude,Pascal Pompey %t2012 %cNIPS %f/NIPS/NIPS-2012-2531.pdf %*Tensor Decomposition for Fast Parsing with Latent-Variable PCFGs %@Michael Collins,Shay B. Cohen %t2012 %cNIPS %f/NIPS/NIPS-2012-2532.pdf %*Semi-supervised Eigenvectors for Locally-biased Learning %@Toke Hansen,Michael W. Mahoney %t2012 %cNIPS %f/NIPS/NIPS-2012-2533.pdf %*Exponential Concentration for Mutual Information Estimation with Application to Forests %@Han Liu,Larry Wasserman,John D. Lafferty %t2012 %cNIPS %f/NIPS/NIPS-2012-2534.pdf %*Augment-and-Conquer Negative Binomial Processes %@Mingyuan Zhou,Lawrence Carin %t2012 %cNIPS %f/NIPS/NIPS-2012-2535.pdf %*Transferring Expectations in Model-based Reinforcement Learning %@Trung Nguyen,Tomi Silander,Tze Y. Leong %t2012 %cNIPS %f/NIPS/NIPS-2012-2536.pdf %*Minimization of Continuous Bethe Approximations: A Positive Variation %@Jason Pacheco,Erik B. Sudderth %t2012 %cNIPS %f/NIPS/NIPS-2012-2537.pdf %*Non-linear Metric Learning %@Dor Kedem,Stephen Tyree,Fei Sha,Gert R. Lanckriet,Kilian Q. Weinberger %t2012 %cNIPS %f/NIPS/NIPS-2012-2538.pdf %*Factorial LDA: Sparse Multi-Dimensional Text Models %@Michael Paul,Mark Dredze %t2012 %cNIPS %f/NIPS/NIPS-2012-2539.pdf %*Ancestor Sampling for Particle Gibbs %@Fredrik Lindsten,Thomas Schön,Michael I. Jordan %t2012 %cNIPS %f/NIPS/NIPS-2012-2540.pdf %*Modelling Reciprocating Relationships with Hawkes Processes %@Charles Blundell,Jeff Beck,Katherine A. Heller %t2012 %cNIPS %f/NIPS/NIPS-2012-2541.pdf %*Expectation Propagation in Gaussian Process Dynamical Systems %@Marc Deisenroth,Shakir Mohamed %t2012 %cNIPS %f/NIPS/NIPS-2012-2542.pdf %*A quasi-Newton proximal splitting method %@Stephen Becker,Jalal Fadili %t2012 %cNIPS %f/NIPS/NIPS-2012-2543.pdf %*Exact and Stable Recovery of Sequences of Signals with Sparse Increments via Differential _1-Minimization %@Demba Ba,Behtash Babadi,Patrick Purdon,Emery Brown %t2012 %cNIPS %f/NIPS/NIPS-2012-2544.pdf %*Efficient Reinforcement Learning for High Dimensional Linear Quadratic Systems %@Morteza Ibrahimi,Adel Javanmard,Benjamin V. Roy %t2012 %cNIPS %f/NIPS/NIPS-2012-2545.pdf %*Multilabel Classification using Bayesian Compressed Sensing %@Ashish Kapoor,Raajay Viswanathan,Prateek Jain %t2012 %cNIPS %f/NIPS/NIPS-2012-2546.pdf %*Scaling MPE Inference for Constrained Continuous Markov Random Fields with Consensus Optimization %@Stephen Bach,Matthias Broecheler,Lise Getoor,Dianne O'leary %t2012 %cNIPS %f/NIPS/NIPS-2012-2547.pdf %*A Stochastic Gradient Method with an Exponential Convergence _Rate for Finite Training Sets %@Nicolas L. Roux,Mark Schmidt,Francis R. Bach %t2012 %cNIPS %f/NIPS/NIPS-2012-2548.pdf %*Query Complexity of Derivative-Free Optimization %@Kevin G. Jamieson,Robert Nowak,Ben Recht %t2012 %cNIPS %f/NIPS/NIPS-2012-2549.pdf %*Emergence of Object-Selective Features in Unsupervised Feature Learning %@Adam Coates,Andrej Karpathy,Andrew Y. Ng %t2012 %cNIPS %f/NIPS/NIPS-2012-2550.pdf %*Burn-in, bias, and the rationality of anchoring %@Falk Lieder,Thomas Griffiths,Noah Goodman %t2012 %cNIPS %f/NIPS/NIPS-2012-2551.pdf %*Truly Nonparametric Online Variational Inference for Hierarchical Dirichlet Processes %@Michael Bryant,Erik B. Sudderth %t2012 %cNIPS %f/NIPS/NIPS-2012-2552.pdf %*A Neural Autoregressive Topic Model %@Hugo Larochelle,Stanislas Lauly %t2012 %cNIPS %f/NIPS/NIPS-2012-2553.pdf %*A Unifying Perspective of Parametric Policy Search Methods for Markov Decision Processes %@Thomas Furmston,David Barber %t2012 %cNIPS %f/NIPS/NIPS-2012-2554.pdf %*Entangled Monte Carlo %@Seong-hwan Jun,Liangliang Wang,Alexandre Bouchard-côté %t2012 %cNIPS %f/NIPS/NIPS-2012-2555.pdf %*Near-Optimal MAP Inference for Determinantal Point Processes %@Jennifer Gillenwater,Alex Kulesza,Ben Taskar %t2012 %cNIPS %f/NIPS/NIPS-2012-2556.pdf %*Probabilistic Low-Rank Subspace Clustering %@S. D. Babacan,Shinichi Nakajima,Minh Do %t2012 %cNIPS %f/NIPS/NIPS-2012-2557.pdf %*How They Vote: Issue-Adjusted Models of Legislative Behavior %@Sean Gerrish,David M. Blei %t2012 %cNIPS %f/NIPS/NIPS-2012-2558.pdf %*Density Propagation and Improved Bounds on the Partition Function %@Stefano Ermon,Ashish Sabharwal,Bart Selman,Carla P. Gomes %t2012 %cNIPS %f/NIPS/NIPS-2012-2559.pdf %*Perceptron Learning of SAT %@Alex Flint,Matthew Blaschko %t2012 %cNIPS %f/NIPS/NIPS-2012-2560.pdf %*Learning Networks of Heterogeneous Influence %@Nan Du,Le Song,Ming Yuan,Alex J. Smola %t2012 %cNIPS %f/NIPS/NIPS-2012-2561.pdf %*Multiclass Learning with Simplex Coding %@Youssef Mroueh,Tomaso Poggio,Lorenzo Rosasco,Jean-jeacques Slotine %t2012 %cNIPS %f/NIPS/NIPS-2012-2562.pdf %*FastEx: Hash Clustering with Exponential Families %@Amr Ahmed,Sujith Ravi,Alex J. Smola,Shravan M. Narayanamurthy %t2012 %cNIPS %f/NIPS/NIPS-2012-2563.pdf %*Topic-Partitioned Multinetwork Embeddings %@Peter Krafft,Juston Moore,Bruce Desmarais,Hanna M. Wallach %t2012 %cNIPS %f/NIPS/NIPS-2012-2564.pdf %*Learning Label Trees for Probabilistic Modelling of Implicit Feedback %@Andriy Mnih,Yee W. Teh %t2012 %cNIPS %f/NIPS/NIPS-2012-2565.pdf %*Learning with Recursive Perceptual Representations %@Oriol Vinyals,Yangqing Jia,Li Deng,Trevor Darrell %t2012 %cNIPS %f/NIPS/NIPS-2012-2566.pdf %*Link Prediction in Graphs with Autoregressive Features %@Emile Richard,Stephane Gaiffas,Nicolas Vayatis %t2012 %cNIPS %f/NIPS/NIPS-2012-2567.pdf %*Deep Neural Networks Segment Neuronal Membranes in Electron Microscopy Images %@Dan Ciresan,Alessandro Giusti,Luca M. Gambardella,Juergen Schmidhuber %t2012 %cNIPS %f/NIPS/NIPS-2012-2568.pdf %*Scalable imputation of genetic data with a discrete fragmentation-coagulation process %@Lloyd Elliott,Yee W. Teh %t2012 %cNIPS %f/NIPS/NIPS-2012-2569.pdf %*Gradient Weights help Nonparametric Regressors %@Samory Kpotufe,Abdeslam Boularias %t2012 %cNIPS %f/NIPS/NIPS-2012-2570.pdf %*Online Sum-Product Computation Over Trees %@Mark Herbster,Stephen Pasteris,Fabio Vitale %t2012 %cNIPS %f/NIPS/NIPS-2012-2571.pdf %*Sparse Approximate Manifolds for Differential Geometric MCMC %@Ben Calderhead,Mátyás A. Sustik %t2012 %cNIPS %f/NIPS/NIPS-2012-2572.pdf %*Fast Variational Inference in the Conjugate Exponential Family %@James Hensman,Magnus Rattray,Neil D. Lawrence %t2012 %cNIPS %f/NIPS/NIPS-2012-2573.pdf %*Bayesian Pedigree Analysis using Measure Factorization %@Bonnie Kirkpatrick,Alexandre Bouchard-côté %t2012 %cNIPS %f/NIPS/NIPS-2012-2574.pdf %*Accelerated Training for Matrix-norm Regularization: A Boosting Approach %@Xinhua Zhang,Dale Schuurmans,Yao-liang Yu %t2012 %cNIPS %f/NIPS/NIPS-2012-2575.pdf %*Controlled Recognition Bounds for Visual Learning and Exploration %@Vasiliy Karasev,Alessandro Chiuso,Stefano Soatto %t2012 %cNIPS %f/NIPS/NIPS-2012-2576.pdf %*Distributed Probabilistic Learning for Camera Networks with Missing Data %@Sejong Yoon,Vladimir Pavlovic %t2012 %cNIPS %f/NIPS/NIPS-2012-2577.pdf %*Submodular-Bregman and the Lovász-Bregman Divergences with Applications %@Rishabh Iyer,Jeff A. Bilmes %t2012 %cNIPS %f/NIPS/NIPS-2012-2578.pdf %*Minimizing Uncertainty in Pipelines %@Nilesh Dalvi,Aditya Parameswaran,Vibhor Rastogi %t2012 %cNIPS %f/NIPS/NIPS-2012-2579.pdf %*Practical Bayesian Optimization of Machine Learning Algorithms %@Jasper Snoek,Hugo Larochelle,Ryan P. Adams %t2012 %cNIPS %f/NIPS/NIPS-2012-2580.pdf %*Forging The Graphs: A Low Rank and Positive Semidefinite Graph Learning Approach %@Dijun Luo,Heng Huang,Feiping Nie,Chris H. Ding %t2012 %cNIPS %f/NIPS/NIPS-2012-2581.pdf %*The Time-Marginalized Coalescent Prior for Hierarchical Clustering %@Levi Boyles,Max Welling %t2012 %cNIPS %f/NIPS/NIPS-2012-2582.pdf %*Fusion with Diffusion for Robust Visual Tracking %@Yu Zhou,Xiang Bai,Wenyu Liu,Longin J. Latecki %t2012 %cNIPS %f/NIPS/NIPS-2012-2583.pdf %*A nonparametric variable clustering model %@Konstantina Palla,Zoubin Ghahramani,David A. Knowles %t2012 %cNIPS %f/NIPS/NIPS-2012-2584.pdf %*Priors for Diversity in Generative Latent Variable Models %@James T. Kwok,Ryan P. Adams %t2012 %cNIPS %f/NIPS/NIPS-2012-2585.pdf %*A Nonparametric Conjugate Prior Distribution for the Maximizing Argument of a Noisy Function %@Pedro Ortega,Jordi Grau-moya,Tim Genewein,David Balduzzi,Daniel Braun %t2012 %cNIPS %f/NIPS/NIPS-2012-2586.pdf %*Convergence Rate Analysis of MAP Coordinate Minimization Algorithms %@Ofer Meshi,Amir Globerson,Tommi S. Jaakkola %t2012 %cNIPS %f/NIPS/NIPS-2012-2587.pdf %*Projection Retrieval for Classification %@Madalina Fiterau,Artur Dubrawski %t2012 %cNIPS %f/NIPS/NIPS-2012-2588.pdf %*Hierarchical spike coding of sound %@Yan Karklin,Chaitanya Ekanadham,Eero P. Simoncelli %t2012 %cNIPS %f/NIPS/NIPS-2012-2589.pdf %*Human memory search as a random walk in a semantic network %@Joseph L. Austerweil,Joshua T. Abbott,Thomas L. Griffiths %t2012 %cNIPS %f/NIPS/NIPS-2012-2590.pdf %*Probabilistic n-Choose-k Models for Classification and Ranking %@Kevin Swersky,Brendan J. Frey,Daniel Tarlow,Richard S. Zemel,Ryan P. Adams %t2012 %cNIPS %f/NIPS/NIPS-2012-2591.pdf %*Complex Inference in Neural Circuits with Probabilistic Population Codes and Topic Models %@Jeff Beck,Alexandre Pouget,Katherine A. Heller %t2012 %cNIPS %f/NIPS/NIPS-2012-2592.pdf %*Cost-Sensitive Exploration in Bayesian Reinforcement Learning %@Dongho Kim,Kee-eung Kim,Pascal Poupart %t2012 %cNIPS %f/NIPS/NIPS-2012-2593.pdf %*Learning with Partially Absorbing Random Walks %@Xiao-ming Wu,Zhenguo Li,Anthony M. So,John Wright,Shih-fu Chang %t2012 %cNIPS %f/NIPS/NIPS-2012-2594.pdf %*Locating Changes in Highly Dependent Data with Unknown Number of Change Points %@Azadeh Khaleghi,Daniil Ryabko %t2012 %cNIPS %f/NIPS/NIPS-2012-2595.pdf %*Probabilistic Event Cascades for Alzheimer's disease %@Jonathan Huang,Daniel Alexander %t2012 %cNIPS %f/NIPS/NIPS-2012-2596.pdf %*Efficient and direct estimation of a neural subunit model for sensory coding %@Brett Vintch,Andrew Zaharia,J Movshon,Eero P. Simoncelli %t2012 %cNIPS %f/NIPS/NIPS-2012-2597.pdf %*One Permutation Hashing %@Ping Li,Art Owen,Cun-hui Zhang %t2012 %cNIPS %f/NIPS/NIPS-2012-2598.pdf %*Unsupervised Template Learning for Fine-Grained Object Recognition %@Shulin Yang,Liefeng Bo,Jue Wang,Linda G. Shapiro %t2012 %cNIPS %f/NIPS/NIPS-2012-2599.pdf %*Risk Aversion in Markov Decision Processes via Near Optimal Chernoff Bounds %@Teodor M. Moldovan,Pieter Abbeel %t2012 %cNIPS %f/NIPS/NIPS-2012-2600.pdf %*Fast Bayesian Inference for Non-Conjugate Gaussian Process Regression %@Emtiyaz Khan,Shakir Mohamed,Kevin P. Murphy %t2012 %cNIPS %f/NIPS/NIPS-2012-2601.pdf %*Imitation Learning by Coaching %@He He,Jason Eisner,Hal Daume %t2012 %cNIPS %f/NIPS/NIPS-2012-2602.pdf %*Small-Variance Asymptotics for Exponential Family Dirichlet Process Mixture Models %@Ke Jiang,Brian Kulis,Michael I. Jordan %t2012 %cNIPS %f/NIPS/NIPS-2012-2603.pdf %*A latent factor model for highly multi-relational data %@Rodolphe Jenatton,Nicolas L. Roux,Antoine Bordes,Guillaume R. Obozinski %t2012 %cNIPS %f/NIPS/NIPS-2012-2604.pdf %*Entropy Estimations Using Correlated Symmetric Stable Random Projections %@Ping Li,Cun-hui Zhang %t2012 %cNIPS %f/NIPS/NIPS-2012-2605.pdf %*Simultaneously Leveraging Output and Task Structures for Multiple-Output Regression %@Piyush Rai,Abhishek Kumar,Hal Daume %t2012 %cNIPS %f/NIPS/NIPS-2012-2606.pdf %*Continuous Relaxations for Discrete Hamiltonian Monte Carlo %@Yichuan Zhang,Zoubin Ghahramani,Amos J. Storkey,Charles A. Sutton %t2012 %cNIPS %f/NIPS/NIPS-2012-2607.pdf %*Deep Learning of Invariant Features via Simulated Fixations in Video %@Will Zou,Shenghuo Zhu,Kai Yu,Andrew Y. Ng %t2012 %cNIPS %f/NIPS/NIPS-2012-2608.pdf %*Best Arm Identification: A Unified Approach to Fixed Budget and Fixed Confidence %@Victor Gabillon,Mohammad Ghavamzadeh,Alessandro Lazaric %t2012 %cNIPS %f/NIPS/NIPS-2012-2609.pdf %*On the Sample Complexity of Robust PCA %@Matthew Coudron,Gilad Lerman %t2012 %cNIPS %f/NIPS/NIPS-2012-2610.pdf %*Latent Coincidence Analysis: A Hidden Variable Model for Distance Metric Learning %@Matthew Der,Lawrence K. Saul %t2012 %cNIPS %f/NIPS/NIPS-2012-2611.pdf %*Discriminative Learning of Sum-Product Networks %@Robert Gens,Pedro Domingos %t2012 %cNIPS %f/NIPS/NIPS-2012-2612.pdf %*Trajectory-Based Short-Sighted Probabilistic Planning %@Felipe Trevizan,Manuela Veloso %t2012 %cNIPS %f/NIPS/NIPS-2012-2613.pdf %*Tight Bounds on Profile Redundancy and Distinguishability %@Jayadev Acharya,Hirakendu Das,Alon Orlitsky %t2012 %cNIPS %f/NIPS/NIPS-2012-2614.pdf %*Interpreting prediction markets: a stochastic approach %@Rafael M. Frongillo,Nicholás Della Penna,Mark D. Reid %t2012 %cNIPS %f/NIPS/NIPS-2012-2615.pdf %*Risk-Aversion in Multi-armed Bandits %@Amir Sani,Alessandro Lazaric,Rémi Munos %t2012 %cNIPS %f/NIPS/NIPS-2012-2616.pdf %*Cardinality Restricted Boltzmann Machines %@Kevin Swersky,Ilya Sutskever,Daniel Tarlow,Richard S. Zemel,Ruslan R. Salakhutdinov,Ryan P. Adams %t2012 %cNIPS %f/NIPS/NIPS-2012-2617.pdf %*Generalization Bounds for Domain Adaptation %@Chao Zhang,Lei Zhang,Jieping Ye %t2012 %cNIPS %f/NIPS/NIPS-2012-2618.pdf %*The Randomized Dependence Coefficient %@David Lopez-Paz,Philipp Hennig,Bernhard Schölkopf %t2013 %cNIPS %f/NIPS/NIPS-2013-2619.pdf %*Documents as multiple overlapping windows into grids of counts %@Alessandro Perina,Nebojsa Jojic,Manuele Bicego,Andrzej Truski %t2013 %cNIPS %f/NIPS/NIPS-2013-2620.pdf %*Reciprocally Coupled Local Estimators Implement Bayesian Information Integration Distributively %@Wenhao Zhang,Si Wu %t2013 %cNIPS %f/NIPS/NIPS-2013-2621.pdf %*Latent Maximum Margin Clustering %@Guang-Tong Zhou,Tian Lan,Arash Vahdat,Greg Mori %t2013 %cNIPS %f/NIPS/NIPS-2013-2622.pdf %*Data-driven Distributionally Robust Polynomial Optimization %@Martin Mevissen,Emanuele Ragnoli,Jia Yuan Yu %t2013 %cNIPS %f/NIPS/NIPS-2013-2623.pdf %*Transfer Learning in a Transductive Setting %@Marcus Rohrbach,Sandra Ebert,Bernt Schiele %t2013 %cNIPS %f/NIPS/NIPS-2013-2624.pdf %*Bayesian optimization explains human active search %@Ali Borji,Laurent Itti %t2013 %cNIPS %f/NIPS/NIPS-2013-2625.pdf %*Provable Subspace Clustering: When LRR meets SSC %@Yu-Xiang Wang,Huan Xu,Chenlei Leng %t2013 %cNIPS %f/NIPS/NIPS-2013-2626.pdf %*Generalized Random Utility Models with Multiple Types %@Hossein Azari Soufiani,Hansheng Diao,Zhenyu Lai,David C. Parkes %t2013 %cNIPS %f/NIPS/NIPS-2013-2627.pdf %*Polar Operators for Structured Sparse Estimation %@Xinhua Zhang,Yao-Liang Yu,Dale Schuurmans %t2013 %cNIPS %f/NIPS/NIPS-2013-2628.pdf %*Point Based Value Iteration with Optimal Belief Compression for Dec-POMDPs %@Liam C. MacDermed,Charles Isbell %t2013 %cNIPS %f/NIPS/NIPS-2013-2629.pdf %*PAC-Bayes-Empirical-Bernstein Inequality %@Ilya O. Tolstikhin,Yevgeny Seldin %t2013 %cNIPS %f/NIPS/NIPS-2013-2630.pdf %*Modeling Clutter Perception using Parametric Proto-object Partitioning %@Chen-Ping Yu,Wen-Yu Hua,Dimitris Samaras,Greg Zelinsky %t2013 %cNIPS %f/NIPS/NIPS-2013-2631.pdf %*Robust Multimodal Graph Matching: Sparse Coding Meets Graph Matching %@Marcelo Fiori,Pablo Sprechmann,Joshua Vogelstein,Pablo Muse,Guillermo Sapiro %t2013 %cNIPS %f/NIPS/NIPS-2013-2632.pdf %*Transportability from Multiple Environments with Limited Experiments %@Elias Bareinboim,Sanghack Lee,Vasant Honavar,Judea Pearl %t2013 %cNIPS %f/NIPS/NIPS-2013-2633.pdf %*More data speeds up training time in learning halfspaces over sparse vectors %@Amit Daniely,Nati Linial,Shai Shalev-Shwartz %t2013 %cNIPS %f/NIPS/NIPS-2013-2634.pdf %*Causal Inference on Time Series using Restricted Structural Equation Models %@Jonas Peters,Dominik Janzing,Bernhard Schölkopf %t2013 %cNIPS %f/NIPS/NIPS-2013-2635.pdf %*Deep Fisher Networks for Large-Scale Image Classification %@Karen Simonyan,Andrea Vedaldi,Andrew Zisserman %t2013 %cNIPS %f/NIPS/NIPS-2013-2636.pdf %*Variance Reduction for Stochastic Gradient Optimization %@Chong Wang,Xi Chen,Alex J. Smola,Eric P. Xing %t2013 %cNIPS %f/NIPS/NIPS-2013-2637.pdf %*Training and Analysing Deep Recurrent Neural Networks %@Michiel Hermans,Benjamin Schrauwen %t2013 %cNIPS %f/NIPS/NIPS-2013-2638.pdf %*A simple example of Dirichlet process mixture inconsistency for the number of components %@Jeffrey W. Miller,Matthew T. Harrison %t2013 %cNIPS %f/NIPS/NIPS-2013-2639.pdf %*Variational Policy Search via Trajectory Optimization %@Sergey Levine,Vladlen Koltun %t2013 %cNIPS %f/NIPS/NIPS-2013-2640.pdf %*Scalable kernels for graphs with continuous attributes %@Aasa Feragen,Niklas Kasenburg,Jens Petersen,Marleen de Bruijne,Karsten Borgwardt %t2013 %cNIPS %f/NIPS/NIPS-2013-2641.pdf %*Density estimation from unweighted k-nearest neighbor graphs: a roadmap %@Ulrike Von Luxburg,Morteza Alamgir %t2013 %cNIPS %f/NIPS/NIPS-2013-2642.pdf %*Decision Jungles: Compact and Rich Models for Classification %@Jamie Shotton,Toby Sharp,Pushmeet Kohli,Sebastian Nowozin,John Winn,Antonio Criminisi %t2013 %cNIPS %f/NIPS/NIPS-2013-2643.pdf %*What Are the Invariant Occlusive Components of Image Patches? A Probabilistic Generative Approach %@Zhenwen Dai,Georgios Exarchakis,Jörg Lücke %t2013 %cNIPS %f/NIPS/NIPS-2013-2644.pdf %*Actor-Critic Algorithms for Risk-Sensitive MDPs %@Prashanth L.A.,Mohammad Ghavamzadeh %t2013 %cNIPS %f/NIPS/NIPS-2013-2645.pdf %*Summary Statistics for Partitionings and Feature Allocations %@Isik B. Fidaner,Taylan Cemgil %t2013 %cNIPS %f/NIPS/NIPS-2013-2646.pdf %*One-shot learning and big data with n=2 %@Lee H. Dicker,Dean P. Foster %t2013 %cNIPS %f/NIPS/NIPS-2013-2647.pdf %*Variational Inference for Mahalanobis Distance Metrics in Gaussian Process Regression %@Michalis Titsias,Miguel Lazaro-Gredilla %t2013 %cNIPS %f/NIPS/NIPS-2013-2648.pdf %*Correlations strike back (again): the case of associative memory retrieval %@Cristina Savin,Peter Dayan,Mate Lengyel %t2013 %cNIPS %f/NIPS/NIPS-2013-2649.pdf %*Optimal Neural Population Codes for High-dimensional Stimulus Variables %@Zhuo Wang,Alan Stocker,Daniel Lee %t2013 %cNIPS %f/NIPS/NIPS-2013-2650.pdf %*Online Variational Approximations to non-Exponential Family Change Point Models: With Application to Radar Tracking %@Ryan D. Turner,Steven Bottone,Clay J. Stanek %t2013 %cNIPS %f/NIPS/NIPS-2013-2651.pdf %*Accelerating Stochastic Gradient Descent using Predictive Variance Reduction %@Rie Johnson,Tong Zhang %t2013 %cNIPS %f/NIPS/NIPS-2013-2652.pdf %*Using multiple samples to learn mixture models %@Jason D. Lee,Ran Gilad-Bachrach,Rich Caruana %t2013 %cNIPS %f/NIPS/NIPS-2013-2653.pdf %*Learning Hidden Markov Models from Non-sequence Data via Tensor Decomposition %@Tzu-Kuo Huang,Jeff Schneider %t2013 %cNIPS %f/NIPS/NIPS-2013-2654.pdf %*On model selection consistency of penalized M-estimators: a geometric theory %@Jason D. Lee,Yuekai Sun,Jonathan E. Taylor %t2013 %cNIPS %f/NIPS/NIPS-2013-2655.pdf %*Dropout Training as Adaptive Regularization %@Stefan Wager,Sida Wang,Percy S. Liang %t2013 %cNIPS %f/NIPS/NIPS-2013-2656.pdf %*New Subsampling Algorithms for Fast Least Squares Regression %@Paramveer Dhillon,Yichao Lu,Dean P. Foster,Lyle Ungar %t2013 %cNIPS %f/NIPS/NIPS-2013-2657.pdf %*Faster Ridge Regression via the Subsampled Randomized Hadamard Transform %@Yichao Lu,Paramveer Dhillon,Dean P. Foster,Lyle Ungar %t2013 %cNIPS %f/NIPS/NIPS-2013-2658.pdf %*Accelerated Mini-Batch Stochastic Dual Coordinate Ascent %@Shai Shalev-Shwartz,Tong Zhang %t2013 %cNIPS %f/NIPS/NIPS-2013-2659.pdf %*Online Robust PCA via Stochastic Optimization %@Jiashi Feng,Huan Xu,Shuicheng Yan %t2013 %cNIPS %f/NIPS/NIPS-2013-2660.pdf %*Least Informative Dimensions %@Fabian Sinz,Anna Stockl,Jan Grewe,Jan Benda %t2013 %cNIPS %f/NIPS/NIPS-2013-2661.pdf %*A Scalable Approach to Probabilistic Latent Space Inference of Large-Scale Networks %@Junming Yin,Qirong Ho,Eric P. Xing %t2013 %cNIPS %f/NIPS/NIPS-2013-2662.pdf %*Understanding variable importances in forests of randomized trees %@Gilles Louppe,Louis Wehenkel,Antonio Sutera,Pierre Geurts %t2013 %cNIPS %f/NIPS/NIPS-2013-2663.pdf %*Correlated random features for fast semi-supervised learning %@Brian McWilliams,David Balduzzi,Joachim M. Buhmann %t2013 %cNIPS %f/NIPS/NIPS-2013-2664.pdf %*Dynamic Clustering via Asymptotics of the Dependent Dirichlet Process Mixture %@Trevor Campbell,Miao Liu,Brian Kulis,Jonathan P. How,Lawrence Carin %t2013 %cNIPS %f/NIPS/NIPS-2013-2665.pdf %*Rapid Distance-Based Outlier Detection via Sampling %@Mahito Sugiyama,Karsten Borgwardt %t2013 %cNIPS %f/NIPS/NIPS-2013-2666.pdf %*Regularized M-estimators with nonconvexity: Statistical and algorithmic theory for local optima %@Po-Ling Loh,Martin J. Wainwright %t2013 %cNIPS %f/NIPS/NIPS-2013-2667.pdf %*Non-Linear Domain Adaptation with Boosting %@Carlos J. Becker,Christos M. Christoudias,Pascal Fua %t2013 %cNIPS %f/NIPS/NIPS-2013-2668.pdf %*Mid-level Visual Element Discovery as Discriminative Mode Seeking %@Carl Doersch,Abhinav Gupta,Alexei A. Efros %t2013 %cNIPS %f/NIPS/NIPS-2013-2669.pdf %*q-OCSVM: A q-Quantile Estimator for High-Dimensional Distributions %@Assaf Glazer,Michael Lindenbaum,Shaul Markovitch %t2013 %cNIPS %f/NIPS/NIPS-2013-2670.pdf %*Auditing: Active Learning with Outcome-Dependent Query Costs %@Sivan Sabato,Anand D. Sarwate,Nati Srebro %t2013 %cNIPS %f/NIPS/NIPS-2013-2671.pdf %*A message-passing algorithm for multi-agent trajectory planning %@Jose Bento,Nate Derbinsky,Javier Alonso-Mora,Jonathan S. Yedidia %t2013 %cNIPS %f/NIPS/NIPS-2013-2672.pdf %*Learning Stochastic Feedforward Neural Networks %@Yichuan Tang,Ruslan R. Salakhutdinov %t2013 %cNIPS %f/NIPS/NIPS-2013-2673.pdf %*Inferring neural population dynamics from multiple partial recordings of the same neural circuit %@Srini Turaga,Lars Buesing,Adam M. Packer,Henry Dalgleish,Noah Pettit,Michael Hausser,Jakob Macke %t2013 %cNIPS %f/NIPS/NIPS-2013-2674.pdf %*Multi-Prediction Deep Boltzmann Machines %@Ian Goodfellow,Mehdi Mirza,Aaron Courville,Yoshua Bengio %t2013 %cNIPS %f/NIPS/NIPS-2013-2675.pdf %*Higher Order Priors for Joint Intrinsic Image, Objects, and Attributes Estimation %@Vibhav Vineet,Carsten Rother,Philip Torr %t2013 %cNIPS %f/NIPS/NIPS-2013-2676.pdf %*Blind Calibration in Compressed Sensing using Message Passing Algorithms %@Christophe Schulke,Francesco Caltagirone,Florent Krzakala,Lenka Zdeborova %t2013 %cNIPS %f/NIPS/NIPS-2013-2677.pdf %*Learning Trajectory Preferences for Manipulators via Iterative Improvement %@Ashesh Jain,Brian Wojcik,Thorsten Joachims,Ashutosh Saxena %t2013 %cNIPS %f/NIPS/NIPS-2013-2678.pdf %*Large Scale Distributed Sparse Precision Estimation %@Huahua Wang,Arindam Banerjee,Cho-Jui Hsieh,Pradeep K. Ravikumar,Inderjit S. Dhillon %t2013 %cNIPS %f/NIPS/NIPS-2013-2679.pdf %*Neural representation of action sequences: how far can a simple snippet-matching model take us? %@Cheston Tan,Jedediah M. Singer,Thomas Serre,David Sheinberg,Tomaso Poggio %t2013 %cNIPS %f/NIPS/NIPS-2013-2680.pdf %*On Algorithms for Sparse Multi-factor NMF %@Siwei Lyu,Xin Wang %t2013 %cNIPS %f/NIPS/NIPS-2013-2681.pdf %*Dirty Statistical Models %@Eunho Yang,Pradeep K. Ravikumar %t2013 %cNIPS %f/NIPS/NIPS-2013-2682.pdf %*Parallel Sampling of DP Mixture Models using Sub-Cluster Splits %@Jason Chang,John W. Fisher III %t2013 %cNIPS %f/NIPS/NIPS-2013-2683.pdf %*Prior-free and prior-dependent regret bounds for Thompson Sampling %@Sebastien Bubeck,Che-Yu Liu %t2013 %cNIPS %f/NIPS/NIPS-2013-2684.pdf %*Which Space Partitioning Tree to Use for Search? %@Parikshit Ram,Alexander Gray %t2013 %cNIPS %f/NIPS/NIPS-2013-2685.pdf %*Projecting Ising Model Parameters for Fast Mixing %@Justin Domke,Xianghang Liu %t2013 %cNIPS %f/NIPS/NIPS-2013-2686.pdf %*Mixed Optimization for Smooth Functions %@Mehrdad Mahdavi,Lijun Zhang,Rong Jin %t2013 %cNIPS %f/NIPS/NIPS-2013-2687.pdf %*Conditional Random Fields via Univariate Exponential Families %@Eunho Yang,Pradeep K. Ravikumar,Genevera I. Allen,Zhandong Liu %t2013 %cNIPS %f/NIPS/NIPS-2013-2688.pdf %*Stochastic blockmodel approximation of a graphon: Theory and consistent estimation %@Edo M. Airoldi,Thiago B. Costa,Stanley H. Chan %t2013 %cNIPS %f/NIPS/NIPS-2013-2689.pdf %*Reinforcement Learning in Robust Markov Decision Processes %@Shiau Hong Lim,Huan Xu,Shie Mannor %t2013 %cNIPS %f/NIPS/NIPS-2013-2690.pdf %*On the Linear Convergence of the Proximal Gradient Method for Trace Norm Regularization %@Ke Hou,Zirui Zhou,Anthony Man-Cho So,Zhi-Quan Luo %t2013 %cNIPS %f/NIPS/NIPS-2013-2691.pdf %*Recurrent networks of coupled Winner-Take-All oscillators for solving constraint satisfaction problems %@Hesham Mostafa,Lorenz. K. Mueller,Giacomo Indiveri %t2013 %cNIPS %f/NIPS/NIPS-2013-2692.pdf %*Latent Structured Active Learning %@Wenjie Luo,Alex Schwing,Raquel Urtasun %t2013 %cNIPS %f/NIPS/NIPS-2013-2693.pdf %*A Gang of Bandits %@Nicolò Cesa-Bianchi,Claudio Gentile,Giovanni Zappella %t2013 %cNIPS %f/NIPS/NIPS-2013-2694.pdf %*Learning Feature Selection Dependencies in Multi-task Learning %@Daniel Hernández-Lobato,José Miguel Hernández-Lobato %t2013 %cNIPS %f/NIPS/NIPS-2013-2695.pdf %*B-test: A Non-parametric, Low Variance Kernel Two-sample Test %@Wojciech Zaremba,Arthur Gretton,Matthew Blaschko %t2013 %cNIPS %f/NIPS/NIPS-2013-2696.pdf %*Online PCA for Contaminated Data %@Jiashi Feng,Huan Xu,Shie Mannor,Shuicheng Yan %t2013 %cNIPS %f/NIPS/NIPS-2013-2697.pdf %*Non-strongly-convex smooth stochastic approximation with convergence rate O(1/n) %@Francis Bach,Eric Moulines %t2013 %cNIPS %f/NIPS/NIPS-2013-2698.pdf %*Efficient Algorithm for Privately Releasing Smooth Queries %@Ziteng Wang,Kai Fan,Jiaqi Zhang,Liwei Wang %t2013 %cNIPS %f/NIPS/NIPS-2013-2699.pdf %*Beyond Pairwise: Provably Fast Algorithms for Approximate k-Way Similarity Search %@Anshumali Shrivastava,Ping Li %t2013 %cNIPS %f/NIPS/NIPS-2013-2700.pdf %*Unsupervised Spectral Learning of Finite State Transducers %@Raphael Bailly,Xavier Carreras,Ariadna Quattoni %t2013 %cNIPS %f/NIPS/NIPS-2013-2701.pdf %*Learning a Deep Compact Image Representation for Visual Tracking %@Naiyan Wang,Dit-Yan Yeung %t2013 %cNIPS %f/NIPS/NIPS-2013-2702.pdf %*Learning Multi-level Sparse Representations %@Ferran Diego Andilla,Fred A. Hamprecht %t2013 %cNIPS %f/NIPS/NIPS-2013-2703.pdf %*Robust Data-Driven Dynamic Programming %@Grani Adiwena Hanasusanto,Daniel Kuhn %t2013 %cNIPS %f/NIPS/NIPS-2013-2704.pdf %*Low-Rank Matrix and Tensor Completion via Adaptive Sampling %@Akshay Krishnamurthy,Aarti Singh %t2013 %cNIPS %f/NIPS/NIPS-2013-2705.pdf %*Probabilistic Low-Rank Matrix Completion with Adaptive Spectral Regularization Algorithms %@Adrien Todeschini,François Caron,Marie Chavent %t2013 %cNIPS %f/NIPS/NIPS-2013-2706.pdf %*Distributed Exploration in Multi-Armed Bandits %@Eshcar Hillel,Zohar S. Karnin,Tomer Koren,Ronny Lempel,Oren Somekh %t2013 %cNIPS %f/NIPS/NIPS-2013-2707.pdf %*Direct 0-1 Loss Minimization and Margin Maximization with Boosting %@Shaodan Zhai,Tian Xia,Ming Tan,Shaojun Wang %t2013 %cNIPS %f/NIPS/NIPS-2013-2708.pdf %*Regret based Robust Solutions for Uncertain Markov Decision Processes %@Asrar Ahmed,Pradeep Varakantham,Yossiri Adulyasak,Patrick Jaillet %t2013 %cNIPS %f/NIPS/NIPS-2013-2709.pdf %*Speeding up Permutation Testing in Neuroimaging %@Chris Hinrichs,Vamsi Ithapu,Qinyuan Sun,Sterling C. Johnson,Vikas Singh %t2013 %cNIPS %f/NIPS/NIPS-2013-2710.pdf %*Generalized Denoising Auto-Encoders as Generative Models %@Yoshua Bengio,Li Yao,Guillaume Alain,Pascal Vincent %t2013 %cNIPS %f/NIPS/NIPS-2013-2711.pdf %*Supervised Sparse Analysis and Synthesis Operators %@Pablo Sprechmann,Roee Litman,Tal Ben Yakar,Alexander M. Bronstein,Guillermo Sapiro %t2013 %cNIPS %f/NIPS/NIPS-2013-2712.pdf %*Low-rank matrix reconstruction and clustering via approximate message passing %@Ryosuke Matsushita,Toshiyuki Tanaka %t2013 %cNIPS %f/NIPS/NIPS-2013-2713.pdf %*Reasoning With Neural Tensor Networks for Knowledge Base Completion %@Richard Socher,Danqi Chen,Christopher D. Manning,Andrew Ng %t2013 %cNIPS %f/NIPS/NIPS-2013-2714.pdf %*Zero-Shot Learning Through Cross-Modal Transfer %@Richard Socher,Milind Ganjoo,Christopher D. Manning,Andrew Ng %t2013 %cNIPS %f/NIPS/NIPS-2013-2715.pdf %*Estimating LASSO Risk and Noise Level %@Mohsen Bayati,Murat A. Erdogdu,Andrea Montanari %t2013 %cNIPS %f/NIPS/NIPS-2013-2716.pdf %*Learning Adaptive Value of Information for Structured Prediction %@David J. Weiss,Ben Taskar %t2013 %cNIPS %f/NIPS/NIPS-2013-2717.pdf %*Efficient Online Inference for Bayesian Nonparametric Relational Models %@Dae Il Kim,Prem K. Gopalan,David Blei,Erik Sudderth %t2013 %cNIPS %f/NIPS/NIPS-2013-2718.pdf %*Approximate inference in latent Gaussian-Markov models from continuous time observations %@Botond Cseke,Manfred Opper,Guido Sanguinetti %t2013 %cNIPS %f/NIPS/NIPS-2013-2719.pdf %*Linear Convergence with Condition Number Independent Access of Full Gradients %@Lijun Zhang,Mehrdad Mahdavi,Rong Jin %t2013 %cNIPS %f/NIPS/NIPS-2013-2720.pdf %*When in Doubt, SWAP: High-Dimensional Sparse Recovery from Correlated Measurements %@Divyanshu Vats,Richard Baraniuk %t2013 %cNIPS %f/NIPS/NIPS-2013-2721.pdf %*Wavelets on Graphs via Deep Learning %@Raif Rustamov,Leonidas J. Guibas %t2013 %cNIPS %f/NIPS/NIPS-2013-2722.pdf %*Robust Spatial Filtering with Beta Divergence %@Wojciech Samek,Duncan Blythe,Klaus-Robert Müller,Motoaki Kawanabe %t2013 %cNIPS %f/NIPS/NIPS-2013-2723.pdf %*Convex Relaxations for Permutation Problems %@Fajwel Fogel,Rodolphe Jenatton,Francis Bach,Alexandre D'Aspremont %t2013 %cNIPS %f/NIPS/NIPS-2013-2724.pdf %*High-Dimensional Gaussian Process Bandits %@Josip Djolonga,Andreas Krause,Volkan Cevher %t2013 %cNIPS %f/NIPS/NIPS-2013-2725.pdf %*A memory frontier for complex synapses %@Subhaneil Lahiri,Surya Ganguli %t2013 %cNIPS %f/NIPS/NIPS-2013-2726.pdf %*Marginals-to-Models Reducibility %@Tim Roughgarden,Michael Kearns %t2013 %cNIPS %f/NIPS/NIPS-2013-2727.pdf %*First-order Decomposition Trees %@Nima Taghipour,Jesse Davis,Hendrik Blockeel %t2013 %cNIPS %f/NIPS/NIPS-2013-2728.pdf %*A Comparative Framework for Preconditioned Lasso Algorithms %@Fabian L. Wauthier,Nebojsa Jojic,Michael I. Jordan %t2013 %cNIPS %f/NIPS/NIPS-2013-2729.pdf %*Lasso Screening Rules via Dual Polytope Projection %@Jie Wang,Jiayu Zhou,Peter Wonka,Jieping Ye %t2013 %cNIPS %f/NIPS/NIPS-2013-2730.pdf %*Binary to Bushy: Bayesian Hierarchical Clustering with the Beta Coalescent %@Yuening Hu,Jordan L. Boyd-Graber,Hal Daume III,Z. Irene Ying %t2013 %cNIPS %f/NIPS/NIPS-2013-2731.pdf %*A Latent Source Model for Nonparametric Time Series Classification %@George H. Chen,Stanislav Nikolov,Devavrat Shah %t2013 %cNIPS %f/NIPS/NIPS-2013-2732.pdf %*Efficient Optimization for Sparse Gaussian Process Regression %@Yanshuai Cao,Marcus A. Brubaker,David J. Fleet,Aaron Hertzmann %t2013 %cNIPS %f/NIPS/NIPS-2013-2733.pdf %*Lexical and Hierarchical Topic Regression %@Viet-An Nguyen,Jordan L. Boyd-Graber,Philip Resnik %t2013 %cNIPS %f/NIPS/NIPS-2013-2734.pdf %*Stochastic Convex Optimization with Multiple Objectives %@Mehrdad Mahdavi,Tianbao Yang,Rong Jin %t2013 %cNIPS %f/NIPS/NIPS-2013-2735.pdf %*A Kernel Test for Three-Variable Interactions %@Dino Sejdinovic,Arthur Gretton,Wicher Bergsma %t2013 %cNIPS %f/NIPS/NIPS-2013-2736.pdf %*Memoized Online Variational Inference for Dirichlet Process Mixture Models %@Michael C. Hughes,Erik Sudderth %t2013 %cNIPS %f/NIPS/NIPS-2013-2737.pdf %*Designed Measurements for Vector Count Data %@Liming Wang,David E. Carlson,Miguel Rodrigues,David Wilcox,Robert Calderbank,Lawrence Carin %t2013 %cNIPS %f/NIPS/NIPS-2013-2738.pdf %*Online Learning with Switching Costs and Other Adaptive Adversaries %@Nicolò Cesa-Bianchi,Ofer Dekel,Ohad Shamir %t2013 %cNIPS %f/NIPS/NIPS-2013-2739.pdf %*Learning Prices for Repeated Auctions with Strategic Buyers %@Kareem Amin,Afshin Rostamizadeh,Umar Syed %t2013 %cNIPS %f/NIPS/NIPS-2013-2740.pdf %*Probabilistic Principal Geodesic Analysis %@Miaomiao Zhang,P.T. Fletcher %t2013 %cNIPS %f/NIPS/NIPS-2013-2741.pdf %*Confidence Intervals and Hypothesis Testing for High-Dimensional Statistical Models %@Adel Javanmard,Andrea Montanari %t2013 %cNIPS %f/NIPS/NIPS-2013-2742.pdf %*Learning with Noisy Labels %@Nagarajan Natarajan,Inderjit S. Dhillon,Pradeep K. Ravikumar,Ambuj Tewari %t2013 %cNIPS %f/NIPS/NIPS-2013-2743.pdf %*Tracking Time-varying Graphical Structure %@Erich Kummerfeld,David Danks %t2013 %cNIPS %f/NIPS/NIPS-2013-2744.pdf %*Factorized Asymptotic Bayesian Inference for Latent Feature Models %@Kohei Hayashi,Ryohei Fujimaki %t2013 %cNIPS %f/NIPS/NIPS-2013-2745.pdf %*More Effective Distributed ML via a Stale Synchronous Parallel Parameter Server %@Qirong Ho,James Cipar,Henggang Cui,Seunghak Lee,Jin Kyu Kim,Phillip B. Gibbons,Garth A. Gibson,Greg Ganger,Eric P. Xing %t2013 %cNIPS %f/NIPS/NIPS-2013-2746.pdf %*Bayesian Estimation of Latently-grouped Parameters in Undirected Graphical Models %@Jie Liu,David Page %t2013 %cNIPS %f/NIPS/NIPS-2013-2747.pdf %*Online Learning with Costly Features and Labels %@Navid Zolghadr,Gabor Bartok,Russell Greiner,András György,Csaba Szepesvari %t2013 %cNIPS %f/NIPS/NIPS-2013-2748.pdf %*Sparse nonnegative deconvolution for compressive calcium imaging: algorithms and phase transitions %@Eftychios A. Pnevmatikakis,Liam Paninski %t2013 %cNIPS %f/NIPS/NIPS-2013-2749.pdf %*A Novel Two-Step Method for Cross Language Representation Learning %@Min Xiao,Yuhong Guo %t2013 %cNIPS %f/NIPS/NIPS-2013-2750.pdf %*On Sampling from the Gibbs Distribution with Random Maximum A-Posteriori Perturbations %@Tamir Hazan,Subhransu Maji,Tommi Jaakkola %t2013 %cNIPS %f/NIPS/NIPS-2013-2751.pdf %*Graphical Models for Inference with Missing Data %@Karthika Mohan,Judea Pearl,Jin Tian %t2013 %cNIPS %f/NIPS/NIPS-2013-2752.pdf %*Reshaping Visual Datasets for Domain Adaptation %@Boqing Gong,Kristen Grauman,Fei Sha %t2013 %cNIPS %f/NIPS/NIPS-2013-2753.pdf %*Statistical Active Learning Algorithms %@Maria-Florina F. Balcan,Vitaly Feldman %t2013 %cNIPS %f/NIPS/NIPS-2013-2754.pdf %*Bayesian Inference and Online Experimental Design for Mapping Neural Microcircuits %@Ben Shababo,Brooks Paige,Ari Pakman,Liam Paninski %t2013 %cNIPS %f/NIPS/NIPS-2013-2755.pdf %*Reflection methods for user-friendly submodular optimization %@Stefanie Jegelka,Francis Bach,Suvrit Sra %t2013 %cNIPS %f/NIPS/NIPS-2013-2756.pdf %*Unsupervised Structure Learning of Stochastic And-Or Grammars %@Kewei Tu,Maria Pavlovskaia,Song-Chun Zhu %t2013 %cNIPS %f/NIPS/NIPS-2013-2757.pdf %*Convex Tensor Decomposition via Structured Schatten Norm Regularization %@Ryota Tomioka,Taiji Suzuki %t2013 %cNIPS %f/NIPS/NIPS-2013-2758.pdf %*Stochastic Ratio Matching of RBMs for Sparse High-Dimensional Inputs %@Yann Dauphin,Yoshua Bengio %t2013 %cNIPS %f/NIPS/NIPS-2013-2759.pdf %*Learning Chordal Markov Networks by Constraint Satisfaction %@Jukka Corander,Tomi Janhunen,Jussi Rintanen,Henrik Nyman,Johan Pensar %t2013 %cNIPS %f/NIPS/NIPS-2013-2760.pdf %*Parametric Task Learning %@Ichiro Takeuchi,Tatsuya Hongo,Masashi Sugiyama,Shinichi Nakajima %t2013 %cNIPS %f/NIPS/NIPS-2013-2761.pdf %*A Deep Architecture for Matching Short Texts %@Zhengdong Lu,Hang Li %t2013 %cNIPS %f/NIPS/NIPS-2013-2762.pdf %*Computing the Stationary Distribution Locally %@Christina E. Lee,Asuman Ozdaglar,Devavrat Shah %t2013 %cNIPS %f/NIPS/NIPS-2013-2763.pdf %*Nonparametric Multi-group Membership Model for Dynamic Networks %@Myunghwan Kim,Jure Leskovec %t2013 %cNIPS %f/NIPS/NIPS-2013-2764.pdf %*Adaptive Step-Size for Policy Gradient Methods %@Matteo Pirotta,Marcello Restelli,Luca Bascetta %t2013 %cNIPS %f/NIPS/NIPS-2013-2765.pdf %*Optimistic Concurrency Control for Distributed Unsupervised Learning %@Xinghao Pan,Joseph E. Gonzalez,Stefanie Jegelka,Tamara Broderick,Michael I. Jordan %t2013 %cNIPS %f/NIPS/NIPS-2013-2766.pdf %*Reservoir Boosting : Between Online and Offline Ensemble Learning %@Leonidas Lefakis,François Fleuret %t2013 %cNIPS %f/NIPS/NIPS-2013-2767.pdf %*Multiclass Total Variation Clustering %@Xavier Bresson,Thomas Laurent,David Uminsky,James von Brecht %t2013 %cNIPS %f/NIPS/NIPS-2013-2768.pdf %*Approximate Inference in Continuous Determinantal Processes %@Raja Hafiz Affandi,Emily Fox,Ben Taskar %t2013 %cNIPS %f/NIPS/NIPS-2013-2769.pdf %*Global Solver and Its Efficient Approximation for Variational Bayesian Low-rank Subspace Clustering %@Shinichi Nakajima,Akiko Takeda,S. Derin Babacan,Masashi Sugiyama,Ichiro Takeuchi %t2013 %cNIPS %f/NIPS/NIPS-2013-2770.pdf %*Thompson Sampling for 1-Dimensional Exponential Family Bandits %@Nathaniel Korda,Emilie Kaufmann,Remi Munos %t2013 %cNIPS %f/NIPS/NIPS-2013-2771.pdf %*Active Learning for Probabilistic Hypotheses Using the Maximum Gibbs Error Criterion %@Nguyen Viet Cuong,Wee Sun Lee,Nan Ye,Kian Ming A. Chai,Hai Leong Chieu %t2013 %cNIPS %f/NIPS/NIPS-2013-2772.pdf %*It is all in the noise: Efficient multi-task Gaussian process inference with structured residuals %@Barbara Rakitsch,Christoph Lippert,Karsten Borgwardt,Oliver Stegle %t2013 %cNIPS %f/NIPS/NIPS-2013-2773.pdf %*Convex Calibrated Surrogates for Low-Rank Loss Matrices with Applications to Subset Ranking Losses %@Harish G. Ramaswamy,Shivani Agarwal,Ambuj Tewari %t2013 %cNIPS %f/NIPS/NIPS-2013-2774.pdf %*Inverse Density as an Inverse Problem: the Fredholm Equation Approach %@Qichao Que,Mikhail Belkin %t2013 %cNIPS %f/NIPS/NIPS-2013-2775.pdf %*Adaptive Multi-Column Deep Neural Networks with Application to Robust Image Denoising %@Forest Agostinelli,Michael R. Anderson,Honglak Lee %t2013 %cNIPS %f/NIPS/NIPS-2013-2776.pdf %*EDML for Learning Parameters in Directed and Undirected Graphical Models %@Khaled S. Refaat,Arthur Choi,Adnan Darwiche %t2013 %cNIPS %f/NIPS/NIPS-2013-2777.pdf %*Similarity Component Analysis %@Soravit Changpinyo,Kuan Liu,Fei Sha %t2013 %cNIPS %f/NIPS/NIPS-2013-2778.pdf %*Approximate Bayesian Image Interpretation using Generative Probabilistic Graphics Programs %@Vikash Mansinghka,Tejas D. Kulkarni,Yura N. Perov,Josh Tenenbaum %t2013 %cNIPS %f/NIPS/NIPS-2013-2779.pdf %*Local Privacy and Minimax Bounds: Sharp Rates for Probability Estimation %@John Duchi,Martin J. Wainwright,Michael I. Jordan %t2013 %cNIPS %f/NIPS/NIPS-2013-2780.pdf %*Firing rate predictions in optimal balanced networks %@David G. Barrett,Sophie Denève,Christian K. Machens %t2013 %cNIPS %f/NIPS/NIPS-2013-2781.pdf %*Manifold-based Similarity Adaptation for Label Propagation %@Masayuki Karasuyama,Hiroshi Mamitsuka %t2013 %cNIPS %f/NIPS/NIPS-2013-2782.pdf %*Non-Uniform Camera Shake Removal Using a Spatially-Adaptive Sparse Penalty %@Haichao Zhang,David Wipf %t2013 %cNIPS %f/NIPS/NIPS-2013-2783.pdf %*Near-Optimal Entrywise Sampling for Data Matrices %@Dimitris Achlioptas,Zohar S. Karnin,Edo Liberty %t2013 %cNIPS %f/NIPS/NIPS-2013-2784.pdf %*Learning to Prune in Metric and Non-Metric Spaces %@Leonid Boytsov,Bilegsaikhan Naidan %t2013 %cNIPS %f/NIPS/NIPS-2013-2785.pdf %*Online learning in episodic Markovian decision processes by relative entropy policy search %@Alexander Zimin,Gergely Neu %t2013 %cNIPS %f/NIPS/NIPS-2013-2786.pdf %*Bayesian Hierarchical Community Discovery %@Charles Blundell,Yee Whye Teh %t2013 %cNIPS %f/NIPS/NIPS-2013-2787.pdf %*From Bandits to Experts: A Tale of Domination and Independence %@Noga Alon,Nicolò Cesa-Bianchi,Claudio Gentile,Yishay Mansour %t2013 %cNIPS %f/NIPS/NIPS-2013-2788.pdf %*Predictive PAC Learning and Process Decompositions %@Cosma Shalizi,Aryeh Kontorovich %t2013 %cNIPS %f/NIPS/NIPS-2013-2789.pdf %*Pass-efficient unsupervised feature selection %@Crystal Maung,Haim Schweitzer %t2013 %cNIPS %f/NIPS/NIPS-2013-2790.pdf %*Simultaneous Rectification and Alignment via Robust Recovery of Low-rank Tensors %@Xiaoqin Zhang,Di Wang,Zhengyuan Zhou,Yi Ma %t2013 %cNIPS %f/NIPS/NIPS-2013-2791.pdf %*Bayesian Mixture Modelling and Inference based Thompson Sampling in Monte-Carlo Tree Search %@Aijun Bai,Feng Wu,Xiaoping Chen %t2013 %cNIPS %f/NIPS/NIPS-2013-2792.pdf %*Solving inverse problem of Markov chain with partial observations %@Tetsuro Morimura,Takayuki Osogami,Tsuyoshi Ide %t2013 %cNIPS %f/NIPS/NIPS-2013-2793.pdf %*Locally Adaptive Bayesian Multivariate Time Series %@Daniele Durante,Bruno Scarpa,David B. Dunson %t2013 %cNIPS %f/NIPS/NIPS-2013-2794.pdf %*Mapping paradigm ontologies to and from the brain %@Yannick Schwartz,Bertrand Thirion,Gael Varoquaux %t2013 %cNIPS %f/NIPS/NIPS-2013-2795.pdf %*Noise-Enhanced Associative Memories %@Amin Karbasi,Amir Hesam Salavati,Amin Shokrollahi,Lav R. Varshney %t2013 %cNIPS %f/NIPS/NIPS-2013-2796.pdf %*Exact and Stable Recovery of Pairwise Interaction Tensors %@Shouyuan Chen,Michael R. Lyu,Irwin King,Zenglin Xu %t2013 %cNIPS %f/NIPS/NIPS-2013-2797.pdf %*Bayesian entropy estimation for binary spike train data using parametric prior knowledge %@Evan W. Archer,Il Memming Park,Jonathan W. Pillow %t2013 %cNIPS %f/NIPS/NIPS-2013-2798.pdf %*Perfect Associative Learning with Spike-Timing-Dependent Plasticity %@Christian Albers,Maren Westkott,Klaus Pawelzik %t2013 %cNIPS %f/NIPS/NIPS-2013-2799.pdf %*On Poisson Graphical Models %@Eunho Yang,Pradeep K. Ravikumar,Genevera I. Allen,Zhandong Liu %t2013 %cNIPS %f/NIPS/NIPS-2013-2800.pdf %*Streaming Variational Bayes %@Tamara Broderick,Nicholas Boyd,Andre Wibisono,Ashia C. Wilson,Michael I. Jordan %t2013 %cNIPS %f/NIPS/NIPS-2013-2801.pdf %*Gaussian Process Conditional Copulas with Applications to Financial Time Series %@José Miguel Hernández-Lobato,James R. Lloyd,Daniel Hernández-Lobato %t2013 %cNIPS %f/NIPS/NIPS-2013-2802.pdf %*Extracting regions of interest from biological images with convolutional sparse block coding %@Marius Pachitariu,Adam M. Packer,Noah Pettit,Henry Dalgleish,Michael Hausser,Maneesh Sahani %t2013 %cNIPS %f/NIPS/NIPS-2013-2803.pdf %*Approximate Dynamic Programming Finally Performs Well in the Game of Tetris %@Victor Gabillon,Mohammad Ghavamzadeh,Bruno Scherrer %t2013 %cNIPS %f/NIPS/NIPS-2013-2804.pdf %*Third-Order Edge Statistics: Contour Continuation, Curvature, and Cortical Connections %@Matthew Lawlor,Steven W. Zucker %t2013 %cNIPS %f/NIPS/NIPS-2013-2805.pdf %*DESPOT: Online POMDP Planning with Regularization %@Adhiraj Somani,Nan Ye,David Hsu,Wee Sun Lee %t2013 %cNIPS %f/NIPS/NIPS-2013-2806.pdf %*Matrix Completion From any Given Set of Observations %@Troy Lee,Adi Shraibman %t2013 %cNIPS %f/NIPS/NIPS-2013-2807.pdf %*Regression-tree Tuning in a Streaming Setting %@Samory Kpotufe,Francesco Orabona %t2013 %cNIPS %f/NIPS/NIPS-2013-2808.pdf %*Multiscale Dictionary Learning for Estimating Conditional Distributions %@Francesca Petralia,Joshua T. Vogelstein,David B. Dunson %t2013 %cNIPS %f/NIPS/NIPS-2013-2809.pdf %*Stochastic Optimization of PCA with Capped MSG %@Raman Arora,Andy Cotter,Nati Srebro %t2013 %cNIPS %f/NIPS/NIPS-2013-2810.pdf %*On Flat versus Hierarchical Classification in Large-Scale Taxonomies %@Rohit Babbar,Ioannis Partalas,Eric Gaussier,Massih-Reza Amini %t2013 %cNIPS %f/NIPS/NIPS-2013-2811.pdf %*Learning Gaussian Graphical Models with Observed or Latent FVSs %@Ying Liu,Alan Willsky %t2013 %cNIPS %f/NIPS/NIPS-2013-2812.pdf %*Visual Concept Learning: Combining Machine Vision and Bayesian Generalization on Concept Hierarchies %@Yangqing Jia,Joshua T. Abbott,Joseph Austerweil,Thomas Griffiths,Trevor Darrell %t2013 %cNIPS %f/NIPS/NIPS-2013-2813.pdf %*Robust Bloom Filters for Large MultiLabel Classification Tasks %@Moustapha M. Cisse,Nicolas Usunier,Thierry Artières,Patrick Gallinari %t2013 %cNIPS %f/NIPS/NIPS-2013-2814.pdf %*Solving the multi-way matching problem by permutation synchronization %@Deepti Pachauri,Risi Kondor,Vikas Singh %t2013 %cNIPS %f/NIPS/NIPS-2013-2815.pdf %*Generalizing Analytic Shrinkage for Arbitrary Covariance Structures %@Daniel Bartz,Klaus-Robert Müller %t2013 %cNIPS %f/NIPS/NIPS-2013-2816.pdf %*Top-Down Regularization of Deep Belief Networks %@Hanlin Goh,Nicolas Thome,Matthieu Cord,Joo-Hwee Lim %t2013 %cNIPS %f/NIPS/NIPS-2013-2817.pdf %*Learning Efficient Random Maximum A-Posteriori Predictors with Non-Decomposable Loss Functions %@Tamir Hazan,Subhransu Maji,Joseph Keshet,Tommi Jaakkola %t2013 %cNIPS %f/NIPS/NIPS-2013-2818.pdf %*Scoring Workers in Crowdsourcing: How Many Control Questions are Enough? %@Qiang Liu,Alexander T. Ihler,Mark Steyvers %t2013 %cNIPS %f/NIPS/NIPS-2013-2819.pdf %*Action from Still Image Dataset and Inverse Optimal Control to Learn Task Specific Visual Scanpaths %@Stefan Mathe,Cristian Sminchisescu %t2013 %cNIPS %f/NIPS/NIPS-2013-2820.pdf %*A Determinantal Point Process Latent Variable Model for Inhibition in Neural Spiking Data %@Jasper Snoek,Richard Zemel,Ryan P. Adams %t2013 %cNIPS %f/NIPS/NIPS-2013-2821.pdf %*Robust Sparse Principal Component Regression under the High Dimensional Elliptical Model %@Fang Han,Han Liu %t2013 %cNIPS %f/NIPS/NIPS-2013-2822.pdf %*Global MAP-Optimality by Shrinking the Combinatorial Search Area with Convex Relaxation %@Bogdan Savchynskyy,Jörg Hendrik Kappes,Paul Swoboda,Christoph Schnörr %t2013 %cNIPS %f/NIPS/NIPS-2013-2823.pdf %*Near-optimal Anomaly Detection in Graphs using Lovasz Extended Scan Statistic %@James L. Sharpnack,Akshay Krishnamurthy,Aarti Singh %t2013 %cNIPS %f/NIPS/NIPS-2013-2824.pdf %*Demixing odors - fast inference in olfaction %@Agnieszka Grabska-Barwinska,Jeff Beck,Alexandre Pouget,Peter Latham %t2013 %cNIPS %f/NIPS/NIPS-2013-2825.pdf %*Learning Multiple Models via Regularized Weighting %@Daniel Vainsencher,Shie Mannor,Huan Xu %t2013 %cNIPS %f/NIPS/NIPS-2013-2826.pdf %*When are Overcomplete Topic Models Identifiable? Uniqueness of Tensor Tucker Decompositions with Structured Sparsity %@Anima Anandkumar,Daniel J. Hsu,Majid Janzamin,Sham M. Kakade %t2013 %cNIPS %f/NIPS/NIPS-2013-2827.pdf %*Distributed k-means and k-median Clustering on General Topologies %@Maria-Florina F. Balcan,Steven Ehrlich,Yingyu Liang %t2013 %cNIPS %f/NIPS/NIPS-2013-2828.pdf %*Multi-Task Bayesian Optimization %@Kevin Swersky,Jasper Snoek,Ryan P. Adams %t2013 %cNIPS %f/NIPS/NIPS-2013-2829.pdf %*Online Learning of Dynamic Parameters in Social Networks %@Shahin Shahrampour,Sasha Rakhlin,Ali Jadbabaie %t2013 %cNIPS %f/NIPS/NIPS-2013-2830.pdf %*A Graphical Transformation for Belief Propagation: Maximum Weight Matchings and Odd-Sized Cycles %@Jinwoo Shin,Andrew E. Gelfand,Misha Chertkov %t2013 %cNIPS %f/NIPS/NIPS-2013-2831.pdf %*Learning with Invariance via Linear Functionals on Reproducing Kernel Hilbert Space %@Xinhua Zhang,Wee Sun Lee,Yee Whye Teh %t2013 %cNIPS %f/NIPS/NIPS-2013-2832.pdf %*Approximate Gaussian process inference for the drift function in stochastic differential equations %@Andreas Ruttor,Philipp Batz,Manfred Opper %t2013 %cNIPS %f/NIPS/NIPS-2013-2833.pdf %*Distributed Submodular Maximization: Identifying Representative Elements in Massive Data %@Baharan Mirzasoleiman,Amin Karbasi,Rik Sarkar,Andreas Krause %t2013 %cNIPS %f/NIPS/NIPS-2013-2834.pdf %*Adaptive Market Making via Online Learning %@Jacob Abernethy,Satyen Kale %t2013 %cNIPS %f/NIPS/NIPS-2013-2835.pdf %*On the Sample Complexity of Subspace Learning %@Alessandro Rudi,Guillermo D. Canas,Lorenzo Rosasco %t2013 %cNIPS %f/NIPS/NIPS-2013-2836.pdf %*Spike train entropy-rate estimation using hierarchical Dirichlet process priors %@Karin C. Knudson,Jonathan W. Pillow %t2013 %cNIPS %f/NIPS/NIPS-2013-2837.pdf %*Embed and Project: Discrete Sampling with Universal Hashing %@Stefano Ermon,Carla P. Gomes,Ashish Sabharwal,Bart Selman %t2013 %cNIPS %f/NIPS/NIPS-2013-2838.pdf %*Discriminative Transfer Learning with Tree-based Priors %@Nitish Srivastava,Ruslan R. Salakhutdinov %t2013 %cNIPS %f/NIPS/NIPS-2013-2839.pdf %*Small-Variance Asymptotics for Hidden Markov Models %@Anirban Roychowdhury,Ke Jiang,Brian Kulis %t2013 %cNIPS %f/NIPS/NIPS-2013-2840.pdf %*Convergence of Monte Carlo Tree Search in Simultaneous Move Games %@Viliam Lisy,Vojta Kovarik,Marc Lanctot,Branislav Bosansky %t2013 %cNIPS %f/NIPS/NIPS-2013-2841.pdf %*DeViSE: A Deep Visual-Semantic Embedding Model %@Andrea Frome,Greg S. Corrado,Jon Shlens,Samy Bengio,Jeff Dean,Marc'Aurelio Ranzato,Tomas Mikolov %t2013 %cNIPS %f/NIPS/NIPS-2013-2842.pdf %*Reward Mapping for Transfer in Long-Lived Agents %@Xiaoxiao Guo,Satinder Singh,Richard L. Lewis %t2013 %cNIPS %f/NIPS/NIPS-2013-2843.pdf %*Minimax Theory for High-dimensional Gaussian Mixtures with Sparse Mean Separation %@Martin Azizyan,Aarti Singh,Larry Wasserman %t2013 %cNIPS %f/NIPS/NIPS-2013-2844.pdf %*Predicting Parameters in Deep Learning %@Misha Denil,Babak Shakibi,Laurent Dinh,Marc'Aurelio Ranzato,Nando de Freitas %t2013 %cNIPS %f/NIPS/NIPS-2013-2845.pdf %*Estimating the Unseen: Improved Estimators for Entropy and other Properties %@Paul Valiant,Gregory Valiant %t2013 %cNIPS %f/NIPS/NIPS-2013-2846.pdf %*What do row and column marginals reveal about your dataset? %@Behzad Golshan,John Byers,Evimaria Terzi %t2013 %cNIPS %f/NIPS/NIPS-2013-2847.pdf %*RNADE: The real-valued neural autoregressive density-estimator %@Benigno Uria,Iain Murray,Hugo Larochelle %t2013 %cNIPS %f/NIPS/NIPS-2013-2848.pdf %*Two-Target Algorithms for Infinite-Armed Bandits with Bernoulli Rewards %@Thomas Bonald,Alexandre Proutiere %t2013 %cNIPS %f/NIPS/NIPS-2013-2849.pdf %*Reconciling "priors" & "priors" without prejudice? %@Remi Gribonval,Pierre Machart %t2013 %cNIPS %f/NIPS/NIPS-2013-2850.pdf %*Sparse Overlapping Sets Lasso for Multitask Learning and its Application to fMRI Analysis %@Nikhil Rao,Christopher Cox,Rob Nowak,Timothy T. Rogers %t2013 %cNIPS %f/NIPS/NIPS-2013-2851.pdf %*Sensor Selection in High-Dimensional Gaussian Trees with Nuisances %@Daniel S. Levine,Jonathan P. How %t2013 %cNIPS %f/NIPS/NIPS-2013-2852.pdf %*Sequential Transfer in Multi-armed Bandit with Finite Set of Models %@Mohammad Gheshlaghi azar,Alessandro Lazaric,Emma Brunskill %t2013 %cNIPS %f/NIPS/NIPS-2013-2853.pdf %*Buy-in-Bulk Active Learning %@Liu Yang,Jaime Carbonell %t2013 %cNIPS %f/NIPS/NIPS-2013-2854.pdf %*Contrastive Learning Using Spectral Methods %@James Y. Zou,Daniel J. Hsu,David C. Parkes,Ryan P. Adams %t2013 %cNIPS %f/NIPS/NIPS-2013-2855.pdf %*Message Passing Inference with Chemical Reaction Networks %@Nils E. Napp,Ryan P. Adams %t2013 %cNIPS %f/NIPS/NIPS-2013-2856.pdf %*Eluder Dimension and the Sample Complexity of Optimistic Exploration %@Dan Russo,Benjamin Van Roy %t2013 %cNIPS %f/NIPS/NIPS-2013-2857.pdf %*Learning word embeddings efficiently with noise-contrastive estimation %@Andriy Mnih,Koray Kavukcuoglu %t2013 %cNIPS %f/NIPS/NIPS-2013-2858.pdf %*Sparse Inverse Covariance Estimation with Calibration %@Tuo Zhao,Han Liu %t2013 %cNIPS %f/NIPS/NIPS-2013-2859.pdf %*Speedup Matrix Completion with Side Information: Application to Multi-Label Learning %@Miao Xu,Rong Jin,Zhi-Hua Zhou %t2013 %cNIPS %f/NIPS/NIPS-2013-2860.pdf %*Compete to Compute %@Rupesh K. Srivastava,Jonathan Masci,Sohrob Kazerounian,Faustino Gomez,Juergen Schmidhuber %t2013 %cNIPS %f/NIPS/NIPS-2013-2861.pdf %*Information-theoretic lower bounds for distributed statistical estimation with communication constraints %@Yuchen Zhang,John Duchi,Michael I. Jordan,Martin J. Wainwright %t2013 %cNIPS %f/NIPS/NIPS-2013-2862.pdf %*Projected Natural Actor-Critic %@Philip S. Thomas,William C. Dabney,Stephen Giguere,Sridhar Mahadevan %t2013 %cNIPS %f/NIPS/NIPS-2013-2863.pdf %*How to Hedge an Option Against an Adversary: Black-Scholes Pricing is Minimax Optimal %@Jacob Abernethy,Peter L. Bartlett,Rafael Frongillo,Andre Wibisono %t2013 %cNIPS %f/NIPS/NIPS-2013-2864.pdf %*Discovering Hidden Variables in Noisy-Or Networks using Quartet Tests %@Yacine Jernite,Yonatan Halpern,David Sontag %t2013 %cNIPS %f/NIPS/NIPS-2013-2865.pdf %*Error-Minimizing Estimates and Universal Entry-Wise Error Bounds for Low-Rank Matrix Completion %@Franz Kiraly,Louis Theran %t2013 %cNIPS %f/NIPS/NIPS-2013-2866.pdf %*Learning the Local Statistics of Optical Flow %@Dan Rosenbaum,Daniel Zoran,Yair Weiss %t2013 %cNIPS %f/NIPS/NIPS-2013-2867.pdf %*Aggregating Optimistic Planning Trees for Solving Markov Decision Processes %@Gunnar Kedenburg,Raphael Fonteneau,Remi Munos %t2013 %cNIPS %f/NIPS/NIPS-2013-2868.pdf %*Robust learning of low-dimensional dynamics from large neural ensembles %@David Pfau,Eftychios A. Pnevmatikakis,Liam Paninski %t2013 %cNIPS %f/NIPS/NIPS-2013-2869.pdf %*Estimation Bias in Multi-Armed Bandit Algorithms for Search Advertising %@Min Xu,Tao Qin,Tie-Yan Liu %t2013 %cNIPS %f/NIPS/NIPS-2013-2870.pdf %*Action is in the Eye of the Beholder: Eye-gaze Driven Model for Spatio-Temporal Action Localization %@Nataliya Shapovalova,Michalis Raptis,Leonid Sigal,Greg Mori %t2013 %cNIPS %f/NIPS/NIPS-2013-2871.pdf %*A* Lasso for Learning a Sparse Bayesian Network Structure for Continuous Variables %@Jing Xiang,Seyoung Kim %t2013 %cNIPS %f/NIPS/NIPS-2013-2872.pdf %*The Total Variation on Hypergraphs - Learning on Hypergraphs Revisited %@Matthias Hein,Simon Setzer,Leonardo Jost,Syama Sundar Rangapuram %t2013 %cNIPS %f/NIPS/NIPS-2013-2873.pdf %*Submodular Optimization with Submodular Cover and Submodular Knapsack Constraints %@Rishabh K. Iyer,Jeff A. Bilmes %t2013 %cNIPS %f/NIPS/NIPS-2013-2874.pdf %*Scalable Inference for Logistic-Normal Topic Models %@Jianfei Chen,Jun Zhu,Zi Wang,Xun Zheng,Bo Zhang %t2013 %cNIPS %f/NIPS/NIPS-2013-2875.pdf %*Spectral methods for neural characterization using generalized quadratic models %@Il Memming Park,Evan W. Archer,Nicholas Priebe,Jonathan W. Pillow %t2013 %cNIPS %f/NIPS/NIPS-2013-2876.pdf %*Universal models for binary spike patterns using centered Dirichlet processes %@Il Memming Park,Evan W. Archer,Kenneth Latimer,Jonathan W. Pillow %t2013 %cNIPS %f/NIPS/NIPS-2013-2877.pdf %*Synthesizing Robust Plans under Incomplete Domain Models %@Tuan A. Nguyen,Subbarao Kambhampati,Minh Do %t2013 %cNIPS %f/NIPS/NIPS-2013-2878.pdf %*Integrated Non-Factorized Variational Inference %@Shaobo Han,Xuejun Liao,Lawrence Carin %t2013 %cNIPS %f/NIPS/NIPS-2013-2879.pdf %*Auxiliary-variable Exact Hamiltonian Monte Carlo Samplers for Binary Distributions %@Ari Pakman,Liam Paninski %t2013 %cNIPS %f/NIPS/NIPS-2013-2880.pdf %*Symbolic Opportunistic Policy Iteration for Factored-Action MDPs %@Aswin Raghavan,Roni Khardon,Alan Fern,Prasad Tadepalli %t2013 %cNIPS %f/NIPS/NIPS-2013-2881.pdf %*Online Learning in Markov Decision Processes with Adversarially Chosen Transition Probability Distributions %@Yasin Abbasi,Peter L. Bartlett,Varun Kanade,Yevgeny Seldin,Csaba Szepesvari %t2013 %cNIPS %f/NIPS/NIPS-2013-2882.pdf %*Flexible sampling of discrete data correlations without the marginal distributions %@Alfredo Kalaitzis,Ricardo Silva %t2013 %cNIPS %f/NIPS/NIPS-2013-2883.pdf %*One-shot learning by inverting a compositional causal process %@Brenden M. Lake,Ruslan R. Salakhutdinov,Josh Tenenbaum %t2013 %cNIPS %f/NIPS/NIPS-2013-2884.pdf %*Statistical analysis of coupled time series with Kernel Cross-Spectral Density operators. %@Michel Besserve,Nikos K. Logothetis,Bernhard Schölkopf %t2013 %cNIPS %f/NIPS/NIPS-2013-2885.pdf %*Fast Algorithms for Gaussian Noise Invariant Independent Component Analysis %@James R. Voss,Luis Rademacher,Mikhail Belkin %t2013 %cNIPS %f/NIPS/NIPS-2013-2886.pdf %*Deep Neural Networks for Object Detection %@Christian Szegedy,Alexander Toshev,Dumitru Erhan %t2013 %cNIPS %f/NIPS/NIPS-2013-2887.pdf %*Geometric optimisation on positive definite matrices for elliptically contoured distributions %@Suvrit Sra,Reshad Hosseini %t2013 %cNIPS %f/NIPS/NIPS-2013-2888.pdf %*Sign Cauchy Projections and Chi-Square Kernel %@Ping Li,Gennady Samorodnitsk,John Hopcroft %t2013 %cNIPS %f/NIPS/NIPS-2013-2889.pdf %*Relevance Topic Model for Unstructured Social Group Activity Recognition %@Fang Zhao,Yongzhen Huang,Liang Wang,Tieniu Tan %t2013 %cNIPS %f/NIPS/NIPS-2013-2890.pdf %*k-Prototype Learning for 3D Rigid Structures %@Hu Ding,Ronald Berezney,Jinhui Xu %t2013 %cNIPS %f/NIPS/NIPS-2013-2891.pdf %*Restricting exchangeable nonparametric distributions %@Sinead A. Williamson,Steve N. MacEachern,Eric P. Xing %t2013 %cNIPS %f/NIPS/NIPS-2013-2892.pdf %*Forgetful Bayes and myopic planning: Human learning and decision-making in a bandit setting %@Shunan Zhang,Angela J. Yu %t2013 %cNIPS %f/NIPS/NIPS-2013-2893.pdf %*Probabilistic Movement Primitives %@Alexandros Paraschos,Christian Daniel,Jan R. Peters,Gerhard Neumann %t2013 %cNIPS %f/NIPS/NIPS-2013-2894.pdf %*Policy Shaping: Integrating Human Feedback with Reinforcement Learning %@Shane Griffith,Kaushik Subramanian,Jonathan Scholz,Charles Isbell,Andrea L. Thomaz %t2013 %cNIPS %f/NIPS/NIPS-2013-2895.pdf %*Multilinear Dynamical Systems for Tensor Time Series %@Mark Rogers,Lei Li,Stuart J. Russell %t2013 %cNIPS %f/NIPS/NIPS-2013-2896.pdf %*Deep content-based music recommendation %@Aaron van den Oord,Sander Dieleman,Benjamin Schrauwen %t2013 %cNIPS %f/NIPS/NIPS-2013-2897.pdf %*A Stability-based Validation Procedure for Differentially Private Machine Learning %@Kamalika Chaudhuri,Staal A. Vinterbo %t2013 %cNIPS %f/NIPS/NIPS-2013-2898.pdf %*Fantope Projection and Selection: A near-optimal convex relaxation of sparse PCA %@Vincent Q. Vu,Juhee Cho,Jing Lei,Karl Rohe %t2013 %cNIPS %f/NIPS/NIPS-2013-2899.pdf %*Cluster Trees on Manifolds %@Sivaraman Balakrishnan,Srivatsan Narayanan,Alessandro Rinaldo,Aarti Singh,Larry Wasserman %t2013 %cNIPS %f/NIPS/NIPS-2013-2900.pdf %*Bayesian inference for low rank spatiotemporal neural receptive fields %@Mijung Park,Jonathan W. Pillow %t2013 %cNIPS %f/NIPS/NIPS-2013-2901.pdf %*Adaptive Submodular Maximization in Bandit Setting %@Victor Gabillon,Branislav Kveton,Zheng Wen,Brian Eriksson,S. Muthukrishnan %t2013 %cNIPS %f/NIPS/NIPS-2013-2902.pdf %*Generalized Method-of-Moments for Rank Aggregation %@Hossein Azari Soufiani,William Chen,David C. Parkes,Lirong Xia %t2013 %cNIPS %f/NIPS/NIPS-2013-2903.pdf %*Analyzing Hogwild Parallel Gaussian Gibbs Sampling %@Matthew Johnson,James Saunderson,Alan Willsky %t2013 %cNIPS %f/NIPS/NIPS-2013-2904.pdf %*Minimax Optimal Algorithms for Unconstrained Linear Optimization %@Brendan McMahan,Jacob Abernethy %t2013 %cNIPS %f/NIPS/NIPS-2013-2905.pdf %*(Nearly) Optimal Algorithms for Private Online Learning in Full-information and Bandit Settings %@Abhradeep Guha Thakurta,Adam Smith %t2013 %cNIPS %f/NIPS/NIPS-2013-2906.pdf %*Curvature and Optimal Algorithms for Learning and Minimizing Submodular Functions %@Rishabh K. Iyer,Stefanie Jegelka,Jeff A. Bilmes %t2013 %cNIPS %f/NIPS/NIPS-2013-2907.pdf %*Σ-Optimality for Active Learning on Gaussian Random Fields %@Yifei Ma,Roman Garnett,Jeff Schneider %t2013 %cNIPS %f/NIPS/NIPS-2013-2908.pdf %*Learning Kernels Using Local Rademacher Complexity %@Corinna Cortes,Marius Kloft,Mehryar Mohri %t2013 %cNIPS %f/NIPS/NIPS-2013-2909.pdf %*Annealing between distributions by averaging moments %@Roger B. Grosse,Chris J. Maddison,Ruslan R. Salakhutdinov %t2013 %cNIPS %f/NIPS/NIPS-2013-2910.pdf %*Optimizing Instructional Policies %@Robert V. Lindsey,Michael C. Mozer,William J. Huggins,Harold Pashler %t2013 %cNIPS %f/NIPS/NIPS-2013-2911.pdf %*Translating Embeddings for Modeling Multi-relational Data %@Antoine Bordes,Nicolas Usunier,Alberto Garcia-Duran,Jason Weston,Oksana Yakhnenko %t2013 %cNIPS %f/NIPS/NIPS-2013-2912.pdf %*Phase Retrieval using Alternating Minimization %@Praneeth Netrapalli,Prateek Jain,Sujay Sanghavi %t2013 %cNIPS %f/NIPS/NIPS-2013-2913.pdf %*Real-Time Inference for a Gamma Process Model of Neural Spiking %@David E. Carlson,Vinayak Rao,Joshua T. Vogelstein,Lawrence Carin %t2013 %cNIPS %f/NIPS/NIPS-2013-2914.pdf %*Understanding Dropout %@Pierre Baldi,Peter J. Sadowski %t2013 %cNIPS %f/NIPS/NIPS-2013-2915.pdf %*The Power of Asymmetry in Binary Hashing %@Behnam Neyshabur,Nati Srebro,Ruslan R. Salakhutdinov,Yury Makarychev,Payman Yadollahpour %t2013 %cNIPS %f/NIPS/NIPS-2013-2916.pdf %*Estimation, Optimization, and Parallelism when Data is Sparse %@John Duchi,Michael I. Jordan,Brendan McMahan %t2013 %cNIPS %f/NIPS/NIPS-2013-2917.pdf %*A multi-agent control framework for co-adaptation in brain-computer interfaces %@Josh S. Merel,Roy Fox,Tony Jebara,Liam Paninski %t2013 %cNIPS %f/NIPS/NIPS-2013-2918.pdf %*Modeling Overlapping Communities with Node Popularities %@Prem K. Gopalan,Chong Wang,David Blei %t2013 %cNIPS %f/NIPS/NIPS-2013-2919.pdf %*Learning from Limited Demonstrations %@Beomjoon Kim,Amir massoud Farahmand,Joelle Pineau,Doina Precup %t2013 %cNIPS %f/NIPS/NIPS-2013-2920.pdf %*On the Complexity and Approximation of Binary Evidence in Lifted Inference %@Guy Van den Broeck,Adnan Darwiche %t2013 %cNIPS %f/NIPS/NIPS-2013-2921.pdf %*On the Representational Efficiency of Restricted Boltzmann Machines %@James Martens,Arkadev Chattopadhya,Toni Pitassi,Richard Zemel %t2013 %cNIPS %f/NIPS/NIPS-2013-2922.pdf %*Memory Limited, Streaming PCA %@Ioannis Mitliagkas,Constantine Caramanis,Prateek Jain %t2013 %cNIPS %f/NIPS/NIPS-2013-2923.pdf %*An Approximate, Efficient LP Solver for LP Rounding %@Srikrishna Sridhar,Stephen Wright,Christopher Re,Ji Liu,Victor Bittorf,Ce Zhang %t2013 %cNIPS %f/NIPS/NIPS-2013-2924.pdf %*On the Relationship Between Binary Classification, Bipartite Ranking, and Binary Class Probability Estimation %@Harikrishna Narasimhan,Shivani Agarwal %t2013 %cNIPS %f/NIPS/NIPS-2013-2925.pdf %*Bayesian inference as iterated random functions with applications to sequential inference in graphical models %@Arash Amini,Long Nguyen %t2013 %cNIPS %f/NIPS/NIPS-2013-2926.pdf %*Compressive Feature Learning %@Hristo S. Paskov,Robert West,John C. Mitchell,Trevor Hastie %t2013 %cNIPS %f/NIPS/NIPS-2013-2927.pdf %*Moment-based Uniform Deviation Bounds for k-means and Friends %@Matus J. Telgarsky,Sanjoy Dasgupta %t2013 %cNIPS %f/NIPS/NIPS-2013-2928.pdf %*Fast Template Evaluation with Vector Quantization %@Mohammad Amin Sadeghi,David Forsyth %t2013 %cNIPS %f/NIPS/NIPS-2013-2929.pdf %*Context-sensitive active sensing in humans %@Sheeraz Ahmad,He Huang,Angela J. Yu %t2013 %cNIPS %f/NIPS/NIPS-2013-2930.pdf %*A New Convex Relaxation for Tensor Completion %@Bernardino Romera-Paredes,Massimiliano Pontil %t2013 %cNIPS %f/NIPS/NIPS-2013-2931.pdf %*Variational Planning for Graph-based MDPs %@Qiang Cheng,Qiang Liu,Feng Chen,Alexander T. Ihler %t2013 %cNIPS %f/NIPS/NIPS-2013-2932.pdf %*Convex Two-Layer Modeling %@Özlem Aslan,Hao Cheng,Xinhua Zhang,Dale Schuurmans %t2013 %cNIPS %f/NIPS/NIPS-2013-2933.pdf %*Sketching Structured Matrices for Faster Nonlinear Regression %@Haim Avron,Vikas Sindhwani,David Woodruff %t2013 %cNIPS %f/NIPS/NIPS-2013-2934.pdf %*(More) Efficient Reinforcement Learning via Posterior Sampling %@Ian Osband,Dan Russo,Benjamin Van Roy %t2013 %cNIPS %f/NIPS/NIPS-2013-2935.pdf %*Model Selection for High-Dimensional Regression under the Generalized Irrepresentability Condition %@Adel Javanmard,Andrea Montanari %t2013 %cNIPS %f/NIPS/NIPS-2013-2936.pdf %*Efficient Exploration and Value Function Generalization in Deterministic Systems %@Zheng Wen,Benjamin Van Roy %t2013 %cNIPS %f/NIPS/NIPS-2013-2937.pdf %*Bellman Error Based Feature Generation using Random Projections on Sparse Spaces %@Mahdi Milani Fard,Yuri Grinberg,Amir massoud Farahmand,Joelle Pineau,Doina Precup %t2013 %cNIPS %f/NIPS/NIPS-2013-2938.pdf %*Learning and using language via recursive pragmatic reasoning about other agents %@Nathaniel J. Smith,Noah Goodman,Michael Frank %t2013 %cNIPS %f/NIPS/NIPS-2013-2939.pdf %*Learning Stochastic Inverses %@Andreas Stuhlmüller,Jacob Taylor,Noah Goodman %t2013 %cNIPS %f/NIPS/NIPS-2013-2940.pdf %*Learning invariant representations and applications to face verification %@Qianli Liao,Joel Z. Leibo,Tomaso Poggio %t2013 %cNIPS %f/NIPS/NIPS-2013-2941.pdf %*Optimization, Learning, and Games with Predictable Sequences %@Sasha Rakhlin,Karthik Sridharan %t2013 %cNIPS %f/NIPS/NIPS-2013-2942.pdf %*Adaptivity to Local Smoothness and Dimension in Kernel Regression %@Samory Kpotufe,Vikas Garg %t2013 %cNIPS %f/NIPS/NIPS-2013-2943.pdf %*Adaptive dropout for training deep neural networks %@Jimmy Ba,Brendan Frey %t2013 %cNIPS %f/NIPS/NIPS-2013-2944.pdf %*Hierarchical Modular Optimization of Convolutional Networks Achieves Representations Similar to Macaque IT and Human Ventral Stream %@Daniel L. Yamins,Ha Hong,Charles Cadieu,James J. DiCarlo %t2013 %cNIPS %f/NIPS/NIPS-2013-2945.pdf %*Stochastic Gradient Riemannian Langevin Dynamics on the Probability Simplex %@Sam Patterson,Yee Whye Teh %t2013 %cNIPS %f/NIPS/NIPS-2013-2946.pdf %*Distributed Representations of Words and Phrases and their Compositionality %@Tomas Mikolov,Ilya Sutskever,Kai Chen,Greg S. Corrado,Jeff Dean %t2013 %cNIPS %f/NIPS/NIPS-2013-2947.pdf %*Regularized Spectral Clustering under the Degree-Corrected Stochastic Blockmodel %@Tai Qin,Karl Rohe %t2013 %cNIPS %f/NIPS/NIPS-2013-2948.pdf %*Analyzing the Harmonic Structure in Graph-Based Learning %@Xiao-Ming Wu,Zhenguo Li,Shih-Fu Chang %t2013 %cNIPS %f/NIPS/NIPS-2013-2949.pdf %*Recurrent linear models of simultaneously-recorded neural populations %@Marius Pachitariu,Biljana Petreska,Maneesh Sahani %t2013 %cNIPS %f/NIPS/NIPS-2013-2950.pdf %*Scalable Influence Estimation in Continuous-Time Diffusion Networks %@Nan Du,Le Song,Manuel Gomez-Rodriguez,Hongyuan Zha %t2013 %cNIPS %f/NIPS/NIPS-2013-2951.pdf %*Bayesian Inference and Learning in Gaussian Process State-Space Models with Particle MCMC %@Roger Frigola,Fredrik Lindsten,Thomas B. Schön,Carl Rasmussen %t2013 %cNIPS %f/NIPS/NIPS-2013-2952.pdf %*BIG & QUIC: Sparse Inverse Covariance Estimation for a Million Variables %@Cho-Jui Hsieh,Matyas A. Sustik,Inderjit S. Dhillon,Pradeep K. Ravikumar,Russell Poldrack %t2013 %cNIPS %f/NIPS/NIPS-2013-2953.pdf %*The Fast Convergence of Incremental PCA %@Akshay Balsubramani,Sanjoy Dasgupta,Yoav Freund %t2013 %cNIPS %f/NIPS/NIPS-2013-2954.pdf %*Multisensory Encoding, Decoding, and Identification %@Aurel A. Lazar,Yevgeniy Slutskiy %t2013 %cNIPS %f/NIPS/NIPS-2013-2955.pdf %*Adaptive Anonymity via b-Matching %@Krzysztof M. Choromanski,Tony Jebara,Kui Tang %t2013 %cNIPS %f/NIPS/NIPS-2013-2956.pdf %*Optimal integration of visual speed across different spatiotemporal frequency channels %@Matjaz Jogan,Alan Stocker %t2013 %cNIPS %f/NIPS/NIPS-2013-2957.pdf %*Matrix factorization with binary components %@Martin Slawski,Matthias Hein,Pavlo Lutsik %t2013 %cNIPS %f/NIPS/NIPS-2013-2958.pdf %*Learning to Pass Expectation Propagation Messages %@Nicolas Heess,Daniel Tarlow,John Winn %t2013 %cNIPS %f/NIPS/NIPS-2013-2959.pdf %*Robust Low Rank Kernel Embeddings of Multivariate Distributions %@Le Song,Bo Dai %t2013 %cNIPS %f/NIPS/NIPS-2013-2960.pdf %*Kernel Mean Estimation via Spectral Filtering %@Krikamol Muandet,Bharath Sriperumbudur,Bernhard Schölkopf %t2014 %cNIPS %f/NIPS/NIPS-2014-2961.pdf %*Semi-Separable Hamiltonian Monte Carlo for Inference in Bayesian Hierarchical Models %@Yichuan Zhang,Charles Sutton %t2014 %cNIPS %f/NIPS/NIPS-2014-2962.pdf %*Communication Efficient Distributed Machine Learning with the Parameter Server %@Mu Li,David G. Andersen,Alex J. Smola,Kai Yu %t2014 %cNIPS %f/NIPS/NIPS-2014-2963.pdf %*The Infinite Mixture of Infinite Gaussian Mixtures %@Halid Z. Yerebakan,Bartek Rajwa,Murat Dundar %t2014 %cNIPS %f/NIPS/NIPS-2014-2964.pdf %*Robust Classification Under Sample Selection Bias %@Anqi Liu,Brian Ziebart %t2014 %cNIPS %f/NIPS/NIPS-2014-2965.pdf %*Zeta Hull Pursuits: Learning Nonconvex Data Hulls %@Yuanjun Xiong,Wei Liu,Deli Zhao,Xiaoou Tang %t2014 %cNIPS %f/NIPS/NIPS-2014-2966.pdf %*Grouping-Based Low-Rank Trajectory Completion and 3D Reconstruction %@Katerina Fragkiadaki,Marta Salas,Pablo Arbelaez,Jitendra Malik %t2014 %cNIPS %f/NIPS/NIPS-2014-2967.pdf %*Sparse Space-Time Deconvolution for Calcium Image Analysis %@Ferran Diego Andilla,Fred A. Hamprecht %t2014 %cNIPS %f/NIPS/NIPS-2014-2968.pdf %*Restricted Boltzmann machines modeling human choice %@Takayuki Osogami,Makoto Otsuka %t2014 %cNIPS %f/NIPS/NIPS-2014-2969.pdf %*Multiscale Fields of Patterns %@Pedro Felzenszwalb,John G. Oberlin %t2014 %cNIPS %f/NIPS/NIPS-2014-2970.pdf %*large scale canonical correlation analysis with iterative least squares %@Yichao Lu,Dean P. Foster %t2014 %cNIPS %f/NIPS/NIPS-2014-2971.pdf %*Altitude Training: Strong Bounds for Single-Layer Dropout %@Stefan Wager,William Fithian,Sida Wang,Percy S. Liang %t2014 %cNIPS %f/NIPS/NIPS-2014-2972.pdf %*Parallel Double Greedy Submodular Maximization %@Xinghao Pan,Stefanie Jegelka,Joseph E. Gonzalez,Joseph K. Bradley,Michael I. Jordan %t2014 %cNIPS %f/NIPS/NIPS-2014-2973.pdf %*Multivariate Regression with Calibration %@Han Liu,Lie Wang,Tuo Zhao %t2014 %cNIPS %f/NIPS/NIPS-2014-2974.pdf %*Exact Post Model Selection Inference for Marginal Screening %@Jason D. Lee,Jonathan E. Taylor %t2014 %cNIPS %f/NIPS/NIPS-2014-2975.pdf %*On a Theory of Nonparametric Pairwise Similarity for Clustering: Connecting Clustering to Classification %@Yingzhen Yang,Feng Liang,Shuicheng Yan,Zhangyang Wang,Thomas S. Huang %t2014 %cNIPS %f/NIPS/NIPS-2014-2976.pdf %*Just-In-Time Learning for Fast and Flexible Inference %@S. M. Ali Eslami,Daniel Tarlow,Pushmeet Kohli,John Winn %t2014 %cNIPS %f/NIPS/NIPS-2014-2977.pdf %*Quantized Kernel Learning for Feature Matching %@Danfeng Qin,Xuanli Chen,Matthieu Guillaumin,Luc V. Gool %t2014 %cNIPS %f/NIPS/NIPS-2014-2978.pdf %*Parallel Direction Method of Multipliers %@Huahua Wang,Arindam Banerjee,Zhi-Quan Luo %t2014 %cNIPS %f/NIPS/NIPS-2014-2979.pdf %*(Almost) No Label No Cry %@Giorgio Patrini,Richard Nock,Tiberio Caetano,Paul Rivera %t2014 %cNIPS %f/NIPS/NIPS-2014-2980.pdf %*Stochastic Multi-Armed-Bandit Problem with Non-stationary Rewards %@Omar Besbes,Yonatan Gur,Assaf Zeevi %t2014 %cNIPS %f/NIPS/NIPS-2014-2981.pdf %*Object Localization based on Structural SVM using Privileged Information %@Jan Feyereisl,Suha Kwak,Jeany Son,Bohyung Han %t2014 %cNIPS %f/NIPS/NIPS-2014-2982.pdf %*Multi-View Perceptron: a Deep Model for Learning Face Identity and View Representations %@Zhenyao Zhu,Ping Luo,Xiaogang Wang,Xiaoou Tang %t2014 %cNIPS %f/NIPS/NIPS-2014-2983.pdf %*Shape and Illumination from Shading using the Generic Viewpoint Assumption %@Daniel Zoran,Dilip Krishnan,Jose Bento,Bill Freeman %t2014 %cNIPS %f/NIPS/NIPS-2014-2984.pdf %*Parallel Sampling of HDPs using Sub-Cluster Splits %@Jason Chang,John W. Fisher III %t2014 %cNIPS %f/NIPS/NIPS-2014-2985.pdf %*From MAP to Marginals: Variational Inference in Bayesian Submodular Models %@Josip Djolonga,Andreas Krause %t2014 %cNIPS %f/NIPS/NIPS-2014-2986.pdf %*Robust Logistic Regression and Classification %@Jiashi Feng,Huan Xu,Shie Mannor,Shuicheng Yan %t2014 %cNIPS %f/NIPS/NIPS-2014-2987.pdf %*Extracting Certainty from Uncertainty: Transductive Pairwise Classification from Pairwise Similarities %@Tianbao Yang,Rong Jin %t2014 %cNIPS %f/NIPS/NIPS-2014-2988.pdf %*A Unified Semantic Embedding: Relating Taxonomies and Attributes %@Sung Ju Hwang,Leonid Sigal %t2014 %cNIPS %f/NIPS/NIPS-2014-2989.pdf %*Transportability from Multiple Environments with Limited Experiments: Completeness Results %@Elias Bareinboim,Judea Pearl %t2014 %cNIPS %f/NIPS/NIPS-2014-2990.pdf %*Augmentative Message Passing for Traveling Salesman Problem and Graph Partitioning %@Siamak Ravanbakhsh,Reihaneh Rabbany,Russell Greiner %t2014 %cNIPS %f/NIPS/NIPS-2014-2991.pdf %*Causal Inference through a Witness Protection Program %@Ricardo Silva,Robin Evans %t2014 %cNIPS %f/NIPS/NIPS-2014-2992.pdf %*Incremental Clustering: The Case for Extra Clusters %@Margareta Ackerman,Sanjoy Dasgupta %t2014 %cNIPS %f/NIPS/NIPS-2014-2993.pdf %*Multi-scale Graphical Models for Spatio-Temporal Processes %@firdaus janoos,Huseyin Denli,Niranjan Subrahmanya %t2014 %cNIPS %f/NIPS/NIPS-2014-2994.pdf %*Iterative Neural Autoregressive Distribution Estimator NADE-k %@Tapani Raiko,Yao Li,Kyunghyun Cho,Yoshua Bengio %t2014 %cNIPS %f/NIPS/NIPS-2014-2995.pdf %*Sparse PCA via Covariance Thresholding %@Yash Deshpande,Andrea Montanari %t2014 %cNIPS %f/NIPS/NIPS-2014-2996.pdf %*Low-dimensional models of neural population activity in sensory cortical circuits %@Evan W. Archer,Urs Koster,Jonathan W. Pillow,Jakob H. Macke %t2014 %cNIPS %f/NIPS/NIPS-2014-2997.pdf %*A Synaptical Story of Persistent Activity with Graded Lifetime in a Neural System %@Yuanyuan Mi,Luozheng Li,Dahui Wang,Si Wu %t2014 %cNIPS %f/NIPS/NIPS-2014-2998.pdf %*A Representation Theory for Ranking Functions %@Harsh H. Pareek,Pradeep K. Ravikumar %t2014 %cNIPS %f/NIPS/NIPS-2014-2999.pdf %*Near-optimal sample compression for nearest neighbors %@Lee-Ad Gottlieb,Aryeh Kontorovich,Pinhas Nisnevitch %t2014 %cNIPS %f/NIPS/NIPS-2014-3000.pdf %*Combinatorial Pure Exploration of Multi-Armed Bandits %@Shouyuan Chen,Tian Lin,Irwin King,Michael R. Lyu,Wei Chen %t2014 %cNIPS %f/NIPS/NIPS-2014-3001.pdf %*Log-Hilbert-Schmidt metric between positive definite operators on Hilbert spaces %@Minh Ha Quang,Marco San Biagio,Vittorio Murino %t2014 %cNIPS %f/NIPS/NIPS-2014-3002.pdf %*Consistency of Spectral Partitioning of Uniform Hypergraphs under Planted Partition Model %@Debarghya Ghoshdastidar,Ambedkar Dukkipati %t2014 %cNIPS %f/NIPS/NIPS-2014-3003.pdf %*Spectral Clustering of graphs with the Bethe Hessian %@Alaa Saade,Florent Krzakala,Lenka Zdeborova %t2014 %cNIPS %f/NIPS/NIPS-2014-3004.pdf %*Fast and Robust Least Squares Estimation in Corrupted Linear Models %@Brian McWilliams,Gabriel Krummenacher,Mario Lucic,Joachim M. Buhmann %t2014 %cNIPS %f/NIPS/NIPS-2014-3005.pdf %*Local Decorrelation For Improved Pedestrian Detection %@Woonhyun Nam,Piotr Dollar,Joon Hee Han %t2014 %cNIPS %f/NIPS/NIPS-2014-3006.pdf %*Robust Kernel Density Estimation by Scaling and Projection in Hilbert Space %@Robert A. Vandermeulen,Clayton Scott %t2014 %cNIPS %f/NIPS/NIPS-2014-3007.pdf %*Beyond Disagreement-Based Agnostic Active Learning %@Chicheng Zhang,Kamalika Chaudhuri %t2014 %cNIPS %f/NIPS/NIPS-2014-3008.pdf %*Bayes-Adaptive Simulation-based Search with Value Function Approximation %@Arthur Guez,Nicolas Heess,David Silver,Peter Dayan %t2014 %cNIPS %f/NIPS/NIPS-2014-3009.pdf %*A State-Space Model for Decoding Auditory Attentional Modulation from MEG in a Competing-Speaker Environment %@Sahar Akram,Jonathan Z. Simon,Shihab A. Shamma,Behtash Babadi %t2014 %cNIPS %f/NIPS/NIPS-2014-3010.pdf %*Active Regression by Stratification %@Sivan Sabato,Remi Munos %t2014 %cNIPS %f/NIPS/NIPS-2014-3011.pdf %*Sensory Integration and Density Estimation %@Joseph G. Makin,Philip N. Sabes %t2014 %cNIPS %f/NIPS/NIPS-2014-3012.pdf %*Learning Deep Features for Scene Recognition using Places Database %@Bolei Zhou,Agata Lapedriza,Jianxiong Xiao,Antonio Torralba,Aude Oliva %t2014 %cNIPS %f/NIPS/NIPS-2014-3013.pdf %*A Complete Variational Tracker %@Ryan D. Turner,Steven Bottone,Bhargav Avasarala %t2014 %cNIPS %f/NIPS/NIPS-2014-3014.pdf %*Spike Frequency Adaptation Implements Anticipative Tracking in Continuous Attractor Neural Networks %@Yuanyuan Mi,C. C. Alan Fung,K. Y. Michael Wong,Si Wu %t2014 %cNIPS %f/NIPS/NIPS-2014-3015.pdf %*Efficient Sampling for Learning Sparse Additive Models in High Dimensions %@Hemant Tyagi,Bernd Gärtner,Andreas Krause %t2014 %cNIPS %f/NIPS/NIPS-2014-3016.pdf %*Deep Joint Task Learning for Generic Object Extraction %@Xiaolong Wang,Liliang Zhang,Liang Lin,Zhujin Liang,Wangmeng Zuo %t2014 %cNIPS %f/NIPS/NIPS-2014-3017.pdf %*Robust Bayesian Max-Margin Clustering %@Changyou Chen,Jun Zhu,Xinhua Zhang %t2014 %cNIPS %f/NIPS/NIPS-2014-3018.pdf %*Permutation Diffusion Maps (PDM) with Application to the Image Association Problem in Computer Vision %@Deepti Pachauri,Risi Kondor,Gautam Sargur,Vikas Singh %t2014 %cNIPS %f/NIPS/NIPS-2014-3019.pdf %*Bounded Regret for Finite-Armed Structured Bandits %@Tor Lattimore,Remi Munos %t2014 %cNIPS %f/NIPS/NIPS-2014-3020.pdf %*Coresets for k-Segmentation of Streaming Data %@Guy Rosman,Mikhail Volkov,Dan Feldman,John W. Fisher III,Daniela Rus %t2014 %cNIPS %f/NIPS/NIPS-2014-3021.pdf %*Two-Stream Convolutional Networks for Action Recognition in Videos %@Karen Simonyan,Andrew Zisserman %t2014 %cNIPS %f/NIPS/NIPS-2014-3022.pdf %*Discovering Structure in High-Dimensional Data Through Correlation Explanation %@Greg Ver Steeg,Aram Galstyan %t2014 %cNIPS %f/NIPS/NIPS-2014-3023.pdf %*Positive Curvature and Hamiltonian Monte Carlo %@Christof Seiler,Simon Rubinstein-Salzedo,Susan Holmes %t2014 %cNIPS %f/NIPS/NIPS-2014-3024.pdf %*Learning Mixed Multinomial Logit Model from Ordinal Data %@Sewoong Oh,Devavrat Shah %t2014 %cNIPS %f/NIPS/NIPS-2014-3025.pdf %*Near-optimal Reinforcement Learning in Factored MDPs %@Ian Osband,Benjamin Van Roy %t2014 %cNIPS %f/NIPS/NIPS-2014-3026.pdf %*Efficient learning by implicit exploration in bandit problems with side observations %@Tomáš Kocák,Gergely Neu,Michal Valko,Remi Munos %t2014 %cNIPS %f/NIPS/NIPS-2014-3027.pdf %*Repeated Contextual Auctions with Strategic Buyers %@Kareem Amin,Afshin Rostamizadeh,Umar Syed %t2014 %cNIPS %f/NIPS/NIPS-2014-3028.pdf %*Recursive Inversion Models for Permutations %@Christopher Meek,Marina Meila %t2014 %cNIPS %f/NIPS/NIPS-2014-3029.pdf %*On the Convergence Rate of Decomposable Submodular Function Minimization %@Robert Nishihara,Stefanie Jegelka,Michael I. Jordan %t2014 %cNIPS %f/NIPS/NIPS-2014-3030.pdf %*New Rules for Domain Independent Lifted MAP Inference %@Happy Mittal,Prasoon Goyal,Vibhav G. Gogate,Parag Singla %t2014 %cNIPS %f/NIPS/NIPS-2014-3031.pdf %*PAC-Bayesian AUC classification and scoring %@James Ridgway,Pierre Alquier,Nicolas Chopin,Feng Liang %t2014 %cNIPS %f/NIPS/NIPS-2014-3032.pdf %*Optimization Methods for Sparse Pseudo-Likelihood Graphical Model Selection %@Sang Oh,Onkar Dalal,Kshitij Khare,Bala Rajaratnam %t2014 %cNIPS %f/NIPS/NIPS-2014-3033.pdf %*On Prior Distributions and Approximate Inference for Structured Variables %@Oluwasanmi O. Koyejo,Rajiv Khanna,Joydeep Ghosh,Russell Poldrack %t2014 %cNIPS %f/NIPS/NIPS-2014-3034.pdf %*On Iterative Hard Thresholding Methods for High-dimensional M-Estimation %@Prateek Jain,Ambuj Tewari,Purushottam Kar %t2014 %cNIPS %f/NIPS/NIPS-2014-3035.pdf %*Online and Stochastic Gradient Methods for Non-decomposable Loss Functions %@Purushottam Kar,Harikrishna Narasimhan,Prateek Jain %t2014 %cNIPS %f/NIPS/NIPS-2014-3036.pdf %*Analysis of Learning from Positive and Unlabeled Data %@Marthinus C. du Plessis,Gang Niu,Masashi Sugiyama %t2014 %cNIPS %f/NIPS/NIPS-2014-3037.pdf %*Dimensionality Reduction with Subspace Structure Preservation %@Devansh Arpit,Ifeoma Nwogu,Venu Govindaraju %t2014 %cNIPS %f/NIPS/NIPS-2014-3038.pdf %*Constrained convex minimization via model-based excessive gap %@Quoc Tran-Dinh,Volkan Cevher %t2014 %cNIPS %f/NIPS/NIPS-2014-3039.pdf %*Poisson Process Jumping between an Unknown Number of Rates: Application to Neural Spike Data %@Florian Stimberg,Andreas Ruttor,Manfred Opper %t2014 %cNIPS %f/NIPS/NIPS-2014-3040.pdf %*Probabilistic ODE Solvers with Runge-Kutta Means %@Michael Schober,David K. Duvenaud,Philipp Hennig %t2014 %cNIPS %f/NIPS/NIPS-2014-3041.pdf %*Optimal decision-making with time-varying evidence reliability %@Jan Drugowitsch,Ruben Moreno-Bote,Alexandre Pouget %t2014 %cNIPS %f/NIPS/NIPS-2014-3042.pdf %*Discriminative Unsupervised Feature Learning with Convolutional Neural Networks %@Alexey Dosovitskiy,Jost Tobias Springenberg,Martin Riedmiller,Thomas Brox %t2014 %cNIPS %f/NIPS/NIPS-2014-3043.pdf %*Distance-Based Network Recovery under Feature Correlation %@David Adametz,Volker Roth %t2014 %cNIPS %f/NIPS/NIPS-2014-3044.pdf %*Bandit Convex Optimization: Towards Tight Bounds %@Elad Hazan,Kfir Levy %t2014 %cNIPS %f/NIPS/NIPS-2014-3045.pdf %*Projective dictionary pair learning for pattern classification %@Shuhang Gu,Lei Zhang,Wangmeng Zuo,Xiangchu Feng %t2014 %cNIPS %f/NIPS/NIPS-2014-3046.pdf %*Provable Submodular Minimization using Wolfe's Algorithm %@Deeparnab Chakrabarty,Prateek Jain,Pravesh Kothari %t2014 %cNIPS %f/NIPS/NIPS-2014-3047.pdf %*Exploiting easy data in online optimization %@Amir Sani,Gergely Neu,Alessandro Lazaric %t2014 %cNIPS %f/NIPS/NIPS-2014-3048.pdf %*Sparse Multi-Task Reinforcement Learning %@Daniele Calandriello,Alessandro Lazaric,Marcello Restelli %t2014 %cNIPS %f/NIPS/NIPS-2014-3049.pdf %*Best-Arm Identification in Linear Bandits %@Marta Soare,Alessandro Lazaric,Remi Munos %t2014 %cNIPS %f/NIPS/NIPS-2014-3050.pdf %*Mind the Nuisance: Gaussian Process Classification using Privileged Noise %@Daniel Hernández-lobato,Viktoriia Sharmanska,Kristian Kersting,Christoph H. Lampert,Novi Quadrianto %t2014 %cNIPS %f/NIPS/NIPS-2014-3051.pdf %*Tight Bounds for Influence in Diffusion Networks and Application to Bond Percolation and Epidemiology %@Remi Lemonnier,Kevin Scaman,Nicolas Vayatis %t2014 %cNIPS %f/NIPS/NIPS-2014-3052.pdf %*On the Computational Efficiency of Training Neural Networks %@Roi Livni,Shai Shalev-Shwartz,Ohad Shamir %t2014 %cNIPS %f/NIPS/NIPS-2014-3053.pdf %*Self-Adaptable Templates for Feature Coding %@Xavier Boix,Gemma Roig,Salomon Diether,Luc V. Gool %t2014 %cNIPS %f/NIPS/NIPS-2014-3054.pdf %*Multilabel Structured Output Learning with Random Spanning Trees of Max-Margin Markov Networks %@Mario Marchand,Hongyu Su,Emilie Morvant,Juho Rousu,John S. Shawe-Taylor %t2014 %cNIPS %f/NIPS/NIPS-2014-3055.pdf %*Stochastic Network Design in Bidirected Trees %@xiaojian wu,Daniel R. Sheldon,Shlomo Zilberstein %t2014 %cNIPS %f/NIPS/NIPS-2014-3056.pdf %*SerialRank: Spectral Ranking using Seriation %@Fajwel Fogel,Alexandre d'Aspremont,Milan Vojnovic %t2014 %cNIPS %f/NIPS/NIPS-2014-3057.pdf %*Clamping Variables and Approximate Inference %@Adrian Weller,Tony Jebara %t2014 %cNIPS %f/NIPS/NIPS-2014-3058.pdf %*Predictive Entropy Search for Efficient Global Optimization of Black-box Functions %@José Miguel Hernández-Lobato,Matthew W. Hoffman,Zoubin Ghahramani %t2014 %cNIPS %f/NIPS/NIPS-2014-3059.pdf %*A Block-Coordinate Descent Approach for Large-scale Sparse Inverse Covariance Estimation %@Eran Treister,Javier S. Turek %t2014 %cNIPS %f/NIPS/NIPS-2014-3060.pdf %*Efficient Inference of Continuous Markov Random Fields with Polynomial Potentials %@Shenlong Wang,Alex Schwing,Raquel Urtasun %t2014 %cNIPS %f/NIPS/NIPS-2014-3061.pdf %*Scalable Methods for Nonnegative Matrix Factorizations of Near-separable Tall-and-skinny Matrices %@Austin R. Benson,Jason D. Lee,Bartek Rajwa,David F. Gleich %t2014 %cNIPS %f/NIPS/NIPS-2014-3062.pdf %*Inferring synaptic conductances from spike trains with a biophysically inspired point process model %@Kenneth W. Latimer,E. J. Chichilnisky,Fred Rieke,Jonathan W. Pillow %t2014 %cNIPS %f/NIPS/NIPS-2014-3063.pdf %*Expectation Backpropagation: Parameter-Free Training of Multilayer Neural Networks with Continuous or Discrete Weights %@Daniel Soudry,Itay Hubara,Ron Meir %t2014 %cNIPS %f/NIPS/NIPS-2014-3064.pdf %*Incremental Local Gaussian Regression %@Franziska Meier,Philipp Hennig,Stefan Schaal %t2014 %cNIPS %f/NIPS/NIPS-2014-3065.pdf %*General Table Completion using a Bayesian Nonparametric Model %@Isabel Valera,Zoubin Ghahramani %t2014 %cNIPS %f/NIPS/NIPS-2014-3066.pdf %*Universal Option Models %@hengshuai yao,Csaba Szepesvari,Richard S. Sutton,Joseph Modayil,Shalabh Bhatnagar %t2014 %cNIPS %f/NIPS/NIPS-2014-3067.pdf %*Approximating Hierarchical MV-sets for Hierarchical Clustering %@Assaf Glazer,Omer Weissbrod,Michael Lindenbaum,Shaul Markovitch %t2014 %cNIPS %f/NIPS/NIPS-2014-3068.pdf %*Constant Nullspace Strong Convexity and Fast Convergence of Proximal Methods under High-Dimensional Settings %@Ian En-Hsu Yen,Cho-Jui Hsieh,Pradeep K. Ravikumar,Inderjit S. Dhillon %t2014 %cNIPS %f/NIPS/NIPS-2014-3069.pdf %*Stochastic Gradient Descent, Weighted Sampling, and the Randomized Kaczmarz algorithm %@Deanna Needell,Rachel Ward,Nati Srebro %t2014 %cNIPS %f/NIPS/NIPS-2014-3070.pdf %*A Framework for Testing Identifiability of Bayesian Models of Perception %@Luigi Acerbi,Wei Ji Ma,Sethu Vijayakumar %t2014 %cNIPS %f/NIPS/NIPS-2014-3071.pdf %*Optimistic Planning in Markov Decision Processes Using a Generative Model %@Balázs Szörényi,Gunnar Kedenburg,Remi Munos %t2014 %cNIPS %f/NIPS/NIPS-2014-3072.pdf %*Gaussian Process Volatility Model %@Yue Wu,José Miguel Hernández-Lobato,Zoubin Ghahramani %t2014 %cNIPS %f/NIPS/NIPS-2014-3073.pdf %*A Safe Screening Rule for Sparse Logistic Regression %@Jie Wang,Jiayu Zhou,Jun Liu,Peter Wonka,Jieping Ye %t2014 %cNIPS %f/NIPS/NIPS-2014-3074.pdf %*Hardness of parameter estimation in graphical models %@Guy Bresler,David Gamarnik,Devavrat Shah %t2014 %cNIPS %f/NIPS/NIPS-2014-3075.pdf %*Learning Neural Network Policies with Guided Policy Search under Unknown Dynamics %@Sergey Levine,Pieter Abbeel %t2014 %cNIPS %f/NIPS/NIPS-2014-3076.pdf %*Magnitude-sensitive preference formation` %@Nisheeth Srivastava,Ed Vul,Paul R. Schrater %t2014 %cNIPS %f/NIPS/NIPS-2014-3077.pdf %*Extreme bandits %@Alexandra Carpentier,Michal Valko %t2014 %cNIPS %f/NIPS/NIPS-2014-3078.pdf %*Distributed Estimation, Information Loss and Exponential Families %@Qiang Liu,Alexander T. Ihler %t2014 %cNIPS %f/NIPS/NIPS-2014-3079.pdf %*Non-convex Robust PCA %@Praneeth Netrapalli,Niranjan U N,Sujay Sanghavi,Animashree Anandkumar,Prateek Jain %t2014 %cNIPS %f/NIPS/NIPS-2014-3080.pdf %*Learning From Weakly Supervised Data by The Expectation Loss SVM (e-SVM) algorithm %@Jun Zhu,Junhua Mao,Alan L. Yuille %t2014 %cNIPS %f/NIPS/NIPS-2014-3081.pdf %*Message Passing Inference for Large Scale Graphical Models with High Order Potentials %@Jian Zhang,Alex Schwing,Raquel Urtasun %t2014 %cNIPS %f/NIPS/NIPS-2014-3082.pdf %*Encoding High Dimensional Local Features by Sparse Coding Based Fisher Vectors %@Lingqiao Liu,Chunhua Shen,Lei Wang,Anton van den Hengel,Chao Wang %t2014 %cNIPS %f/NIPS/NIPS-2014-3083.pdf %*Dependent nonparametric trees for dynamic hierarchical clustering %@Kumar Dubey,Qirong Ho,Sinead A. Williamson,Eric P. Xing %t2014 %cNIPS %f/NIPS/NIPS-2014-3084.pdf %*Causal Strategic Inference in Networked Microfinance Economies %@Mohammad T. Irfan,Luis E. Ortiz %t2014 %cNIPS %f/NIPS/NIPS-2014-3085.pdf %*Learning Multiple Tasks in Parallel with a Shared Annotator %@Haim Cohen,Koby Crammer %t2014 %cNIPS %f/NIPS/NIPS-2014-3086.pdf %*Reducing the Rank in Relational Factorization Models by Including Observable Patterns %@Maximilian Nickel,Xueyan Jiang,Volker Tresp %t2014 %cNIPS %f/NIPS/NIPS-2014-3087.pdf %*Clustering from Labels and Time-Varying Graphs %@Shiau Hong Lim,Yudong Chen,Huan Xu %t2014 %cNIPS %f/NIPS/NIPS-2014-3088.pdf %*From Stochastic Mixability to Fast Rates %@Nishant A. Mehta,Robert C. Williamson %t2014 %cNIPS %f/NIPS/NIPS-2014-3089.pdf %*Recovery of Coherent Data via Low-Rank Dictionary Pursuit %@Guangcan Liu,Ping Li %t2014 %cNIPS %f/NIPS/NIPS-2014-3090.pdf %*Inferring sparse representations of continuous signals with continuous orthogonal matching pursuit %@Karin C. Knudson,Jacob Yates,Alexander Huk,Jonathan W. Pillow %t2014 %cNIPS %f/NIPS/NIPS-2014-3091.pdf %*Analysis of Variational Bayesian Latent Dirichlet Allocation: Weaker Sparsity Than MAP %@Shinichi Nakajima,Issei Sato,Masashi Sugiyama,Kazuho Watanabe,Hiroko Kobayashi %t2014 %cNIPS %f/NIPS/NIPS-2014-3092.pdf %*Discovering, Learning and Exploiting Relevance %@Cem Tekin,Mihaela Van Der Schaar %t2014 %cNIPS %f/NIPS/NIPS-2014-3093.pdf %*Divide-and-Conquer Learning by Anchoring a Conical Hull %@Tianyi Zhou,Jeff A. Bilmes,Carlos Guestrin %t2014 %cNIPS %f/NIPS/NIPS-2014-3094.pdf %*Extended and Unscented Gaussian Processes %@Daniel M. Steinberg,Edwin V. Bonilla %t2014 %cNIPS %f/NIPS/NIPS-2014-3095.pdf %*Spectral Methods meet EM: A Provably Optimal Algorithm for Crowdsourcing %@Yuchen Zhang,Xi Chen,Denny Zhou,Michael I. Jordan %t2014 %cNIPS %f/NIPS/NIPS-2014-3096.pdf %*Exploiting Linear Structure Within Convolutional Networks for Efficient Evaluation %@Emily L. Denton,Wojciech Zaremba,Joan Bruna,Yann LeCun,Rob Fergus %t2014 %cNIPS %f/NIPS/NIPS-2014-3097.pdf %*Learning to Discover Efficient Mathematical Identities %@Wojciech Zaremba,Karol Kurach,Rob Fergus %t2014 %cNIPS %f/NIPS/NIPS-2014-3098.pdf %*The Large Margin Mechanism for Differentially Private Maximization %@Kamalika Chaudhuri,Daniel J. Hsu,Shuang Song %t2014 %cNIPS %f/NIPS/NIPS-2014-3099.pdf %*DFacTo: Distributed Factorization of Tensors %@Joon Hee Choi,S. Vishwanathan %t2014 %cNIPS %f/NIPS/NIPS-2014-3100.pdf %*Localized Data Fusion for Kernel k-Means Clustering with Application to Cancer Biology %@Mehmet Gönen,Adam A. Margolin %t2014 %cNIPS %f/NIPS/NIPS-2014-3101.pdf %*Conditional Swap Regret and Conditional Correlated Equilibrium %@Mehryar Mohri,Scott Yang %t2014 %cNIPS %f/NIPS/NIPS-2014-3102.pdf %*Mode Estimation for High Dimensional Discrete Tree Graphical Models %@Chao Chen,Han Liu,Dimitris Metaxas,Tianqi Zhao %t2014 %cNIPS %f/NIPS/NIPS-2014-3103.pdf %*Large-scale L-BFGS using MapReduce %@Weizhu Chen,Zhenghao Wang,Jingren Zhou %t2014 %cNIPS %f/NIPS/NIPS-2014-3104.pdf %*Submodular Attribute Selection for Action Recognition in Video %@Jingjing Zheng,Zhuolin Jiang,Rama Chellappa,Jonathon P. Phillips %t2014 %cNIPS %f/NIPS/NIPS-2014-3105.pdf %*Efficient Structured Matrix Rank Minimization %@Adams Wei Yu,Wanli Ma,Yaoliang Yu,Jaime Carbonell,Suvrit Sra %t2014 %cNIPS %f/NIPS/NIPS-2014-3106.pdf %*On Integrated Clustering and Outlier Detection %@Lionel Ott,Linsey Pang,Fabio T. Ramos,Sanjay Chawla %t2014 %cNIPS %f/NIPS/NIPS-2014-3107.pdf %*A Drifting-Games Analysis for Online Learning and Applications to Boosting %@Haipeng Luo,Robert E. Schapire %t2014 %cNIPS %f/NIPS/NIPS-2014-3108.pdf %*Projecting Markov Random Field Parameters for Fast Mixing %@Xianghang Liu,Justin Domke %t2014 %cNIPS %f/NIPS/NIPS-2014-3109.pdf %*Automatic Discovery of Cognitive Skills to Improve the Prediction of Student Learning %@Robert V. Lindsey,Mohammad Khajah,Michael C. Mozer %t2014 %cNIPS %f/NIPS/NIPS-2014-3110.pdf %*Near-Optimal-Sample Estimators for Spherical Gaussian Mixtures %@Ananda Theertha Suresh,Alon Orlitsky,Jayadev Acharya,Ashkan Jafarpour %t2014 %cNIPS %f/NIPS/NIPS-2014-3111.pdf %*Automated Variational Inference for Gaussian Process Models %@Trung V. Nguyen,Edwin V. Bonilla %t2014 %cNIPS %f/NIPS/NIPS-2014-3112.pdf %*Learning Mixtures of Submodular Functions for Image Collection Summarization %@Sebastian Tschiatschek,Rishabh K. Iyer,Haochen Wei,Jeff A. Bilmes %t2014 %cNIPS %f/NIPS/NIPS-2014-3113.pdf %*Robust Tensor Decomposition with Gross Corruption %@Quanquan Gu,Huan Gui,Jiawei Han %t2014 %cNIPS %f/NIPS/NIPS-2014-3114.pdf %*Provable Tensor Factorization with Missing Data %@Prateek Jain,Sewoong Oh %t2014 %cNIPS %f/NIPS/NIPS-2014-3115.pdf %*Parallel Successive Convex Approximation for Nonsmooth Nonconvex Optimization %@Meisam Razaviyayn,Mingyi Hong,Zhi-Quan Luo,Jong-Shi Pang %t2014 %cNIPS %f/NIPS/NIPS-2014-3116.pdf %*Using Convolutional Neural Networks to Recognize Rhythm Stimuli from Electroencephalography Recordings %@Sebastian Stober,Daniel J. Cameron,Jessica A. Grahn %t2014 %cNIPS %f/NIPS/NIPS-2014-3117.pdf %*Blossom Tree Graphical Models %@Zhe Liu,John Lafferty %t2014 %cNIPS %f/NIPS/NIPS-2014-3118.pdf %*Model-based Reinforcement Learning and the Eluder Dimension %@Ian Osband,Benjamin Van Roy %t2014 %cNIPS %f/NIPS/NIPS-2014-3119.pdf %*Minimax-optimal Inference from Partial Rankings %@Bruce Hajek,Sewoong Oh,Jiaming Xu %t2014 %cNIPS %f/NIPS/NIPS-2014-3120.pdf %*Spectral Methods for Indian Buffet Process Inference %@Hsiao-Yu Tung,Alex J. Smola %t2014 %cNIPS %f/NIPS/NIPS-2014-3121.pdf %*On the Statistical Consistency of Plug-in Classifiers for Non-decomposable Performance Measures %@Harikrishna Narasimhan,Rohit Vaish,Shivani Agarwal %t2014 %cNIPS %f/NIPS/NIPS-2014-3122.pdf %*Top Rank Optimization in Linear Time %@Nan Li,Rong Jin,Zhi-Hua Zhou %t2014 %cNIPS %f/NIPS/NIPS-2014-3123.pdf %*Spectral Methods for Supervised Topic Models %@Yining Wang,Jun Zhu %t2014 %cNIPS %f/NIPS/NIPS-2014-3124.pdf %*Graphical Models for Recovering Probabilistic and Causal Queries from Missing Data %@Karthika Mohan,Judea Pearl %t2014 %cNIPS %f/NIPS/NIPS-2014-3125.pdf %*Sparse PCA with Oracle Property %@Quanquan Gu,Zhaoran Wang,Han Liu %t2014 %cNIPS %f/NIPS/NIPS-2014-3126.pdf %*Unsupervised Transcription of Piano Music %@Taylor Berg-Kirkpatrick,Jacob Andreas,Dan Klein %t2014 %cNIPS %f/NIPS/NIPS-2014-3127.pdf %*Estimation with Norm Regularization %@Arindam Banerjee,Sheng Chen,Farideh Fazayeli,Vidyashankar Sivakumar %t2014 %cNIPS %f/NIPS/NIPS-2014-3128.pdf %*Decomposing Parameter Estimation Problems %@Khaled S. Refaat,Arthur Choi,Adnan Darwiche %t2014 %cNIPS %f/NIPS/NIPS-2014-3129.pdf %*Learning to Optimize via Information-Directed Sampling %@Dan Russo,Benjamin Van Roy %t2014 %cNIPS %f/NIPS/NIPS-2014-3130.pdf %*Covariance shrinkage for autocorrelated data %@Daniel Bartz,Klaus-Robert Müller %t2014 %cNIPS %f/NIPS/NIPS-2014-3131.pdf %*Do Convnets Learn Correspondence? %@Jonathan L. Long,Ning Zhang,Trevor Darrell %t2014 %cNIPS %f/NIPS/NIPS-2014-3132.pdf %*The Blinded Bandit: Learning with Adaptive Feedback %@Ofer Dekel,Elad Hazan,Tomer Koren %t2014 %cNIPS %f/NIPS/NIPS-2014-3133.pdf %*Convex Optimization Procedure for Clustering: Theoretical Revisit %@Changbo Zhu,Huan Xu,Chenlei Leng,Shuicheng Yan %t2014 %cNIPS %f/NIPS/NIPS-2014-3134.pdf %*Sparse Bayesian structure learning with “dependent relevance determination” priors %@Anqi Wu,Mijung Park,Oluwasanmi O. Koyejo,Jonathan W. Pillow %t2014 %cNIPS %f/NIPS/NIPS-2014-3135.pdf %*Weakly-supervised Discovery of Visual Pattern Configurations %@Hyun Oh Song,Yong Jae Lee,Stefanie Jegelka,Trevor Darrell %t2014 %cNIPS %f/NIPS/NIPS-2014-3136.pdf %*SAGA: A Fast Incremental Gradient Method With Support for Non-Strongly Convex Composite Objectives %@Aaron Defazio,Francis Bach,Simon Lacoste-Julien %t2014 %cNIPS %f/NIPS/NIPS-2014-3137.pdf %*Exclusive Feature Learning on Arbitrary Structures via \ell_{1,2}-norm %@Deguang Kong,Ryohei Fujimaki,Ji Liu,Feiping Nie,Chris Ding %t2014 %cNIPS %f/NIPS/NIPS-2014-3138.pdf %*Time--Data Tradeoffs by Aggressive Smoothing %@John J. Bruer,Joel A. Tropp,Volkan Cevher,Stephen Becker %t2014 %cNIPS %f/NIPS/NIPS-2014-3139.pdf %*Distributed Power-law Graph Computing: Theoretical and Empirical Analysis %@Cong Xie,Ling Yan,Wu-Jun Li,Zhihua Zhang %t2014 %cNIPS %f/NIPS/NIPS-2014-3140.pdf %*A Multi-World Approach to Question Answering about Real-World Scenes based on Uncertain Input %@Mateusz Malinowski,Mario Fritz %t2014 %cNIPS %f/NIPS/NIPS-2014-3141.pdf %*Efficient Partial Monitoring with Prior Information %@Hastagiri P. Vanchinathan,Gábor Bartók,Andreas Krause %t2014 %cNIPS %f/NIPS/NIPS-2014-3142.pdf %*Distributed Parameter Estimation in Probabilistic Graphical Models %@Yariv D. Mizrahi,Misha Denil,Nando de Freitas %t2014 %cNIPS %f/NIPS/NIPS-2014-3143.pdf %*Unsupervised Deep Haar Scattering on Graphs %@Xu Chen,Xiuyuan Cheng,Stephane Mallat %t2014 %cNIPS %f/NIPS/NIPS-2014-3144.pdf %*Online Optimization for Max-Norm Regularization %@Jie Shen,Huan Xu,Ping Li %t2014 %cNIPS %f/NIPS/NIPS-2014-3145.pdf %*Probabilistic low-rank matrix completion on finite alphabets %@Jean Lafond,Olga Klopp,Eric Moulines,Joseph Salmon %t2014 %cNIPS %f/NIPS/NIPS-2014-3146.pdf %*Articulated Pose Estimation by a Graphical Model with Image Dependent Pairwise Relations %@Xianjie Chen,Alan L. Yuille %t2014 %cNIPS %f/NIPS/NIPS-2014-3147.pdf %*Bayesian Inference for Structured Spike and Slab Priors %@Michael R. Andersen,Ole Winther,Lars K. Hansen %t2014 %cNIPS %f/NIPS/NIPS-2014-3148.pdf %*Bayesian Nonlinear Support Vector Machines and Discriminative Factor Modeling %@Ricardo Henao,Xin Yuan,Lawrence Carin %t2014 %cNIPS %f/NIPS/NIPS-2014-3149.pdf %*Generalized Higher-Order Orthogonal Iteration for Tensor Decomposition and Completion %@Yuanyuan Liu,Fanhua Shang,Wei Fan,James Cheng,Hong Cheng %t2014 %cNIPS %f/NIPS/NIPS-2014-3150.pdf %*Making Pairwise Binary Graphical Models Attractive %@Nicholas Ruozzi,Tony Jebara %t2014 %cNIPS %f/NIPS/NIPS-2014-3151.pdf %*Deep Convolutional Neural Network for Image Deconvolution %@Li Xu,Jimmy SJ Ren,Ce Liu,Jiaya Jia %t2014 %cNIPS %f/NIPS/NIPS-2014-3152.pdf %*Joint Training of a Convolutional Network and a Graphical Model for Human Pose Estimation %@Jonathan J. Tompson,Arjun Jain,Yann LeCun,Christoph Bregler %t2014 %cNIPS %f/NIPS/NIPS-2014-3153.pdf %*Learning Generative Models with Visual Attention %@Yichuan Tang,Nitish Srivastava,Ruslan R. Salakhutdinov %t2014 %cNIPS %f/NIPS/NIPS-2014-3154.pdf %*Metric Learning for Temporal Sequence Alignment %@Damien Garreau,Rémi Lajugie,Sylvain Arlot,Francis Bach %t2014 %cNIPS %f/NIPS/NIPS-2014-3155.pdf %*Learning Optimal Commitment to Overcome Insecurity %@Avrim Blum,Nika Haghtalab,Ariel D. Procaccia %t2014 %cNIPS %f/NIPS/NIPS-2014-3156.pdf %*How hard is my MDP?" The distribution-norm to the rescue" %@Odalric-Ambrym Maillard,Timothy A. Mann,Shie Mannor %t2014 %cNIPS %f/NIPS/NIPS-2014-3157.pdf %*Near-Optimal Density Estimation in Near-Linear Time Using Variable-Width Histograms %@Siu On Chan,Ilias Diakonikolas,Rocco A. Servedio,Xiaorui Sun %t2014 %cNIPS %f/NIPS/NIPS-2014-3158.pdf %*An Autoencoder Approach to Learning Bilingual Word Representations %@Sarath Chandar A P,Stanislas Lauly,Hugo Larochelle,Mitesh Khapra,Balaraman Ravindran,Vikas C. Raykar,Amrita Saha %t2014 %cNIPS %f/NIPS/NIPS-2014-3159.pdf %*Sequential Monte Carlo for Graphical Models %@Christian Andersson Naesseth,Fredrik Lindsten,Thomas B. Schön %t2014 %cNIPS %f/NIPS/NIPS-2014-3160.pdf %*Optimal Regret Minimization in Posted-Price Auctions with Strategic Buyers %@Mehryar Mohri,Andres Munoz %t2014 %cNIPS %f/NIPS/NIPS-2014-3161.pdf %*Optimal prior-dependent neural population codes under shared input noise %@Agnieszka Grabska-Barwinska,Jonathan W. Pillow %t2014 %cNIPS %f/NIPS/NIPS-2014-3162.pdf %*Deep Fragment Embeddings for Bidirectional Image Sentence Mapping %@Andrej Karpathy,Armand Joulin,Fei Fei F. Li %t2014 %cNIPS %f/NIPS/NIPS-2014-3163.pdf %*Flexible Transfer Learning under Support and Model Shift %@Xuezhi Wang,Jeff Schneider %t2014 %cNIPS %f/NIPS/NIPS-2014-3164.pdf %*Probabilistic Differential Dynamic Programming %@Yunpeng Pan,Evangelos Theodorou %t2014 %cNIPS %f/NIPS/NIPS-2014-3165.pdf %*Predicting Useful Neighborhoods for Lazy Local Learning %@Aron Yu,Kristen Grauman %t2014 %cNIPS %f/NIPS/NIPS-2014-3166.pdf %*Modeling Deep Temporal Dependencies with Recurrent Grammar Cells"" %@Vincent Michalski,Roland Memisevic,Kishore Konda %t2014 %cNIPS %f/NIPS/NIPS-2014-3167.pdf %*Generalized Dantzig Selector: Application to the k-support norm %@Soumyadeep Chatterjee,Sheng Chen,Arindam Banerjee %t2014 %cNIPS %f/NIPS/NIPS-2014-3168.pdf %*Neurons as Monte Carlo Samplers: Bayesian Inference and Learning in Spiking Networks %@Yanping Huang,Rajesh P. Rao %t2014 %cNIPS %f/NIPS/NIPS-2014-3169.pdf %*The Bayesian Case Model: A Generative Approach for Case-Based Reasoning and Prototype Classification %@Been Kim,Cynthia Rudin,Julie A. Shah %t2014 %cNIPS %f/NIPS/NIPS-2014-3170.pdf %*Latent Support Measure Machines for Bag-of-Words Data Classification %@Yuya Yoshikawa,Tomoharu Iwata,Hiroshi Sawada %t2014 %cNIPS %f/NIPS/NIPS-2014-3171.pdf %*Local Linear Convergence of Forward--Backward under Partial Smoothness %@Jingwei Liang,Jalal Fadili,Gabriel Peyré %t2014 %cNIPS %f/NIPS/NIPS-2014-3172.pdf %*RAAM: The Benefits of Robustness in Approximating Aggregated MDPs in Reinforcement Learning %@Marek Petrik,Dharmashankar Subramanian %t2014 %cNIPS %f/NIPS/NIPS-2014-3173.pdf %*Deep Learning Face Representation by Joint Identification-Verification %@Yi Sun,Yuheng Chen,Xiaogang Wang,Xiaoou Tang %t2014 %cNIPS %f/NIPS/NIPS-2014-3174.pdf %*A provable SVD-based algorithm for learning topics in dominant admixture corpus %@Trapit Bansal,Chiranjib Bhattacharyya,Ravindran Kannan %t2014 %cNIPS %f/NIPS/NIPS-2014-3175.pdf %*QUIC & DIRTY: A Quadratic Approximation Approach for Dirty Statistical Models %@Cho-Jui Hsieh,Inderjit S. Dhillon,Pradeep K. Ravikumar,Stephen Becker,Peder A. Olsen %t2014 %cNIPS %f/NIPS/NIPS-2014-3176.pdf %*General Stochastic Networks for Classification %@Matthias Zöhrer,Franz Pernkopf %t2014 %cNIPS %f/NIPS/NIPS-2014-3177.pdf %*Spatio-temporal Representations of Uncertainty in Spiking Neural Networks %@Cristina Savin,Sophie Denève %t2014 %cNIPS %f/NIPS/NIPS-2014-3178.pdf %*Attentional Neural Network: Feature Selection Using Cognitive Feedback %@Qian Wang,Jiaxing Zhang,Sen Song,Zheng Zhang %t2014 %cNIPS %f/NIPS/NIPS-2014-3179.pdf %*Convolutional Neural Network Architectures for Matching Natural Language Sentences %@Baotian Hu,Zhengdong Lu,Hang Li,Qingcai Chen %t2014 %cNIPS %f/NIPS/NIPS-2014-3180.pdf %*Scalable Non-linear Learning with Adaptive Polynomial Expansions %@Alekh Agarwal,Alina Beygelzimer,Daniel J. Hsu,John Langford,Matus J. Telgarsky %t2014 %cNIPS %f/NIPS/NIPS-2014-3181.pdf %*On the relations of LFPs & Neural Spike Trains %@David E. Carlson,Jana Schaich Borg,Kafui Dzirasa,Lawrence Carin %t2014 %cNIPS %f/NIPS/NIPS-2014-3182.pdf %*Diverse Sequential Subset Selection for Supervised Video Summarization %@Boqing Gong,Wei-Lun Chao,Kristen Grauman,Fei Sha %t2014 %cNIPS %f/NIPS/NIPS-2014-3183.pdf %*Self-Paced Learning with Diversity %@Lu Jiang,Deyu Meng,Shoou-I Yu,Zhenzhong Lan,Shiguang Shan,Alexander Hauptmann %t2014 %cNIPS %f/NIPS/NIPS-2014-3184.pdf %*Feature Cross-Substitution in Adversarial Classification %@Bo Li,Yevgeniy Vorobeychik %t2014 %cNIPS %f/NIPS/NIPS-2014-3185.pdf %*Deep Recursive Neural Networks for Compositionality in Language %@Ozan Irsoy,Claire Cardie %t2014 %cNIPS %f/NIPS/NIPS-2014-3186.pdf %*Inference by Learning: Speeding-up Graphical Model Optimization via a Coarse-to-Fine Cascade of Pruning Classifiers %@Bruno Conejo,Nikos Komodakis,Sebastien Leprince,Jean Philippe Avouac %t2014 %cNIPS %f/NIPS/NIPS-2014-3187.pdf %*A Filtering Approach to Stochastic Variational Inference %@Neil Houlsby,David Blei %t2014 %cNIPS %f/NIPS/NIPS-2014-3188.pdf %*Optimizing F-Measures by Cost-Sensitive Classification %@Shameem Puthiya Parambath,Nicolas Usunier,Yves Grandvalet %t2014 %cNIPS %f/NIPS/NIPS-2014-3189.pdf %*Two-Layer Feature Reduction for Sparse-Group Lasso via Decomposition of Convex Sets %@Jie Wang,Jieping Ye %t2014 %cNIPS %f/NIPS/NIPS-2014-3190.pdf %*Improved Multimodal Deep Learning with Variation of Information %@Kihyuk Sohn,Wenling Shang,Honglak Lee %t2014 %cNIPS %f/NIPS/NIPS-2014-3191.pdf %*Elementary Estimators for Graphical Models %@Eunho Yang,Aurelie C. Lozano,Pradeep K. Ravikumar %t2014 %cNIPS %f/NIPS/NIPS-2014-3192.pdf %*Beyond the Birkhoff Polytope: Convex Relaxations for Vector Permutation Problems %@Cong Han Lim,Stephen Wright %t2014 %cNIPS %f/NIPS/NIPS-2014-3193.pdf %*Neural Word Embedding as Implicit Matrix Factorization %@Omer Levy,Yoav Goldberg %t2014 %cNIPS %f/NIPS/NIPS-2014-3194.pdf %*Multi-Resolution Cascades for Multiclass Object Detection %@Mohammad Saberian,Nuno Vasconcelos %t2014 %cNIPS %f/NIPS/NIPS-2014-3195.pdf %*Median Selection Subset Aggregation for Parallel Inference %@Xiangyu Wang,Peichao Peng,David B. Dunson %t2014 %cNIPS %f/NIPS/NIPS-2014-3196.pdf %*Recurrent Models of Visual Attention %@Volodymyr Mnih,Nicolas Heess,Alex Graves,koray kavukcuoglu %t2014 %cNIPS %f/NIPS/NIPS-2014-3197.pdf %*Tree-structured Gaussian Process Approximations %@Thang D. Bui,Richard E. Turner %t2014 %cNIPS %f/NIPS/NIPS-2014-3198.pdf %*Active Learning and Best-Response Dynamics %@Maria-Florina F. Balcan,Christopher Berlind,Avrim Blum,Emma Cohen,Kaushik Patnaik,Le Song %t2014 %cNIPS %f/NIPS/NIPS-2014-3199.pdf %*Analog Memories in a Balanced Rate-Based Network of E-I Neurons %@Dylan Festa,Guillaume Hennequin,Mate Lengyel %t2014 %cNIPS %f/NIPS/NIPS-2014-3200.pdf %*Fast Sampling-Based Inference in Balanced Neuronal Networks %@Guillaume Hennequin,Laurence Aitchison,Mate Lengyel %t2014 %cNIPS %f/NIPS/NIPS-2014-3201.pdf %*Spectral Learning of Mixture of Hidden Markov Models %@Cem Subakan,Johannes Traa,Paris Smaragdis %t2014 %cNIPS %f/NIPS/NIPS-2014-3202.pdf %*Subspace Embeddings for the Polynomial Kernel %@Haim Avron,Huy Nguyen,David Woodruff %t2014 %cNIPS %f/NIPS/NIPS-2014-3203.pdf %*A Boosting Framework on Grounds of Online Learning %@Tofigh Naghibi Mohamadpoor,Beat Pfister %t2014 %cNIPS %f/NIPS/NIPS-2014-3204.pdf %*A Dual Algorithm for Olfactory Computation in the Locust Brain %@Sina Tootoonian,Mate Lengyel %t2014 %cNIPS %f/NIPS/NIPS-2014-3205.pdf %*Advances in Learning Bayesian Networks of Bounded Treewidth %@Siqi Nie,Denis D. Maua,Cassio P. de Campos,Qiang Ji %t2014 %cNIPS %f/NIPS/NIPS-2014-3206.pdf %*Learning the Learning Rate for Prediction with Expert Advice %@Wouter M. Koolen,Tim van Erven,Peter Grünwald %t2014 %cNIPS %f/NIPS/NIPS-2014-3207.pdf %*On the Information Theoretic Limits of Learning Ising Models %@Rashish Tandon,Karthikeyan Shanmugam,Pradeep K. Ravikumar,Alexandros G. Dimakis %t2014 %cNIPS %f/NIPS/NIPS-2014-3208.pdf %*Efficient Optimization for Average Precision SVM %@Pritish Mohapatra,C.V. Jawahar,M. Pawan Kumar %t2014 %cNIPS %f/NIPS/NIPS-2014-3209.pdf %*Asymmetric LSH (ALSH) for Sublinear Time Maximum Inner Product Search (MIPS) %@Anshumali Shrivastava,Ping Li %t2014 %cNIPS %f/NIPS/NIPS-2014-3210.pdf %*A framework for studying synaptic plasticity with neural spike train data %@Scott Linderman,Christopher H. Stock,Ryan P. Adams %t2014 %cNIPS %f/NIPS/NIPS-2014-3211.pdf %*Randomized Experimental Design for Causal Graph Discovery %@Huining Hu,Zhentao Li,Adrian R. Vetta %t2014 %cNIPS %f/NIPS/NIPS-2014-3212.pdf %*A Multiplicative Model for Learning Distributed Text-Based Attribute Representations %@Ryan Kiros,Richard Zemel,Ruslan R. Salakhutdinov %t2014 %cNIPS %f/NIPS/NIPS-2014-3213.pdf %*Learning Chordal Markov Networks by Dynamic Programming %@Kustaa Kangas,Mikko Koivisto,Teppo Niinimäki %t2014 %cNIPS %f/NIPS/NIPS-2014-3214.pdf %*Depth Map Prediction from a Single Image using a Multi-Scale Deep Network %@David Eigen,Christian Puhrsch,Rob Fergus %t2014 %cNIPS %f/NIPS/NIPS-2014-3215.pdf %*Proximal Quasi-Newton for Computationally Intensive L1-regularized M-estimators %@Kai Zhong,Ian En-Hsu Yen,Inderjit S. Dhillon,Pradeep K. Ravikumar %t2014 %cNIPS %f/NIPS/NIPS-2014-3216.pdf %*A Probabilistic Framework for Multimodal Retrieval using Integrative Indian Buffet Process %@Bahadir Ozdemir,Larry S. Davis %t2014 %cNIPS %f/NIPS/NIPS-2014-3217.pdf %*Searching for Higgs Boson Decay Modes with Deep Learning %@Peter J. Sadowski,Daniel Whiteson,Pierre Baldi %t2014 %cNIPS %f/NIPS/NIPS-2014-3218.pdf %*On Multiplicative Multitask Feature Learning %@Xin Wang,Jinbo Bi,Shipeng Yu,Jiangwen Sun %t2014 %cNIPS %f/NIPS/NIPS-2014-3219.pdf %*Multivariate f-divergence Estimation With Confidence %@Kevin Moon,Alfred Hero %t2014 %cNIPS %f/NIPS/NIPS-2014-3220.pdf %*Generalized Unsupervised Manifold Alignment %@Zhen Cui,Hong Chang,Shiguang Shan,Xilin Chen %t2014 %cNIPS %f/NIPS/NIPS-2014-3221.pdf %*Smoothed Gradients for Stochastic Variational Inference %@Stephan Mandt,David Blei %t2014 %cNIPS %f/NIPS/NIPS-2014-3222.pdf %*Recursive Context Propagation Network for Semantic Scene Labeling %@Abhishek Sharma,Oncel Tuzel,Ming-Yu Liu %t2014 %cNIPS %f/NIPS/NIPS-2014-3223.pdf %*Sparse Random Feature Algorithm as Coordinate Descent in Hilbert Space %@Ian En-Hsu Yen,Ting-Wei Lin,Shou-De Lin,Pradeep K. Ravikumar,Inderjit S. Dhillon %t2014 %cNIPS %f/NIPS/NIPS-2014-3224.pdf %*Optimal Teaching for Limited-Capacity Human Learners %@Kaustubh R. Patil,Xiaojin Zhu,Łukasz Kopeć,Bradley C. Love %t2014 %cNIPS %f/NIPS/NIPS-2014-3225.pdf %*Shaping Social Activity by Incentivizing Users %@Mehrdad Farajtabar,Nan Du,Manuel Gomez-Rodriguez,Isabel Valera,Hongyuan Zha,Le Song %t2014 %cNIPS %f/NIPS/NIPS-2014-3226.pdf %*Analysis of Brain States from Multi-Region LFP Time-Series %@Kyle R. Ulrich,David E. Carlson,Wenzhao Lian,Jana S. Borg,Kafui Dzirasa,Lawrence Carin %t2014 %cNIPS %f/NIPS/NIPS-2014-3227.pdf %*Reputation-based Worker Filtering in Crowdsourcing %@Srikanth Jagabathula,Lakshminarayanan Subramanian,Ashwin Venkataraman %t2014 %cNIPS %f/NIPS/NIPS-2014-3228.pdf %*Multi-Class Deep Boosting %@Vitaly Kuznetsov,Mehryar Mohri,Umar Syed %t2014 %cNIPS %f/NIPS/NIPS-2014-3229.pdf %*A Differential Equation for Modeling Nesterov’s Accelerated Gradient Method: Theory and Insights %@Weijie Su,Stephen Boyd,Emmanuel Candes %t2014 %cNIPS %f/NIPS/NIPS-2014-3230.pdf %*Difference of Convex Functions Programming for Reinforcement Learning %@Bilal Piot,Matthieu Geist,Olivier Pietquin %t2014 %cNIPS %f/NIPS/NIPS-2014-3231.pdf %*Design Principles of the Hippocampal Cognitive Map %@Kimberly L. Stachenfeld,Matthew Botvinick,Samuel J. Gershman %t2014 %cNIPS %f/NIPS/NIPS-2014-3232.pdf %*Deep Symmetry Networks %@Robert Gens,Pedro M. Domingos %t2014 %cNIPS %f/NIPS/NIPS-2014-3233.pdf %*Nonparametric Bayesian inference on multivariate exponential families %@William R. Vega-Brown,Marek Doniec,Nicholas G. Roy %t2014 %cNIPS %f/NIPS/NIPS-2014-3234.pdf %*Optimal rates for k-NN density and mode estimation %@Sanjoy Dasgupta,Samory Kpotufe %t2014 %cNIPS %f/NIPS/NIPS-2014-3235.pdf %*Feedforward Learning of Mixture Models %@Matthew Lawlor,Steven W. Zucker %t2014 %cNIPS %f/NIPS/NIPS-2014-3236.pdf %*Diverse Randomized Agents Vote to Win %@Albert Jiang,Leandro Soriano Marcolino,Ariel D. Procaccia,Tuomas Sandholm,Nisarg Shah,Milind Tambe %t2014 %cNIPS %f/NIPS/NIPS-2014-3237.pdf %*Ranking via Robust Binary Classification %@Hyokun Yun,Parameswaran Raman,S. Vishwanathan %t2014 %cNIPS %f/NIPS/NIPS-2014-3238.pdf %*Distributed Balanced Clustering via Mapping Coresets %@Mohammadhossein Bateni,Aditya Bhaskara,Silvio Lattanzi,Vahab Mirrokni %t2014 %cNIPS %f/NIPS/NIPS-2014-3239.pdf %*Augur: Data-Parallel Probabilistic Modeling %@Jean-Baptiste Tristan,Daniel Huang,Joseph Tassarotti,Adam C. Pocock,Stephen Green,Guy L. Steele %t2014 %cNIPS %f/NIPS/NIPS-2014-3240.pdf %*Learning Mixtures of Ranking Models %@Pranjal Awasthi,Avrim Blum,Or Sheffet,Aravindan Vijayaraghavan %t2014 %cNIPS %f/NIPS/NIPS-2014-3241.pdf %*Controlling privacy in recommender systems %@Yu Xin,Tommi Jaakkola %t2014 %cNIPS %f/NIPS/NIPS-2014-3242.pdf %*Convolutional Kernel Networks %@Julien Mairal,Piotr Koniusz,Zaid Harchaoui,Cordelia Schmid %t2014 %cNIPS %f/NIPS/NIPS-2014-3243.pdf %*Fairness in Multi-Agent Sequential Decision-Making %@Chongjie Zhang,Julie A. Shah %t2014 %cNIPS %f/NIPS/NIPS-2014-3244.pdf %*Submodular meets Structured: Finding Diverse Subsets in Exponentially-Large Structured Item Sets %@Adarsh Prasad,Stefanie Jegelka,Dhruv Batra %t2014 %cNIPS %f/NIPS/NIPS-2014-3245.pdf %*Do Deep Nets Really Need to be Deep? %@Jimmy Ba,Rich Caruana %t2014 %cNIPS %f/NIPS/NIPS-2014-3246.pdf %*Dynamic Rank Factor Model for Text Streams %@Shaobo Han,Lin Du,Esther Salazar,Lawrence Carin %t2014 %cNIPS %f/NIPS/NIPS-2014-3247.pdf %*Generative Adversarial Nets %@Ian Goodfellow,Jean Pouget-Abadie,Mehdi Mirza,Bing Xu,David Warde-Farley,Sherjil Ozair,Aaron Courville,Yoshua Bengio %t2014 %cNIPS %f/NIPS/NIPS-2014-3248.pdf %*Testing Unfaithful Gaussian Graphical Models %@De Wen Soh,Sekhar C. Tatikonda %t2014 %cNIPS %f/NIPS/NIPS-2014-3249.pdf %*Global Sensitivity Analysis for MAP Inference in Graphical Models %@Jasper De Bock,Cassio P. de Campos,Alessandro Antonucci %t2014 %cNIPS %f/NIPS/NIPS-2014-3250.pdf %*Deconvolution of High Dimensional Mixtures via Boosting, with Application to Diffusion-Weighted MRI of Human Brain %@Charles Y. Zheng,Franco Pestilli,Ariel Rokem %t2014 %cNIPS %f/NIPS/NIPS-2014-3251.pdf %*Efficient Minimax Signal Detection on Graphs %@Jing Qian,Venkatesh Saligrama %t2014 %cNIPS %f/NIPS/NIPS-2014-3252.pdf %*Cone-Constrained Principal Component Analysis %@Yash Deshpande,Andrea Montanari,Emile Richard %t2014 %cNIPS %f/NIPS/NIPS-2014-3253.pdf %*On Communication Cost of Distributed Statistical Estimation and Dimensionality %@Ankit Garg,Tengyu Ma,Huy Nguyen %t2014 %cNIPS %f/NIPS/NIPS-2014-3254.pdf %*Computing Nash Equilibria in Generalized Interdependent Security Games %@Hau Chan,Luis E. Ortiz %t2014 %cNIPS %f/NIPS/NIPS-2014-3255.pdf %*Consistent Binary Classification with Generalized Performance Metrics %@Oluwasanmi O. Koyejo,Nagarajan Natarajan,Pradeep K. Ravikumar,Inderjit S. Dhillon %t2014 %cNIPS %f/NIPS/NIPS-2014-3256.pdf %*Greedy Subspace Clustering %@Dohyung Park,Constantine Caramanis,Sujay Sanghavi %t2014 %cNIPS %f/NIPS/NIPS-2014-3257.pdf %*Deterministic Symmetric Positive Semidefinite Matrix Completion %@William E. Bishop,Byron M. Yu %t2014 %cNIPS %f/NIPS/NIPS-2014-3258.pdf %*Multi-Step Stochastic ADMM in High Dimensions: Applications to Sparse Optimization and Matrix Decomposition %@Hanie Sedghi,Anima Anandkumar,Edmond Jonckheere %t2014 %cNIPS %f/NIPS/NIPS-2014-3259.pdf %*Online combinatorial optimization with stochastic decision sets and adversarial losses %@Gergely Neu,Michal Valko %t2014 %cNIPS %f/NIPS/NIPS-2014-3260.pdf %*Sampling for Inference in Probabilistic Models with Fast Bayesian Quadrature %@Tom Gunter,Michael A. Osborne,Roman Garnett,Philipp Hennig,Stephen J. Roberts %t2014 %cNIPS %f/NIPS/NIPS-2014-3261.pdf %*Multi-Scale Spectral Decomposition of Massive Graphs %@Si Si,Donghyuk Shin,Inderjit S. Dhillon,Beresford N. Parlett %t2014 %cNIPS %f/NIPS/NIPS-2014-3262.pdf %*The limits of squared Euclidean distance regularization %@Michal Derezinski,Manfred K. Warmuth %t2014 %cNIPS %f/NIPS/NIPS-2014-3263.pdf %*Bregman Alternating Direction Method of Multipliers %@Huahua Wang,Arindam Banerjee %t2014 %cNIPS %f/NIPS/NIPS-2014-3264.pdf %*Multitask learning meets tensor factorization: task imputation via convex optimization %@Kishan Wimalawarne,Masashi Sugiyama,Ryota Tomioka %t2014 %cNIPS %f/NIPS/NIPS-2014-3265.pdf %*On Model Parallelization and Scheduling Strategies for Distributed Machine Learning %@Seunghak Lee,Jin Kyu Kim,Xun Zheng,Qirong Ho,Garth A. Gibson,Eric P. Xing %t2014 %cNIPS %f/NIPS/NIPS-2014-3266.pdf %*Scalable Inference for Neuronal Connectivity from Calcium Imaging %@Alyson K. Fletcher,Sundeep Rangan %t2014 %cNIPS %f/NIPS/NIPS-2014-3267.pdf %*Structure learning of antiferromagnetic Ising models %@Guy Bresler,David Gamarnik,Devavrat Shah %t2014 %cNIPS %f/NIPS/NIPS-2014-3268.pdf %*The Noisy Power Method: A Meta Algorithm with Applications %@Moritz Hardt,Eric Price %t2014 %cNIPS %f/NIPS/NIPS-2014-3269.pdf %*Algorithm selection by rational metareasoning as a model of human strategy selection %@Falk Lieder,Dillon Plunkett,Jessica B. Hamrick,Stuart J. Russell,Nicholas Hay,Thomas Griffiths %t2014 %cNIPS %f/NIPS/NIPS-2014-3270.pdf %*Extremal Mechanisms for Local Differential Privacy %@Peter Kairouz,Sewoong Oh,Pramod Viswanath %t2014 %cNIPS %f/NIPS/NIPS-2014-3271.pdf %*Global Belief Recursive Neural Networks %@Romain Paulus,Richard Socher,Christopher D. Manning %t2014 %cNIPS %f/NIPS/NIPS-2014-3272.pdf %*A statistical model for tensor PCA %@Emile Richard,Andrea Montanari %t2014 %cNIPS %f/NIPS/NIPS-2014-3273.pdf %*Real-Time Decoding of an Integrate and Fire Encoder %@Shreya Saxena,Munther Dahleh %t2014 %cNIPS %f/NIPS/NIPS-2014-3274.pdf %*Delay-Tolerant Algorithms for Asynchronous Distributed Online Learning %@Brendan McMahan,Matthew Streeter %t2014 %cNIPS %f/NIPS/NIPS-2014-3275.pdf %*On the Number of Linear Regions of Deep Neural Networks %@Guido F. Montufar,Razvan Pascanu,Kyunghyun Cho,Yoshua Bengio %t2014 %cNIPS %f/NIPS/NIPS-2014-3276.pdf %*Identifying and attacking the saddle point problem in high-dimensional non-convex optimization %@Yann N. Dauphin,Razvan Pascanu,Caglar Gulcehre,Kyunghyun Cho,Surya Ganguli,Yoshua Bengio %t2014 %cNIPS %f/NIPS/NIPS-2014-3277.pdf %*Extracting Latent Structure From Multiple Interacting Neural Populations %@Joao Semedo,Amin Zandvakili,Adam Kohn,Christian K. Machens,Byron M. Yu %t2014 %cNIPS %f/NIPS/NIPS-2014-3278.pdf %*Learning with Fredholm Kernels %@Qichao Que,Mikhail Belkin,Yusu Wang %t2014 %cNIPS %f/NIPS/NIPS-2014-3279.pdf %*Hamming Ball Auxiliary Sampling for Factorial Hidden Markov Models %@Michalis Titsias,Christopher Yau %t2014 %cNIPS %f/NIPS/NIPS-2014-3280.pdf %*Optimizing Energy Production Using Policy Search and Predictive State Representations %@Yuri Grinberg,Doina Precup,Michel Gendreau %t2014 %cNIPS %f/NIPS/NIPS-2014-3281.pdf %*Scaling-up Importance Sampling for Markov Logic Networks %@Deepak Venugopal,Vibhav G. Gogate %t2014 %cNIPS %f/NIPS/NIPS-2014-3282.pdf %*Optimal Neural Codes for Control and Estimation %@Alex K. Susemihl,Ron Meir,Manfred Opper %t2014 %cNIPS %f/NIPS/NIPS-2014-3283.pdf %*Graph Clustering With Missing Data: Convex Algorithms and Analysis %@Ramya Korlakai Vinayak,Samet Oymak,Babak Hassibi %t2014 %cNIPS %f/NIPS/NIPS-2014-3284.pdf %*Scale Adaptive Blind Deblurring %@Haichao Zhang,Jianchao Yang %t2014 %cNIPS %f/NIPS/NIPS-2014-3285.pdf %*Weighted importance sampling for off-policy learning with linear function approximation %@A. Rupam Mahmood,Hado P. van Hasselt,Richard S. Sutton %t2014 %cNIPS %f/NIPS/NIPS-2014-3286.pdf %*Information-based learning by agents in unbounded state spaces %@Shariq A. Mobin,James A. Arnemann,Fritz Sommer %t2014 %cNIPS %f/NIPS/NIPS-2014-3287.pdf %*Exponential Concentration of a Density Functional Estimator %@Shashank Singh,Barnabas Poczos %t2014 %cNIPS %f/NIPS/NIPS-2014-3288.pdf %*Scalable Kernel Methods via Doubly Stochastic Gradients %@Bo Dai,Bo Xie,Niao He,Yingyu Liang,Anant Raj,Maria-Florina F. Balcan,Le Song %t2014 %cNIPS %f/NIPS/NIPS-2014-3289.pdf %*Fast Training of Pose Detectors in the Fourier Domain %@João F. Henriques,Pedro Martins,Rui F. Caseiro,Jorge Batista %t2014 %cNIPS %f/NIPS/NIPS-2014-3290.pdf %*An Accelerated Proximal Coordinate Gradient Method %@Qihang Lin,Zhaosong Lu,Lin Xiao %t2014 %cNIPS %f/NIPS/NIPS-2014-3291.pdf %*Communication-Efficient Distributed Dual Coordinate Ascent %@Martin Jaggi,Virginia Smith,Martin Takac,Jonathan Terhorst,Sanjay Krishnan,Thomas Hofmann,Michael I. Jordan %t2014 %cNIPS %f/NIPS/NIPS-2014-3292.pdf %*Simple MAP Inference via Low-Rank Relaxations %@Roy Frostig,Sida Wang,Percy S. Liang,Christopher D. Manning %t2014 %cNIPS %f/NIPS/NIPS-2014-3293.pdf %*A* Sampling %@Chris J. Maddison,Daniel Tarlow,Tom Minka %t2014 %cNIPS %f/NIPS/NIPS-2014-3294.pdf %*A Bayesian model for identifying hierarchically organised states in neural population activity %@Patrick Putzky,Florian Franzen,Giacomo Bassetto,Jakob H. Macke %t2014 %cNIPS %f/NIPS/NIPS-2014-3295.pdf %*Sequence to Sequence Learning with Neural Networks %@Ilya Sutskever,Oriol Vinyals,Quoc V. Le %t2014 %cNIPS %f/NIPS/NIPS-2014-3296.pdf %*Improved Distributed Principal Component Analysis %@Yingyu Liang,Maria-Florina F. Balcan,Vandana Kanchanapally,David Woodruff %t2014 %cNIPS %f/NIPS/NIPS-2014-3297.pdf %*Sparse Polynomial Learning and Graph Sketching %@Murat Kocaoglu,Karthikeyan Shanmugam,Alexandros G. Dimakis,Adam Klivans %t2014 %cNIPS %f/NIPS/NIPS-2014-3298.pdf %*Tight Continuous Relaxation of the Balanced k-Cut Problem %@Syama Sundar Rangapuram,Pramod Kaushik Mudrakarta,Matthias Hein %t2014 %cNIPS %f/NIPS/NIPS-2014-3299.pdf %*Mondrian Forests: Efficient Online Random Forests %@Balaji Lakshminarayanan,Daniel M. Roy,Yee Whye Teh %t2014 %cNIPS %f/NIPS/NIPS-2014-3300.pdf %*Expectation-Maximization for Learning Determinantal Point Processes %@Jennifer A. Gillenwater,Alex Kulesza,Emily Fox,Ben Taskar %t2014 %cNIPS %f/NIPS/NIPS-2014-3301.pdf %*Capturing Semantically Meaningful Word Dependencies with an Admixture of Poisson MRFs %@David I. Inouye,Pradeep K. Ravikumar,Inderjit S. Dhillon %t2014 %cNIPS %f/NIPS/NIPS-2014-3302.pdf %*Streaming, Memory Limited Algorithms for Community Detection %@Se-Young Yun,marc lelarge,Alexandre Proutiere %t2014 %cNIPS %f/NIPS/NIPS-2014-3303.pdf %*Content-based recommendations with Poisson factorization %@Prem K. Gopalan,Laurent Charlin,David Blei %t2014 %cNIPS %f/NIPS/NIPS-2014-3304.pdf %*A Statistical Decision-Theoretic Framework for Social Choice %@Hossein Azari Soufiani,David C. Parkes,Lirong Xia %t2014 %cNIPS %f/NIPS/NIPS-2014-3305.pdf %*Compressive Sensing of Signals from a GMM with Sparse Precision Matrices %@Jianbo Yang,Xuejun Liao,Minhua Chen,Lawrence Carin %t2014 %cNIPS %f/NIPS/NIPS-2014-3306.pdf %*Bayesian Sampling Using Stochastic Gradient Thermostats %@Nan Ding,Youhan Fang,Ryan Babbush,Changyou Chen,Robert D. Skeel,Hartmut Neven %t2014 %cNIPS %f/NIPS/NIPS-2014-3307.pdf %*On Sparse Gaussian Chain Graph Models %@Calvin McCarter,Seyoung Kim %t2014 %cNIPS %f/NIPS/NIPS-2014-3308.pdf %*Orbit Regularization %@Renato Negrinho,Andre Martins %t2014 %cNIPS %f/NIPS/NIPS-2014-3309.pdf %*Efficient Minimax Strategies for Square Loss Games %@Wouter M. Koolen,Alan Malek,Peter L. Bartlett %t2014 %cNIPS %f/NIPS/NIPS-2014-3310.pdf %*Large-Margin Convex Polytope Machine %@Alex Kantchelian,Michael C. Tschantz,Ling Huang,Peter L. Bartlett,Anthony D. Joseph,J. D. Tygar %t2014 %cNIPS %f/NIPS/NIPS-2014-3311.pdf %*Distributed Variational Inference in Sparse Gaussian Process Regression and Latent Variable Models %@Yarin Gal,Mark van der Wilk,Carl Rasmussen %t2014 %cNIPS %f/NIPS/NIPS-2014-3312.pdf %*Learning Distributed Representations for Structured Output Prediction %@Vivek Srikumar,Christopher D. Manning %t2014 %cNIPS %f/NIPS/NIPS-2014-3313.pdf %*Convex Deep Learning via Normalized Kernels %@Özlem Aslan,Xinhua Zhang,Dale Schuurmans %t2014 %cNIPS %f/NIPS/NIPS-2014-3314.pdf %*Tight convex relaxations for sparse matrix factorization %@Emile Richard,Guillaume R. Obozinski,Jean-Philippe Vert %t2014 %cNIPS %f/NIPS/NIPS-2014-3315.pdf %*Learning to Search in Branch and Bound Algorithms %@He He,Hal Daume III,Jason M. Eisner %t2014 %cNIPS %f/NIPS/NIPS-2014-3316.pdf %*An Integer Polynomial Programming Based Framework for Lifted MAP Inference %@Somdeb Sarkhel,Deepak Venugopal,Parag Singla,Vibhav G. Gogate %t2014 %cNIPS %f/NIPS/NIPS-2014-3317.pdf %*Conditional Random Field Autoencoders for Unsupervised Structured Prediction %@Waleed Ammar,Chris Dyer,Noah A. Smith %t2014 %cNIPS %f/NIPS/NIPS-2014-3318.pdf %*How transferable are features in deep neural networks? %@Jason Yosinski,Jeff Clune,Yoshua Bengio,Hod Lipson %t2014 %cNIPS %f/NIPS/NIPS-2014-3319.pdf %*Accelerated Mini-batch Randomized Block Coordinate Descent Method %@Tuo Zhao,Mo Yu,Yiming Wang,Raman Arora,Han Liu %t2014 %cNIPS %f/NIPS/NIPS-2014-3320.pdf %*Deep Learning for Real-Time Atari Game Play Using Offline Monte-Carlo Tree Search Planning %@Xiaoxiao Guo,Satinder Singh,Honglak Lee,Richard L. Lewis,Xiaoshi Wang %t2014 %cNIPS %f/NIPS/NIPS-2014-3321.pdf %*A Latent Source Model for Online Collaborative Filtering %@Guy Bresler,George H. Chen,Devavrat Shah %t2014 %cNIPS %f/NIPS/NIPS-2014-3322.pdf %*Distributed Bayesian Posterior Sampling via Moment Sharing %@Minjie Xu,Balaji Lakshminarayanan,Yee Whye Teh,Jun Zhu,Bo Zhang %t2014 %cNIPS %f/NIPS/NIPS-2014-3323.pdf %*Learning with Pseudo-Ensembles %@Philip Bachman,Ouais Alsharif,Doina Precup %t2014 %cNIPS %f/NIPS/NIPS-2014-3324.pdf %*Learning Time-Varying Coverage Functions %@Nan Du,Yingyu Liang,Maria-Florina F. Balcan,Le Song %t2014 %cNIPS %f/NIPS/NIPS-2014-3325.pdf %*Tighten after Relax: Minimax-Optimal Sparse PCA in Polynomial Time %@Zhaoran Wang,Huanran Lu,Han Liu %t2014 %cNIPS %f/NIPS/NIPS-2014-3326.pdf %*Discriminative Metric Learning by Neighborhood Gerrymandering %@Shubhendu Trivedi,David Mcallester,Greg Shakhnarovich %t2014 %cNIPS %f/NIPS/NIPS-2014-3327.pdf %*Finding a sparse vector in a subspace: Linear sparsity using alternating directions %@Qing Qu,Ju Sun,John Wright %t2014 %cNIPS %f/NIPS/NIPS-2014-3328.pdf %*Asynchronous Anytime Sequential Monte Carlo %@Brooks Paige,Frank Wood,Arnaud Doucet,Yee Whye Teh %t2014 %cNIPS %f/NIPS/NIPS-2014-3329.pdf %*Discrete Graph Hashing %@Wei Liu,Cun Mu,Sanjiv Kumar,Shih-Fu Chang %t2014 %cNIPS %f/NIPS/NIPS-2014-3330.pdf %*Feedback Detection for Live Predictors %@Stefan Wager,Nick Chamandy,Omkar Muralidharan,Amir Najmi %t2014 %cNIPS %f/NIPS/NIPS-2014-3331.pdf %*Rates of Convergence for Nearest Neighbor Classification %@Kamalika Chaudhuri,Sanjoy Dasgupta %t2014 %cNIPS %f/NIPS/NIPS-2014-3332.pdf %*Consistency of weighted majority votes %@Daniel Berend,Aryeh Kontorovich %t2014 %cNIPS %f/NIPS/NIPS-2014-3333.pdf %*Zero-shot recognition with unreliable attributes %@Dinesh Jayaraman,Kristen Grauman %t2014 %cNIPS %f/NIPS/NIPS-2014-3334.pdf %*Concavity of reweighted Kikuchi approximation %@Po-Ling Loh,Andre Wibisono %t2014 %cNIPS %f/NIPS/NIPS-2014-3335.pdf %*Online Decision-Making in General Combinatorial Spaces %@Arun Rajkumar,Shivani Agarwal %t2014 %cNIPS %f/NIPS/NIPS-2014-3336.pdf %*Fast Multivariate Spatio-temporal Analysis via Low Rank Tensor Learning %@Mohammad Taha Bahadori,Qi (Rose) Yu,Yan Liu %t2014 %cNIPS %f/NIPS/NIPS-2014-3337.pdf %*Clustered factor analysis of multineuronal spike data %@Lars Buesing,Timothy A. Machado,John P. Cunningham,Liam Paninski %t2014 %cNIPS %f/NIPS/NIPS-2014-3338.pdf %*Algorithms for CVaR Optimization in MDPs %@Yinlam Chow,Mohammad Ghavamzadeh %t2014 %cNIPS %f/NIPS/NIPS-2014-3339.pdf %*Factoring Variations in Natural Images with Deep Gaussian Mixture Models %@Aaron van den Oord,Benjamin Schrauwen %t2014 %cNIPS %f/NIPS/NIPS-2014-3340.pdf %*Partition-wise Linear Models %@Hidekazu Oiwa,Ryohei Fujimaki %t2014 %cNIPS %f/NIPS/NIPS-2014-3341.pdf %*LSDA: Large Scale Detection through Adaptation %@Judy Hoffman,Sergio Guadarrama,Eric S. Tzeng,Ronghang Hu,Jeff Donahue,Ross Girshick,Trevor Darrell,Kate Saenko %t2014 %cNIPS %f/NIPS/NIPS-2014-3342.pdf %*Deep Networks with Internal Selective Attention through Feedback Connections %@Marijn F. Stollenga,Jonathan Masci,Faustino Gomez,Juergen Schmidhuber %t2014 %cNIPS %f/NIPS/NIPS-2014-3343.pdf %*Parallel Feature Selection Inspired by Group Testing %@Yingbo Zhou,Utkarsh Porwal,Ce Zhang,Hung Q. Ngo,Long Nguyen,Christopher Ré,Venu Govindaraju %t2014 %cNIPS %f/NIPS/NIPS-2014-3344.pdf %*Low-Rank Time-Frequency Synthesis %@Cédric Févotte,Matthieu Kowalski %t2014 %cNIPS %f/NIPS/NIPS-2014-3345.pdf %*Pre-training of Recurrent Neural Networks via Linear Autoencoders %@Luca Pasa,Alessandro Sperduti %t2014 %cNIPS %f/NIPS/NIPS-2014-3346.pdf %*Semi-supervised Learning with Deep Generative Models %@Diederik P. Kingma,Shakir Mohamed,Danilo Jimenez Rezende,Max Welling %t2014 %cNIPS %f/NIPS/NIPS-2014-3347.pdf %*Signal Aggregate Constraints in Additive Factorial HMMs, with Application to Energy Disaggregation %@Mingjun Zhong,Nigel Goddard,Charles Sutton %t2014 %cNIPS %f/NIPS/NIPS-2014-3348.pdf %*Stochastic variational inference for hidden Markov models %@Nicholas Foti,Jason Xu,Dillon Laird,Emily Fox %t2014 %cNIPS %f/NIPS/NIPS-2014-3349.pdf %*A Wild Bootstrap for Degenerate Kernel Tests %@Kacper P. Chwialkowski,Dino Sejdinovic,Arthur Gretton %t2014 %cNIPS %f/NIPS/NIPS-2014-3350.pdf %*Biclustering Using Message Passing %@Luke O'Connor,Soheil Feizi %t2014 %cNIPS %f/NIPS/NIPS-2014-3351.pdf %*Fast Kernel Learning for Multidimensional Pattern Extrapolation %@Andrew Wilson,Elad Gilboa,John P. Cunningham,Arye Nehorai %t2014 %cNIPS %f/NIPS/NIPS-2014-3352.pdf %*Learning on graphs using Orthonormal Representation is Statistically Consistent %@Rakesh Shivanna,Chiranjib Bhattacharyya %t2014 %cNIPS %f/NIPS/NIPS-2014-3353.pdf %*Spectral k-Support Norm Regularization %@Andrew M. McDonald,Massimiliano Pontil,Dimitris Stamos %t2014 %cNIPS %f/NIPS/NIPS-2014-3354.pdf %*Unsupervised learning of an efficient short-term memory network %@Pietro Vertechi,Wieland Brendel,Christian K. Machens %t2014 %cNIPS %f/NIPS/NIPS-2014-3355.pdf %*Quantized Estimation of Gaussian Sequence Models in Euclidean Balls %@Yuancheng Zhu,John Lafferty %t2014 %cNIPS %f/NIPS/NIPS-2014-3356.pdf %*Learning a Concept Hierarchy from Multi-labeled Documents %@Viet-An Nguyen,Jordan L. Boyd-Graber,Philip Resnik,Jonathan Chang %t2014 %cNIPS %f/NIPS/NIPS-2014-3357.pdf %*Variational Gaussian Process State-Space Models %@Roger Frigola,Yutian Chen,Carl Rasmussen %t2014 %cNIPS %f/NIPS/NIPS-2014-3358.pdf %*Fast Prediction for Large-Scale Kernel Machines %@Cho-Jui Hsieh,Si Si,Inderjit S. Dhillon %t2014 %cNIPS %f/NIPS/NIPS-2014-3359.pdf %*Double or Nothing: Multiplicative Incentive Mechanisms for Crowdsourcing %@Nihar Bhadresh Shah,Denny Zhou %t2015 %cNIPS %f/NIPS/NIPS-2015-3360.pdf %*Learning with Symmetric Label Noise: The Importance of Being Unhinged %@Brendan van Rooyen,Aditya Menon,Robert C. Williamson %t2015 %cNIPS %f/NIPS/NIPS-2015-3361.pdf %*Adaptive Low-Complexity Sequential Inference for Dirichlet Process Mixture Models %@Theodoros Tsiligkaridis,Theodoros Tsiligkaridis,Keith Forsythe %t2015 %cNIPS %f/NIPS/NIPS-2015-3362.pdf %*Covariance-Controlled Adaptive Langevin Thermostat for Large-Scale Bayesian Sampling %@Xiaocheng Shang,Zhanxing Zhu,Benedict Leimkuhler,Amos J. Storkey %t2015 %cNIPS %f/NIPS/NIPS-2015-3363.pdf %*Robust Portfolio Optimization %@Huitong Qiu,Fang Han,Han Liu,Brian Caffo %t2015 %cNIPS %f/NIPS/NIPS-2015-3364.pdf %*Logarithmic Time Online Multiclass prediction %@Anna E. Choromanska,John Langford %t2015 %cNIPS %f/NIPS/NIPS-2015-3365.pdf %*Planar Ultrametrics for Image Segmentation %@Julian E. Yarkony,Charless Fowlkes %t2015 %cNIPS %f/NIPS/NIPS-2015-3366.pdf %*Expressing an Image Stream with a Sequence of Natural Sentences %@Cesc C. Park,Gunhee Kim %t2015 %cNIPS %f/NIPS/NIPS-2015-3367.pdf %*Parallel Correlation Clustering on Big Graphs %@Xinghao Pan,Dimitris Papailiopoulos,Samet Oymak,Benjamin Recht,Kannan Ramchandran,Michael I. Jordan %t2015 %cNIPS %f/NIPS/NIPS-2015-3368.pdf %*Faster R-CNN: Towards Real-Time Object Detection with Region Proposal Networks %@Shaoqing Ren,Kaiming He,Ross Girshick,Jian Sun %t2015 %cNIPS %f/NIPS/NIPS-2015-3369.pdf %*Space-Time Local Embeddings %@Ke Sun,Jun Wang,Alexandros Kalousis,Stephane Marchand-Maillet %t2015 %cNIPS %f/NIPS/NIPS-2015-3370.pdf %*A Convergent Gradient Descent Algorithm for Rank Minimization and Semidefinite Programming from Random Linear Measurements %@Qinqing Zheng,John Lafferty %t2015 %cNIPS %f/NIPS/NIPS-2015-3371.pdf %*Smooth Interactive Submodular Set Cover %@Bryan D. He,Yisong Yue %t2015 %cNIPS %f/NIPS/NIPS-2015-3372.pdf %*Galileo: Perceiving Physical Object Properties by Integrating a Physics Engine with Deep Learning %@Jiajun Wu,Ilker Yildirim,Joseph J. Lim,Bill Freeman,Josh Tenenbaum %t2015 %cNIPS %f/NIPS/NIPS-2015-3373.pdf %*On the Pseudo-Dimension of Nearly Optimal Auctions %@Jamie H. Morgenstern,Tim Roughgarden %t2015 %cNIPS %f/NIPS/NIPS-2015-3374.pdf %*Unlocking neural population non-stationarities using hierarchical dynamics models %@Mijung Park,Gergo Bohner,Jakob H. Macke %t2015 %cNIPS %f/NIPS/NIPS-2015-3375.pdf %*Bayesian Manifold Learning: The Locally Linear Latent Variable Model (LL-LVM) %@Mijung Park,Wittawat Jitkrittum,Ahmad Qamar,Zoltan Szabo,Lars Buesing,Maneesh Sahani %t2015 %cNIPS %f/NIPS/NIPS-2015-3376.pdf %*Fast and Accurate Inference of Plackett–Luce Models %@Lucas Maystre,Matthias Grossglauser %t2015 %cNIPS %f/NIPS/NIPS-2015-3377.pdf %*Probabilistic Line Searches for Stochastic Optimization %@Maren Mahsereci,Philipp Hennig %t2015 %cNIPS %f/NIPS/NIPS-2015-3378.pdf %*Inferring Algorithmic Patterns with Stack-Augmented Recurrent Nets %@Armand Joulin,Tomas Mikolov %t2015 %cNIPS %f/NIPS/NIPS-2015-3379.pdf %*Where are they looking? %@Adria Recasens,Aditya Khosla,Carl Vondrick,Antonio Torralba %t2015 %cNIPS %f/NIPS/NIPS-2015-3380.pdf %*On the Limitation of Spectral Methods: From the Gaussian Hidden Clique Problem to Rank-One Perturbations of Gaussian Tensors %@Andrea Montanari,Daniel Reichman,Ofer Zeitouni %t2015 %cNIPS %f/NIPS/NIPS-2015-3381.pdf %*Measuring Sample Quality with Stein's Method %@Jackson Gorham,Lester Mackey %t2015 %cNIPS %f/NIPS/NIPS-2015-3382.pdf %*Bidirectional Recurrent Convolutional Networks for Multi-Frame Super-Resolution %@Yan Huang,Wei Wang,Liang Wang %t2015 %cNIPS %f/NIPS/NIPS-2015-3383.pdf %*Bounding errors of Expectation-Propagation %@Guillaume P. Dehaene,Simon Barthelmé %t2015 %cNIPS %f/NIPS/NIPS-2015-3384.pdf %*A fast, universal algorithm to learn parametric nonlinear embeddings %@Miguel A. Carreira-Perpinan,Max Vladymyrov %t2015 %cNIPS %f/NIPS/NIPS-2015-3385.pdf %*Texture Synthesis Using Convolutional Neural Networks %@Leon Gatys,Alexander S. Ecker,Matthias Bethge %t2015 %cNIPS %f/NIPS/NIPS-2015-3386.pdf %*Extending Gossip Algorithms to Distributed Estimation of U-statistics %@Igor Colin,Aurélien Bellet,Joseph Salmon,Stéphan Clémençon %t2015 %cNIPS %f/NIPS/NIPS-2015-3387.pdf %*Streaming, Distributed Variational Inference for Bayesian Nonparametrics %@Trevor Campbell,Julian Straub,John W. Fisher III,Jonathan P. How %t2015 %cNIPS %f/NIPS/NIPS-2015-3388.pdf %*Learning visual biases from human imagination %@Carl Vondrick,Hamed Pirsiavash,Aude Oliva,Antonio Torralba %t2015 %cNIPS %f/NIPS/NIPS-2015-3389.pdf %*Smooth and Strong: MAP Inference with Linear Convergence %@Ofer Meshi,Mehrdad Mahdavi,Alex Schwing %t2015 %cNIPS %f/NIPS/NIPS-2015-3390.pdf %*Copeland Dueling Bandits %@Masrour Zoghi,Zohar S. Karnin,Shimon Whiteson,Maarten de Rijke %t2015 %cNIPS %f/NIPS/NIPS-2015-3391.pdf %*Optimal Ridge Detection using Coverage Risk %@Yen-Chi Chen,Christopher R. Genovese,Shirley Ho,Larry Wasserman %t2015 %cNIPS %f/NIPS/NIPS-2015-3392.pdf %*Top-k Multiclass SVM %@Maksim Lapin,Matthias Hein,Bernt Schiele %t2015 %cNIPS %f/NIPS/NIPS-2015-3393.pdf %*Policy Evaluation Using the Ω-Return %@Philip S. Thomas,Scott Niekum,Georgios Theocharous,George Konidaris %t2015 %cNIPS %f/NIPS/NIPS-2015-3394.pdf %*Orthogonal NMF through Subspace Exploration %@Megasthenis Asteris,Dimitris Papailiopoulos,Alexandros G. Dimakis %t2015 %cNIPS %f/NIPS/NIPS-2015-3395.pdf %*Stochastic Online Greedy Learning with Semi-bandit Feedbacks %@Tian Lin,Jian Li,Wei Chen %t2015 %cNIPS %f/NIPS/NIPS-2015-3396.pdf %*Deeply Learning the Messages in Message Passing Inference %@Guosheng Lin,Chunhua Shen,Ian Reid,Anton van den Hengel %t2015 %cNIPS %f/NIPS/NIPS-2015-3397.pdf %*Synaptic Sampling: A Bayesian Approach to Neural Network Plasticity and Rewiring %@David Kappel,Stefan Habenschuss,Robert Legenstein,Wolfgang Maass %t2015 %cNIPS %f/NIPS/NIPS-2015-3398.pdf %*Accelerated Proximal Gradient Methods for Nonconvex Programming %@Huan Li,Zhouchen Lin %t2015 %cNIPS %f/NIPS/NIPS-2015-3399.pdf %*Approximating Sparse PCA from Incomplete Data %@ABHISEK KUNDU,Petros Drineas,Malik Magdon-Ismail %t2015 %cNIPS %f/NIPS/NIPS-2015-3400.pdf %*Nonparametric von Mises Estimators for Entropies, Divergences and Mutual Informations %@Kirthevasan Kandasamy,Akshay Krishnamurthy,Barnabas Poczos,Larry Wasserman,james m. robins %t2015 %cNIPS %f/NIPS/NIPS-2015-3401.pdf %*Column Selection via Adaptive Sampling %@Saurabh Paul,Malik Magdon-Ismail,Petros Drineas %t2015 %cNIPS %f/NIPS/NIPS-2015-3402.pdf %*HONOR: Hybrid Optimization for NOn-convex Regularized problems %@Pinghua Gong,Jieping Ye %t2015 %cNIPS %f/NIPS/NIPS-2015-3403.pdf %*3D Object Proposals for Accurate Object Class Detection %@Xiaozhi Chen,Kaustav Kundu,Yukun Zhu,Andrew G. Berneshawi,Huimin Ma,Sanja Fidler,Raquel Urtasun %t2015 %cNIPS %f/NIPS/NIPS-2015-3404.pdf %*Algorithms with Logarithmic or Sublinear Regret for Constrained Contextual Bandits %@Huasen Wu,R. Srikant,Xin Liu,Chong Jiang %t2015 %cNIPS %f/NIPS/NIPS-2015-3405.pdf %*Tensorizing Neural Networks %@Alexander Novikov,Dmitrii Podoprikhin,Anton Osokin,Dmitry P. Vetrov %t2015 %cNIPS %f/NIPS/NIPS-2015-3406.pdf %*Parallelizing MCMC with Random Partition Trees %@Xiangyu Wang,Fangjian Guo,Katherine A. Heller,David B. Dunson %t2015 %cNIPS %f/NIPS/NIPS-2015-3407.pdf %*A Reduced-Dimension fMRI Shared Response Model %@Po-Hsuan (Cameron) Chen,Janice Chen,Yaara Yeshurun,Uri Hasson,James Haxby,Peter J. Ramadge %t2015 %cNIPS %f/NIPS/NIPS-2015-3408.pdf %*Spectral Learning of Large Structured HMMs for Comparative Epigenomics %@Chicheng Zhang,Jimin Song,Kamalika Chaudhuri,Kevin Chen %t2015 %cNIPS %f/NIPS/NIPS-2015-3409.pdf %*Individual Planning in Infinite-Horizon Multiagent Settings: Inference, Structure and Scalability %@Xia Qu,Prashant Doshi %t2015 %cNIPS %f/NIPS/NIPS-2015-3410.pdf %*Estimating Mixture Models via Mixtures of Polynomials %@Sida Wang,Arun Tejasvi Chaganty,Percy S. Liang %t2015 %cNIPS %f/NIPS/NIPS-2015-3411.pdf %*On the Global Linear Convergence of Frank-Wolfe Optimization Variants %@Simon Lacoste-Julien,Martin Jaggi %t2015 %cNIPS %f/NIPS/NIPS-2015-3412.pdf %*Deep Knowledge Tracing %@Chris Piech,Jonathan Bassen,Jonathan Huang,Surya Ganguli,Mehran Sahami,Leonidas J. Guibas,Jascha Sohl-Dickstein %t2015 %cNIPS %f/NIPS/NIPS-2015-3413.pdf %*Rethinking LDA: Moment Matching for Discrete ICA %@Anastasia Podosinnikova,Francis Bach,Simon Lacoste-Julien %t2015 %cNIPS %f/NIPS/NIPS-2015-3414.pdf %*Efficient Compressive Phase Retrieval with Constrained Sensing Vectors %@Sohail Bahmani,Justin Romberg %t2015 %cNIPS %f/NIPS/NIPS-2015-3415.pdf %*Barrier Frank-Wolfe for Marginal Inference %@Rahul G. Krishnan,Simon Lacoste-Julien,David Sontag %t2015 %cNIPS %f/NIPS/NIPS-2015-3416.pdf %*Learning Theory and Algorithms for Forecasting Non-stationary Time Series %@Vitaly Kuznetsov,Mehryar Mohri %t2015 %cNIPS %f/NIPS/NIPS-2015-3417.pdf %*Compressive spectral embedding: sidestepping the SVD %@Dinesh Ramasamy,Upamanyu Madhow %t2015 %cNIPS %f/NIPS/NIPS-2015-3418.pdf %*A Nonconvex Optimization Framework for Low Rank Matrix Estimation %@Tuo Zhao,Zhaoran Wang,Han Liu %t2015 %cNIPS %f/NIPS/NIPS-2015-3419.pdf %*Automatic Variational Inference in Stan %@Alp Kucukelbir,Rajesh Ranganath,Andrew Gelman,David Blei %t2015 %cNIPS %f/NIPS/NIPS-2015-3420.pdf %*Attention-Based Models for Speech Recognition %@Jan K. Chorowski,Dzmitry Bahdanau,Dmitriy Serdyuk,Kyunghyun Cho,Yoshua Bengio %t2015 %cNIPS %f/NIPS/NIPS-2015-3421.pdf %*Closed-form Estimators for High-dimensional Generalized Linear Models %@Eunho Yang,Aurelie C. Lozano,Pradeep K. Ravikumar %t2015 %cNIPS %f/NIPS/NIPS-2015-3422.pdf %*Online F-Measure Optimization %@Róbert Busa-Fekete,Balázs Szörényi,Krzysztof Dembczynski,Eyke Hüllermeier %t2015 %cNIPS %f/NIPS/NIPS-2015-3423.pdf %*Online Rank Elicitation for Plackett-Luce: A Dueling Bandits Approach %@Balázs Szörényi,Róbert Busa-Fekete,Adil Paul,Eyke Hüllermeier %t2015 %cNIPS %f/NIPS/NIPS-2015-3424.pdf %*M-Best-Diverse Labelings for Submodular Energies and Beyond %@Alexander Kirillov,Dmytro Shlezinger,Dmitry P. Vetrov,Carsten Rother,Bogdan Savchynskyy %t2015 %cNIPS %f/NIPS/NIPS-2015-3425.pdf %*Tractable Bayesian Network Structure Learning with Bounded Vertex Cover Number %@Janne H. Korhonen,Pekka Parviainen %t2015 %cNIPS %f/NIPS/NIPS-2015-3426.pdf %*Learning Large-Scale Poisson DAG Models based on OverDispersion Scoring %@Gunwoong Park,Garvesh Raskutti %t2015 %cNIPS %f/NIPS/NIPS-2015-3427.pdf %*Training Restricted Boltzmann Machine via the Thouless-Anderson-Palmer free energy %@Marylou Gabrie,Eric W. Tramel,Florent Krzakala %t2015 %cNIPS %f/NIPS/NIPS-2015-3428.pdf %*Character-level Convolutional Networks for Text Classification %@Xiang Zhang,Junbo Zhao,Yann LeCun %t2015 %cNIPS %f/NIPS/NIPS-2015-3429.pdf %*Robust Feature-Sample Linear Discriminant Analysis for Brain Disorders Diagnosis %@Ehsan Adeli-Mosabbeb,Kim-Han Thung,Le An,Feng Shi,Dinggang Shen %t2015 %cNIPS %f/NIPS/NIPS-2015-3430.pdf %*Black-box optimization of noisy functions with unknown smoothness %@Jean-Bastien grill,Michal Valko,Remi Munos,Remi Munos %t2015 %cNIPS %f/NIPS/NIPS-2015-3431.pdf %*Recovering Communities in the General Stochastic Block Model Without Knowing the Parameters %@Emmanuel Abbe,Colin Sandon %t2015 %cNIPS %f/NIPS/NIPS-2015-3432.pdf %*Deep learning with Elastic Averaging SGD %@Sixin Zhang,Anna E. Choromanska,Yann LeCun %t2015 %cNIPS %f/NIPS/NIPS-2015-3433.pdf %*Monotone k-Submodular Function Maximization with Size Constraints %@Naoto Ohsaka,Yuichi Yoshida %t2015 %cNIPS %f/NIPS/NIPS-2015-3434.pdf %*Active Learning from Weak and Strong Labelers %@Chicheng Zhang,Kamalika Chaudhuri %t2015 %cNIPS %f/NIPS/NIPS-2015-3435.pdf %*On the Optimality of Classifier Chain for Multi-label Classification %@Weiwei Liu,Ivor Tsang %t2015 %cNIPS %f/NIPS/NIPS-2015-3436.pdf %*Robust Regression via Hard Thresholding %@Kush Bhatia,Prateek Jain,Purushottam Kar %t2015 %cNIPS %f/NIPS/NIPS-2015-3437.pdf %*Sparse Local Embeddings for Extreme Multi-label Classification %@Kush Bhatia,Himanshu Jain,Purushottam Kar,Manik Varma,Prateek Jain %t2015 %cNIPS %f/NIPS/NIPS-2015-3438.pdf %*Solving Random Quadratic Systems of Equations Is Nearly as Easy as Solving Linear Systems %@Yuxin Chen,Emmanuel Candes %t2015 %cNIPS %f/NIPS/NIPS-2015-3439.pdf %*A Framework for Individualizing Predictions of Disease Trajectories by Exploiting Multi-Resolution Structure %@Peter Schulam,Suchi Saria %t2015 %cNIPS %f/NIPS/NIPS-2015-3440.pdf %*Subspace Clustering with Irrelevant Features via Robust Dantzig Selector %@Chao Qu,Huan Xu %t2015 %cNIPS %f/NIPS/NIPS-2015-3441.pdf %*Sparse PCA via Bipartite Matchings %@Megasthenis Asteris,Dimitris Papailiopoulos,Anastasios Kyrillidis,Alexandros G. Dimakis %t2015 %cNIPS %f/NIPS/NIPS-2015-3442.pdf %*Fast Randomized Kernel Ridge Regression with Statistical Guarantees %@Ahmed Alaoui,Michael W. Mahoney %t2015 %cNIPS %f/NIPS/NIPS-2015-3443.pdf %*Online Learning for Adversaries with Memory: Price of Past Mistakes %@Oren Anava,Elad Hazan,Shie Mannor %t2015 %cNIPS %f/NIPS/NIPS-2015-3444.pdf %*Convolutional spike-triggered covariance analysis for neural subunit models %@Anqi Wu,Il Memming Park,Jonathan W. Pillow %t2015 %cNIPS %f/NIPS/NIPS-2015-3445.pdf %*Convolutional LSTM Network: A Machine Learning Approach for Precipitation Nowcasting %@Xingjian SHI,Zhourong Chen,Hao Wang,Dit-Yan Yeung,Wai-kin Wong,Wang-chun WOO %t2015 %cNIPS %f/NIPS/NIPS-2015-3446.pdf %*GAP Safe screening rules for sparse multi-task and multi-class models %@Eugene Ndiaye,Olivier Fercoq,Alexandre Gramfort,Joseph Salmon %t2015 %cNIPS %f/NIPS/NIPS-2015-3447.pdf %*Empirical Localization of Homogeneous Divergences on Discrete Sample Spaces %@Takashi Takenouchi,Takafumi Kanamori %t2015 %cNIPS %f/NIPS/NIPS-2015-3448.pdf %*Statistical Model Criticism using Kernel Two Sample Tests %@James R. Lloyd,Zoubin Ghahramani %t2015 %cNIPS %f/NIPS/NIPS-2015-3449.pdf %*Precision-Recall-Gain Curves: PR Analysis Done Right %@Peter Flach,Meelis Kull %t2015 %cNIPS %f/NIPS/NIPS-2015-3450.pdf %*A Generalization of Submodular Cover via the Diminishing Return Property on the Integer Lattice %@Tasuku Soma,Yuichi Yoshida %t2015 %cNIPS %f/NIPS/NIPS-2015-3451.pdf %*Bidirectional Recurrent Neural Networks as Generative Models %@Mathias Berglund,Tapani Raiko,Mikko Honkala,Leo Kärkkäinen,Akos Vetek,Juha T. Karhunen %t2015 %cNIPS %f/NIPS/NIPS-2015-3452.pdf %*Quartz: Randomized Dual Coordinate Ascent with Arbitrary Sampling %@Zheng Qu,Peter Richtarik,Tong Zhang %t2015 %cNIPS %f/NIPS/NIPS-2015-3453.pdf %*Hessian-free Optimization for Learning Deep Multidimensional Recurrent Neural Networks %@Minhyung Cho,Chandra Dhir,Jaehyung Lee %t2015 %cNIPS %f/NIPS/NIPS-2015-3454.pdf %*Large-scale probabilistic predictors with and without guarantees of validity %@Vladimir Vovk,Ivan Petej,Valentina Fedorova %t2015 %cNIPS %f/NIPS/NIPS-2015-3455.pdf %*Shepard Convolutional Neural Networks %@Jimmy SJ Ren,Li Xu,Qiong Yan,Wenxiu Sun %t2015 %cNIPS %f/NIPS/NIPS-2015-3456.pdf %*Matrix Manifold Optimization for Gaussian Mixtures %@Reshad Hosseini,Suvrit Sra %t2015 %cNIPS %f/NIPS/NIPS-2015-3457.pdf %*Semi-supervised Convolutional Neural Networks for Text Categorization via Region Embedding %@Rie Johnson,Tong Zhang %t2015 %cNIPS %f/NIPS/NIPS-2015-3458.pdf %*Parallel Recursive Best-First AND/OR Search for Exact MAP Inference in Graphical Models %@Akihiro Kishimoto,Radu Marinescu,Adi Botea %t2015 %cNIPS %f/NIPS/NIPS-2015-3459.pdf %*Convolutional Neural Networks with Intra-Layer Recurrent Connections for Scene Labeling %@Ming Liang,Xiaolin Hu,Bo Zhang %t2015 %cNIPS %f/NIPS/NIPS-2015-3460.pdf %*Bounding the Cost of Search-Based Lifted Inference %@David B. Smith,Vibhav G. Gogate %t2015 %cNIPS %f/NIPS/NIPS-2015-3461.pdf %*Gradient-free Hamiltonian Monte Carlo with Efficient Kernel Exponential Families %@Heiko Strathmann,Dino Sejdinovic,Samuel Livingstone,Zoltan Szabo,Arthur Gretton %t2015 %cNIPS %f/NIPS/NIPS-2015-3462.pdf %*Linear Multi-Resource Allocation with Semi-Bandit Feedback %@Tor Lattimore,Koby Crammer,Csaba Szepesvari %t2015 %cNIPS %f/NIPS/NIPS-2015-3463.pdf %*Unsupervised Learning by Program Synthesis %@Kevin Ellis,Armando Solar-Lezama,Josh Tenenbaum %t2015 %cNIPS %f/NIPS/NIPS-2015-3464.pdf %*Enforcing balance allows local supervised learning in spiking recurrent networks %@Ralph Bourdoukan,Sophie Denève %t2015 %cNIPS %f/NIPS/NIPS-2015-3465.pdf %*Fast and Guaranteed Tensor Decomposition via Sketching %@Yining Wang,Hsiao-Yu Tung,Alex J. Smola,Anima Anandkumar %t2015 %cNIPS %f/NIPS/NIPS-2015-3466.pdf %*Differentially private subspace clustering %@Yining Wang,Yu-Xiang Wang,Aarti Singh %t2015 %cNIPS %f/NIPS/NIPS-2015-3467.pdf %*Predtron: A Family of Online Algorithms for General Prediction Problems %@Prateek Jain,Nagarajan Natarajan,Ambuj Tewari %t2015 %cNIPS %f/NIPS/NIPS-2015-3468.pdf %*Weighted Theta Functions and Embeddings with Applications to Max-Cut, Clustering and Summarization %@Fredrik D. Johansson,Ankani Chattoraj,Chiranjib Bhattacharyya,Devdatt Dubhashi %t2015 %cNIPS %f/NIPS/NIPS-2015-3469.pdf %*SGD Algorithms based on Incomplete U-statistics: Large-Scale Minimization of Empirical Risk %@Guillaume Papa,Stéphan Clémençon,Aurélien Bellet %t2015 %cNIPS %f/NIPS/NIPS-2015-3470.pdf %*On Top-k Selection in Multi-Armed Bandits and Hidden Bipartite Graphs %@Wei Cao,Jian Li,Yufei Tao,Zhize Li %t2015 %cNIPS %f/NIPS/NIPS-2015-3471.pdf %*The Brain Uses Reliability of Stimulus Information when Making Perceptual Decisions %@Sebastian Bitzer,Stefan Kiebel %t2015 %cNIPS %f/NIPS/NIPS-2015-3472.pdf %*Fast Classification Rates for High-dimensional Gaussian Generative Models %@Tianyang Li,Adarsh Prasad,Pradeep K. Ravikumar %t2015 %cNIPS %f/NIPS/NIPS-2015-3473.pdf %*Fast Distributed k-Center Clustering with Outliers on Massive Data %@Gustavo Malkomes,Matt J. Kusner,Wenlin Chen,Kilian Q. Weinberger,Benjamin Moseley %t2015 %cNIPS %f/NIPS/NIPS-2015-3474.pdf %*Human Memory Search as Initial-Visit Emitting Random Walk %@Kwang-Sung Jun,Xiaojin Zhu,Timothy T. Rogers,Zhuoran Yang,ming yuan %t2015 %cNIPS %f/NIPS/NIPS-2015-3475.pdf %*Non-convex Statistical Optimization for Sparse Tensor Graphical Model %@Wei Sun,Zhaoran Wang,Han Liu,Guang Cheng %t2015 %cNIPS %f/NIPS/NIPS-2015-3476.pdf %*Convergence Rates of Active Learning for Maximum Likelihood Estimation %@Kamalika Chaudhuri,Sham M. Kakade,Praneeth Netrapalli,Sujay Sanghavi %t2015 %cNIPS %f/NIPS/NIPS-2015-3477.pdf %*Weakly-supervised Disentangling with Recurrent Transformations for 3D View Synthesis %@Jimei Yang,Scott E. Reed,Ming-Hsuan Yang,Honglak Lee %t2015 %cNIPS %f/NIPS/NIPS-2015-3478.pdf %*Efficient Exact Gradient Update for training Deep Networks with Very Large Sparse Targets %@Pascal Vincent,Alexandre de Brébisson,Xavier Bouthillier %t2015 %cNIPS %f/NIPS/NIPS-2015-3479.pdf %*Backpropagation for Energy-Efficient Neuromorphic Computing %@Steve K. Esser,Rathinakumar Appuswamy,Paul Merolla,John V. Arthur,Dharmendra S. Modha %t2015 %cNIPS %f/NIPS/NIPS-2015-3480.pdf %*Alternating Minimization for Regression Problems with Vector-valued Outputs %@Prateek Jain,Ambuj Tewari %t2015 %cNIPS %f/NIPS/NIPS-2015-3481.pdf %*Learning both Weights and Connections for Efficient Neural Network %@Song Han,Jeff Pool,John Tran,William Dally %t2015 %cNIPS %f/NIPS/NIPS-2015-3482.pdf %*Optimal Rates for Random Fourier Features %@Bharath Sriperumbudur,Zoltan Szabo %t2015 %cNIPS %f/NIPS/NIPS-2015-3483.pdf %*The Population Posterior and Bayesian Modeling on Streams %@James McInerney,Rajesh Ranganath,David Blei %t2015 %cNIPS %f/NIPS/NIPS-2015-3484.pdf %*Frank-Wolfe Bayesian Quadrature: Probabilistic Integration with Theoretical Guarantees %@François-Xavier Briol,Chris Oates,Mark Girolami,Michael A. Osborne %t2015 %cNIPS %f/NIPS/NIPS-2015-3485.pdf %*Scheduled Sampling for Sequence Prediction with Recurrent Neural Networks %@Samy Bengio,Oriol Vinyals,Navdeep Jaitly,Noam Shazeer %t2015 %cNIPS %f/NIPS/NIPS-2015-3486.pdf %*Unified View of Matrix Completion under General Structural Constraints %@Suriya Gunasekar,Arindam Banerjee,Joydeep Ghosh %t2015 %cNIPS %f/NIPS/NIPS-2015-3487.pdf %*Efficient Output Kernel Learning for Multiple Tasks %@Pratik Jawanpuria,Maksim Lapin,Matthias Hein,Bernt Schiele %t2015 %cNIPS %f/NIPS/NIPS-2015-3488.pdf %*Scalable Adaptation of State Complexity for Nonparametric Hidden Markov Models %@Michael C. Hughes,William T. Stephenson,Erik Sudderth %t2015 %cNIPS %f/NIPS/NIPS-2015-3489.pdf %*Variational Consensus Monte Carlo %@Maxim Rabinovich,Elaine Angelino,Michael I. Jordan %t2015 %cNIPS %f/NIPS/NIPS-2015-3490.pdf %*Practical and Optimal LSH for Angular Distance %@Alexandr Andoni,Piotr Indyk,Thijs Laarhoven,Ilya Razenshteyn,Ludwig Schmidt %t2015 %cNIPS %f/NIPS/NIPS-2015-3491.pdf %*Learning to Linearize Under Uncertainty %@Ross Goroshin,Michael F. Mathieu,Yann LeCun %t2015 %cNIPS %f/NIPS/NIPS-2015-3492.pdf %*Finite-Time Analysis of Projected Langevin Monte Carlo %@Sebastien Bubeck,Ronen Eldan,Joseph Lehec %t2015 %cNIPS %f/NIPS/NIPS-2015-3493.pdf %*Deep Visual Analogy-Making %@Scott E. Reed,Yi Zhang,Yuting Zhang,Honglak Lee %t2015 %cNIPS %f/NIPS/NIPS-2015-3494.pdf %*Matrix Completion from Fewer Entries: Spectral Detectability and Rank Estimation %@Alaa Saade,Florent Krzakala,Lenka Zdeborová %t2015 %cNIPS %f/NIPS/NIPS-2015-3495.pdf %*Online Learning with Adversarial Delays %@Kent Quanrud,Daniel Khashabi %t2015 %cNIPS %f/NIPS/NIPS-2015-3496.pdf %*Multi-Layer Feature Reduction for Tree Structured Group Lasso via Hierarchical Projection %@Jie Wang,Jieping Ye %t2015 %cNIPS %f/NIPS/NIPS-2015-3497.pdf %*Minimum Weight Perfect Matching via Blossom Belief Propagation %@Sung-Soo Ahn,Sejun Park,Michael Chertkov,Jinwoo Shin %t2015 %cNIPS %f/NIPS/NIPS-2015-3498.pdf %*Efficient Thompson Sampling for Online Matrix-Factorization Recommendation %@Jaya Kawale,Hung H. Bui,Branislav Kveton,Long Tran-Thanh,Sanjay Chawla %t2015 %cNIPS %f/NIPS/NIPS-2015-3499.pdf %*Improved Iteration Complexity Bounds of Cyclic Block Coordinate Descent for Convex Problems %@Ruoyu Sun,Mingyi Hong %t2015 %cNIPS %f/NIPS/NIPS-2015-3500.pdf %*Lifted Symmetry Detection and Breaking for MAP Inference %@Timothy Kopp,Parag Singla,Henry Kautz %t2015 %cNIPS %f/NIPS/NIPS-2015-3501.pdf %*Evaluating the statistical significance of biclusters %@Jason D. Lee,Yuekai Sun,Jonathan E. Taylor %t2015 %cNIPS %f/NIPS/NIPS-2015-3502.pdf %*Discriminative Robust Transformation Learning %@Jiaji Huang,Qiang Qiu,Guillermo Sapiro,Robert Calderbank %t2015 %cNIPS %f/NIPS/NIPS-2015-3503.pdf %*Bandits with Unobserved Confounders: A Causal Approach %@Elias Bareinboim,Andrew Forney,Judea Pearl %t2015 %cNIPS %f/NIPS/NIPS-2015-3504.pdf %*Scalable Semi-Supervised Aggregation of Classifiers %@Akshay Balsubramani,Yoav Freund %t2015 %cNIPS %f/NIPS/NIPS-2015-3505.pdf %*Online Learning with Gaussian Payoffs and Side Observations %@Yifan Wu,András György,Csaba Szepesvari %t2015 %cNIPS %f/NIPS/NIPS-2015-3506.pdf %*Private Graphon Estimation for Sparse Graphs %@Christian Borgs,Jennifer Chayes,Adam Smith %t2015 %cNIPS %f/NIPS/NIPS-2015-3507.pdf %*SubmodBoxes: Near-Optimal Search for a Set of Diverse Object Proposals %@Qing Sun,Dhruv Batra %t2015 %cNIPS %f/NIPS/NIPS-2015-3508.pdf %*Fast Second Order Stochastic Backpropagation for Variational Inference %@Kai Fan,Ziteng Wang,Jeff Beck,James Kwok,Katherine A. Heller %t2015 %cNIPS %f/NIPS/NIPS-2015-3509.pdf %*Randomized Block Krylov Methods for Stronger and Faster Approximate Singular Value Decomposition %@Cameron Musco,Christopher Musco %t2015 %cNIPS %f/NIPS/NIPS-2015-3510.pdf %*Cross-Domain Matching for Bag-of-Words Data via Kernel Embeddings of Latent Distributions %@Yuya Yoshikawa,Tomoharu Iwata,Hiroshi Sawada,Takeshi Yamada %t2015 %cNIPS %f/NIPS/NIPS-2015-3511.pdf %*Scalable Inference for Gaussian Process Models with Black-Box Likelihoods %@Amir Dezfouli,Edwin V. Bonilla %t2015 %cNIPS %f/NIPS/NIPS-2015-3512.pdf %*Fast Bidirectional Probability Estimation in Markov Models %@Siddhartha Banerjee,Peter Lofgren %t2015 %cNIPS %f/NIPS/NIPS-2015-3513.pdf %*Probabilistic Variational Bounds for Graphical Models %@Qiang Liu,John W. Fisher III,Alexander T. Ihler %t2015 %cNIPS %f/NIPS/NIPS-2015-3514.pdf %*Linear Response Methods for Accurate Covariance Estimates from Mean Field Variational Bayes %@Ryan J. Giordano,Tamara Broderick,Michael I. Jordan %t2015 %cNIPS %f/NIPS/NIPS-2015-3515.pdf %*Combinatorial Cascading Bandits %@Branislav Kveton,Zheng Wen,Azin Ashkan,Csaba Szepesvari %t2015 %cNIPS %f/NIPS/NIPS-2015-3516.pdf %*Mixing Time Estimation in Reversible Markov Chains from a Single Sample Path %@Daniel J. Hsu,Aryeh Kontorovich,Csaba Szepesvari %t2015 %cNIPS %f/NIPS/NIPS-2015-3517.pdf %*Policy Gradient for Coherent Risk Measures %@Aviv Tamar,Yinlam Chow,Mohammad Ghavamzadeh,Shie Mannor %t2015 %cNIPS %f/NIPS/NIPS-2015-3518.pdf %*Fast Rates for Exp-concave Empirical Risk Minimization %@Tomer Koren,Kfir Levy %t2015 %cNIPS %f/NIPS/NIPS-2015-3519.pdf %*Deep Generative Image Models using a Laplacian Pyramid of Adversarial Networks %@Emily L. Denton,Soumith Chintala,arthur szlam,Rob Fergus %t2015 %cNIPS %f/NIPS/NIPS-2015-3520.pdf %*Decoupled Deep Neural Network for Semi-supervised Semantic Segmentation %@Seunghoon Hong,Hyeonwoo Noh,Bohyung Han %t2015 %cNIPS %f/NIPS/NIPS-2015-3521.pdf %*Equilibrated adaptive learning rates for non-convex optimization %@Yann Dauphin,Harm de Vries,Yoshua Bengio %t2015 %cNIPS %f/NIPS/NIPS-2015-3522.pdf %*BACKSHIFT: Learning causal cyclic graphs from unknown shift interventions %@Dominik Rothenhäusler,Christina Heinze,Jonas Peters,Nicolai Meinshausen %t2015 %cNIPS %f/NIPS/NIPS-2015-3523.pdf %*Risk-Sensitive and Robust Decision-Making: a CVaR Optimization Approach %@Yinlam Chow,Aviv Tamar,Shie Mannor,Marco Pavone %t2015 %cNIPS %f/NIPS/NIPS-2015-3524.pdf %*Asynchronous stochastic convex optimization: the noise is in the noise and SGD don't care %@Sorathan Chaturapruek,John C. Duchi,Christopher Ré %t2015 %cNIPS %f/NIPS/NIPS-2015-3525.pdf %*Lifelong Learning with Non-i.i.d. Tasks %@Anastasia Pentina,Christoph H. Lampert %t2015 %cNIPS %f/NIPS/NIPS-2015-3526.pdf %*Optimal Linear Estimation under Unknown Nonlinear Transform %@Xinyang Yi,Zhaoran Wang,Constantine Caramanis,Han Liu %t2015 %cNIPS %f/NIPS/NIPS-2015-3527.pdf %*Learning with Group Invariant Features: A Kernel Perspective. %@Youssef Mroueh,Stephen Voinea,Tomaso A. Poggio %t2015 %cNIPS %f/NIPS/NIPS-2015-3528.pdf %*Regularized EM Algorithms: A Unified Framework and Statistical Guarantees %@Xinyang Yi,Constantine Caramanis %t2015 %cNIPS %f/NIPS/NIPS-2015-3529.pdf %*Distributionally Robust Logistic Regression %@Soroosh Shafieezadeh-Abadeh,Peyman Mohajerin Esfahani,Daniel Kuhn %t2015 %cNIPS %f/NIPS/NIPS-2015-3530.pdf %*Adaptive Stochastic Optimization: From Sets to Paths %@Zhan Wei Lim,David Hsu,Wee Sun Lee %t2015 %cNIPS %f/NIPS/NIPS-2015-3531.pdf %*Beyond Convexity: Stochastic Quasi-Convex Optimization %@Elad Hazan,Kfir Levy,Shai Shalev-Shwartz %t2015 %cNIPS %f/NIPS/NIPS-2015-3532.pdf %*A Tractable Approximation to Optimal Point Process Filtering: Application to Neural Encoding %@Yuval Harel,Ron Meir,Manfred Opper %t2015 %cNIPS %f/NIPS/NIPS-2015-3533.pdf %*Sum-of-Squares Lower Bounds for Sparse PCA %@Tengyu Ma,Avi Wigderson %t2015 %cNIPS %f/NIPS/NIPS-2015-3534.pdf %*Max-Margin Majority Voting for Learning from Crowds %@TIAN TIAN,Jun Zhu %t2015 %cNIPS %f/NIPS/NIPS-2015-3535.pdf %*Learning with Incremental Iterative Regularization %@Lorenzo Rosasco,Silvia Villa %t2015 %cNIPS %f/NIPS/NIPS-2015-3536.pdf %*Halting in Random Walk Kernels %@Mahito Sugiyama,Karsten Borgwardt %t2015 %cNIPS %f/NIPS/NIPS-2015-3537.pdf %*MCMC for Variationally Sparse Gaussian Processes %@James Hensman,Alexander G. Matthews,Maurizio Filippone,Zoubin Ghahramani %t2015 %cNIPS %f/NIPS/NIPS-2015-3538.pdf %*Less is More: Nyström Computational Regularization %@Alessandro Rudi,Raffaello Camoriano,Lorenzo Rosasco %t2015 %cNIPS %f/NIPS/NIPS-2015-3539.pdf %*Infinite Factorial Dynamical Model %@Isabel Valera,Francisco Ruiz,Lennart Svensson,Fernando Perez-Cruz %t2015 %cNIPS %f/NIPS/NIPS-2015-3540.pdf %*Regularization Path of Cross-Validation Error Lower Bounds %@Atsushi Shibagaki,Yoshiki Suzuki,Masayuki Karasuyama,Ichiro Takeuchi %t2015 %cNIPS %f/NIPS/NIPS-2015-3541.pdf %*Attractor Network Dynamics Enable Preplay and Rapid Path Planning in Maze–like Environments %@Dane S. Corneil,Wulfram Gerstner %t2015 %cNIPS %f/NIPS/NIPS-2015-3542.pdf %*Teaching Machines to Read and Comprehend %@Karl Moritz Hermann,Tomas Kocisky,Edward Grefenstette,Lasse Espeholt,Will Kay,Mustafa Suleyman,Phil Blunsom %t2015 %cNIPS %f/NIPS/NIPS-2015-3543.pdf %*Principal Differences Analysis: Interpretable Characterization of Differences between Distributions %@Jonas W. Mueller,Tommi Jaakkola %t2015 %cNIPS %f/NIPS/NIPS-2015-3544.pdf %*When are Kalman-Filter Restless Bandits Indexable? %@Christopher R. Dance,Tomi Silander %t2015 %cNIPS %f/NIPS/NIPS-2015-3545.pdf %*Efficient Non-greedy Optimization of Decision Trees %@Mohammad Norouzi,Maxwell Collins,Matthew A. Johnson,David J. Fleet,Pushmeet Kohli %t2015 %cNIPS %f/NIPS/NIPS-2015-3546.pdf %*Probabilistic Curve Learning: Coulomb Repulsion and the Electrostatic Gaussian Process %@Ye Wang,David B. Dunson %t2015 %cNIPS %f/NIPS/NIPS-2015-3547.pdf %*Inverse Reinforcement Learning with Locally Consistent Reward Functions %@Quoc Phong Nguyen,Bryan Kian Hsiang Low,Patrick Jaillet %t2015 %cNIPS %f/NIPS/NIPS-2015-3548.pdf %*Communication Complexity of Distributed Convex Learning and Optimization %@Yossi Arjevani,Ohad Shamir %t2015 %cNIPS %f/NIPS/NIPS-2015-3549.pdf %*End-to-end Learning of LDA by Mirror-Descent Back Propagation over a Deep Architecture %@Jianshu Chen,Ji He,Yelong Shen,Lin Xiao,Xiaodong He,Jianfeng Gao,Xinying Song,Li Deng %t2015 %cNIPS %f/NIPS/NIPS-2015-3550.pdf %*Subset Selection by Pareto Optimization %@Chao Qian,Yang Yu,Zhi-Hua Zhou %t2015 %cNIPS %f/NIPS/NIPS-2015-3551.pdf %*On the Accuracy of Self-Normalized Log-Linear Models %@Jacob Andreas,Maxim Rabinovich,Michael I. Jordan,Dan Klein %t2015 %cNIPS %f/NIPS/NIPS-2015-3552.pdf %*Regret Lower Bound and Optimal Algorithm in Finite Stochastic Partial Monitoring %@Junpei Komiyama,Junya Honda,Hiroshi Nakagawa %t2015 %cNIPS %f/NIPS/NIPS-2015-3553.pdf %*Is Approval Voting Optimal Given Approval Votes? %@Ariel D. Procaccia,Nisarg Shah %t2015 %cNIPS %f/NIPS/NIPS-2015-3554.pdf %*Regressive Virtual Metric Learning %@Michaël Perrot,Amaury Habrard %t2015 %cNIPS %f/NIPS/NIPS-2015-3555.pdf %*Analysis of Robust PCA via Local Incoherence %@Huishuai Zhang,Yi Zhou,Yingbin Liang %t2015 %cNIPS %f/NIPS/NIPS-2015-3556.pdf %*Learning to Transduce with Unbounded Memory %@Edward Grefenstette,Karl Moritz Hermann,Mustafa Suleyman,Phil Blunsom %t2015 %cNIPS %f/NIPS/NIPS-2015-3557.pdf %*Max-Margin Deep Generative Models %@Chongxuan Li,Jun Zhu,Tianlin Shi,Bo Zhang %t2015 %cNIPS %f/NIPS/NIPS-2015-3558.pdf %*Spherical Random Features for Polynomial Kernels %@Jeffrey Pennington,Felix Yu,Sanjiv Kumar %t2015 %cNIPS %f/NIPS/NIPS-2015-3559.pdf %*Rectified Factor Networks %@Djork-Arné Clevert,Andreas Mayr,Thomas Unterthiner,Sepp Hochreiter %t2015 %cNIPS %f/NIPS/NIPS-2015-3560.pdf %*Learning Bayesian Networks with Thousands of Variables %@Mauro Scanagatta,Cassio P. de Campos,Giorgio Corani,Marco Zaffalon %t2015 %cNIPS %f/NIPS/NIPS-2015-3561.pdf %*Matrix Completion Under Monotonic Single Index Models %@Ravi Sastry Ganti,Laura Balzano,Rebecca Willett %t2015 %cNIPS %f/NIPS/NIPS-2015-3562.pdf %*Visalogy: Answering Visual Analogy Questions %@Fereshteh Sadeghi,C. Lawrence Zitnick,Ali Farhadi %t2015 %cNIPS %f/NIPS/NIPS-2015-3563.pdf %*Tree-Guided MCMC Inference for Normalized Random Measure Mixture Models %@Juho Lee,Seungjin Choi %t2015 %cNIPS %f/NIPS/NIPS-2015-3564.pdf %*Streaming Min-max Hypergraph Partitioning %@Dan Alistarh,Jennifer Iglesias,Milan Vojnovic %t2015 %cNIPS %f/NIPS/NIPS-2015-3565.pdf %*Collaboratively Learning Preferences from Ordinal Data %@Sewoong Oh,Kiran K. Thekumparampil,Jiaming Xu %t2015 %cNIPS %f/NIPS/NIPS-2015-3566.pdf %*Biologically Inspired Dynamic Textures for Probing Motion Perception %@Jonathan Vacher,Andrew Isaac Meso,Laurent U. Perrinet,Gabriel Peyré %t2015 %cNIPS %f/NIPS/NIPS-2015-3567.pdf %*Generative Image Modeling Using Spatial LSTMs %@Lucas Theis,Matthias Bethge %t2015 %cNIPS %f/NIPS/NIPS-2015-3568.pdf %*Robust PCA with compressed data %@Wooseok Ha,Rina Foygel Barber %t2015 %cNIPS %f/NIPS/NIPS-2015-3569.pdf %*Sampling from Probabilistic Submodular Models %@Alkis Gotovos,Hamed Hassani,Andreas Krause %t2015 %cNIPS %f/NIPS/NIPS-2015-3570.pdf %*COEVOLVE: A Joint Point Process Model for Information Diffusion and Network Co-evolution %@Mehrdad Farajtabar,Yichen Wang,Manuel Gomez-Rodriguez,Shuang Li,Hongyuan Zha,Le Song %t2015 %cNIPS %f/NIPS/NIPS-2015-3571.pdf %*Supervised Learning for Dynamical System Learning %@Ahmed Hefny,Carlton Downey,Geoffrey J. Gordon %t2015 %cNIPS %f/NIPS/NIPS-2015-3572.pdf %*Regret-Based Pruning in Extensive-Form Games %@Noam Brown,Tuomas Sandholm %t2015 %cNIPS %f/NIPS/NIPS-2015-3573.pdf %*Fast Two-Sample Testing with Analytic Representations of Probability Measures %@Kacper P. Chwialkowski,Aaditya Ramdas,Dino Sejdinovic,Arthur Gretton %t2015 %cNIPS %f/NIPS/NIPS-2015-3574.pdf %*Learning to Segment Object Candidates %@Pedro O. Pinheiro,Ronan Collobert,Piotr Dollar %t2015 %cNIPS %f/NIPS/NIPS-2015-3575.pdf %*GP Kernels for Cross-Spectrum Analysis %@Kyle R. Ulrich,David E. Carlson,Kafui Dzirasa,Lawrence Carin %t2015 %cNIPS %f/NIPS/NIPS-2015-3576.pdf %*Secure Multi-party Differential Privacy %@Peter Kairouz,Sewoong Oh,Pramod Viswanath %t2015 %cNIPS %f/NIPS/NIPS-2015-3577.pdf %*Spatial Transformer Networks %@Max Jaderberg,Karen Simonyan,Andrew Zisserman,koray kavukcuoglu %t2015 %cNIPS %f/NIPS/NIPS-2015-3578.pdf %*Anytime Influence Bounds and the Explosive Behavior of Continuous-Time Diffusion Networks %@Kevin Scaman,Rémi Lemonnier,Nicolas Vayatis %t2015 %cNIPS %f/NIPS/NIPS-2015-3579.pdf %*Multi-class SVMs: From Tighter Data-Dependent Generalization Bounds to Novel Algorithms %@Yunwen Lei,Urun Dogan,Alexander Binder,Marius Kloft %t2015 %cNIPS %f/NIPS/NIPS-2015-3580.pdf %*High-dimensional neural spike train analysis with generalized count linear dynamical systems %@YUANJUN GAO,Lars Busing,Krishna V. Shenoy,John P. Cunningham %t2015 %cNIPS %f/NIPS/NIPS-2015-3581.pdf %*Learning with a Wasserstein Loss %@Charlie Frogner,Chiyuan Zhang,Hossein Mobahi,Mauricio Araya,Tomaso A. Poggio %t2015 %cNIPS %f/NIPS/NIPS-2015-3582.pdf %*b-bit Marginal Regression %@Martin Slawski,Ping Li %t2015 %cNIPS %f/NIPS/NIPS-2015-3583.pdf %*Natural Neural Networks %@Guillaume Desjardins,Karen Simonyan,Razvan Pascanu,koray kavukcuoglu %t2015 %cNIPS %f/NIPS/NIPS-2015-3584.pdf %*Optimization Monte Carlo: Efficient and Embarrassingly Parallel Likelihood-Free Inference %@Ted Meeds,Max Welling %t2015 %cNIPS %f/NIPS/NIPS-2015-3585.pdf %*Adaptive Primal-Dual Splitting Methods for Statistical Learning and Image Processing %@Tom Goldstein,Min Li,Xiaoming Yuan %t2015 %cNIPS %f/NIPS/NIPS-2015-3586.pdf %*On some provably correct cases of variational inference for topic models %@Pranjal Awasthi,Andrej Risteski %t2015 %cNIPS %f/NIPS/NIPS-2015-3587.pdf %*Collaborative Filtering with Graph Information: Consistency and Scalable Methods %@Nikhil Rao,Hsiang-Fu Yu,Pradeep K. Ravikumar,Inderjit S. Dhillon %t2015 %cNIPS %f/NIPS/NIPS-2015-3588.pdf %*Combinatorial Bandits Revisited %@Richard Combes,Mohammad Sadegh Talebi Mazraeh Shahi,Alexandre Proutiere,marc lelarge %t2015 %cNIPS %f/NIPS/NIPS-2015-3589.pdf %*Variational Information Maximisation for Intrinsically Motivated Reinforcement Learning %@Shakir Mohamed,Danilo Jimenez Rezende %t2015 %cNIPS %f/NIPS/NIPS-2015-3590.pdf %*A Structural Smoothing Framework For Robust Graph Comparison %@Pinar Yanardag,S.V.N. Vishwanathan %t2015 %cNIPS %f/NIPS/NIPS-2015-3591.pdf %*Competitive Distribution Estimation: Why is Good-Turing Good %@Alon Orlitsky,Ananda Theertha Suresh %t2015 %cNIPS %f/NIPS/NIPS-2015-3592.pdf %*Efficient Learning by Directed Acyclic Graph For Resource Constrained Prediction %@Joseph Wang,Kirill Trapeznikov,Venkatesh Saligrama %t2015 %cNIPS %f/NIPS/NIPS-2015-3593.pdf %*A hybrid sampler for Poisson-Kingman mixture models %@Maria Lomeli,Stefano Favaro,Yee Whye Teh %t2015 %cNIPS %f/NIPS/NIPS-2015-3594.pdf %*An Active Learning Framework using Sparse-Graph Codes for Sparse Polynomials and Graph Sketching %@Xiao Li,Kannan Ramchandran %t2015 %cNIPS %f/NIPS/NIPS-2015-3595.pdf %*Local Smoothness in Variance Reduced Optimization %@Daniel Vainsencher,Han Liu,Tong Zhang %t2015 %cNIPS %f/NIPS/NIPS-2015-3596.pdf %*Saliency, Scale and Information: Towards a Unifying Theory %@Shafin Rahman,Neil Bruce %t2015 %cNIPS %f/NIPS/NIPS-2015-3597.pdf %*Fighting Bandits with a New Kind of Smoothness %@Jacob D. Abernethy,Chansoo Lee,Ambuj Tewari %t2015 %cNIPS %f/NIPS/NIPS-2015-3598.pdf %*Beyond Sub-Gaussian Measurements: High-Dimensional Structured Estimation with Sub-Exponential Designs %@Vidyashankar Sivakumar,Arindam Banerjee,Pradeep K. Ravikumar %t2015 %cNIPS %f/NIPS/NIPS-2015-3599.pdf %*Spectral Norm Regularization of Orthonormal Representations for Graph Transduction %@Rakesh Shivanna,Bibaswan K. Chatterjee,Raman Sankaran,Chiranjib Bhattacharyya,Francis Bach %t2015 %cNIPS %f/NIPS/NIPS-2015-3600.pdf %*Convolutional Networks on Graphs for Learning Molecular Fingerprints %@David K. Duvenaud,Dougal Maclaurin,Jorge Iparraguirre,Rafael Bombarell,Timothy Hirzel,Alan Aspuru-Guzik,Ryan P. Adams %t2015 %cNIPS %f/NIPS/NIPS-2015-3601.pdf %*Mixed Robust/Average Submodular Partitioning: Fast Algorithms, Guarantees, and Applications %@Kai Wei,Rishabh K. Iyer,Shengjie Wang,Wenruo Bai,Jeff A. Bilmes %t2015 %cNIPS %f/NIPS/NIPS-2015-3602.pdf %*Tractable Learning for Complex Probability Queries %@Jessa Bekker,Jesse Davis,Arthur Choi,Adnan Darwiche,Guy Van den Broeck %t2015 %cNIPS %f/NIPS/NIPS-2015-3603.pdf %*StopWasting My Gradients: Practical SVRG %@Reza Harikandeh,Mohamed Osama Ahmed,Alim Virani,Mark Schmidt,Jakub Konečný,Scott Sallinen %t2015 %cNIPS %f/NIPS/NIPS-2015-3604.pdf %*Mind the Gap: A Generative Approach to Interpretable Feature Selection and Extraction %@Been Kim,Julie A. Shah,Finale Doshi-Velez %t2015 %cNIPS %f/NIPS/NIPS-2015-3605.pdf %*A Normative Theory of Adaptive Dimensionality Reduction in Neural Networks %@Cengiz Pehlevan,Dmitri Chklovskii %t2015 %cNIPS %f/NIPS/NIPS-2015-3606.pdf %*On the Convergence of Stochastic Gradient MCMC Algorithms with High-Order Integrators %@Changyou Chen,Nan Ding,Lawrence Carin %t2015 %cNIPS %f/NIPS/NIPS-2015-3607.pdf %*Learning structured densities via infinite dimensional exponential families %@Siqi Sun,mladen kolar,Jinbo Xu %t2015 %cNIPS %f/NIPS/NIPS-2015-3608.pdf %*Are You Talking to a Machine? Dataset and Methods for Multilingual Image Question %@Haoyuan Gao,Junhua Mao,Jie Zhou,Zhiheng Huang,Lei Wang,Wei Xu %t2015 %cNIPS %f/NIPS/NIPS-2015-3609.pdf %*Variance Reduced Stochastic Gradient Descent with Neighbors %@Thomas Hofmann,Aurelien Lucchi,Simon Lacoste-Julien,Brian McWilliams %t2015 %cNIPS %f/NIPS/NIPS-2015-3610.pdf %*Sample Efficient Path Integral Control under Uncertainty %@Yunpeng Pan,Evangelos Theodorou,Michail Kontitsis %t2015 %cNIPS %f/NIPS/NIPS-2015-3611.pdf %*Stochastic Expectation Propagation %@Yingzhen Li,José Miguel Hernández-Lobato,Richard E. Turner %t2015 %cNIPS %f/NIPS/NIPS-2015-3612.pdf %*Scale Up Nonlinear Component Analysis with Doubly Stochastic Gradients %@Bo Xie,Yingyu Liang,Le Song %t2015 %cNIPS %f/NIPS/NIPS-2015-3613.pdf %*Generalization in Adaptive Data Analysis and Holdout Reuse %@Cynthia Dwork,Vitaly Feldman,Moritz Hardt,Toni Pitassi,Omer Reingold,Aaron Roth %t2015 %cNIPS %f/NIPS/NIPS-2015-3614.pdf %*Market Scoring Rules Act As Opinion Pools For Risk-Averse Agents %@Mithun Chakraborty,Sanmay Das %t2015 %cNIPS %f/NIPS/NIPS-2015-3615.pdf %*Sparse Linear Programming via Primal and Dual Augmented Coordinate Descent %@Ian En-Hsu Yen,Kai Zhong,Cho-Jui Hsieh,Pradeep K. Ravikumar,Inderjit S. Dhillon %t2015 %cNIPS %f/NIPS/NIPS-2015-3616.pdf %*Training Very Deep Networks %@Rupesh K. Srivastava,Klaus Greff,Juergen Schmidhuber %t2015 %cNIPS %f/NIPS/NIPS-2015-3617.pdf %*Bayesian Active Model Selection with an Application to Automated Audiometry %@Jacob Gardner,Gustavo Malkomes,Roman Garnett,Kilian Q. Weinberger,Dennis Barbour,John P. Cunningham %t2015 %cNIPS %f/NIPS/NIPS-2015-3618.pdf %*Particle Gibbs for Infinite Hidden Markov Models %@Nilesh Tripuraneni,Shixiang Gu,Hong Ge,Zoubin Ghahramani %t2015 %cNIPS %f/NIPS/NIPS-2015-3619.pdf %*Learning spatiotemporal trajectories from manifold-valued longitudinal data %@Jean-Baptiste SCHIRATTI,Stéphanie ALLASSONNIERE,Olivier Colliot,Stanley DURRLEMAN %t2015 %cNIPS %f/NIPS/NIPS-2015-3620.pdf %*A Bayesian Framework for Modeling Confidence in Perceptual Decision Making %@Koosha Khalvati,Rajesh P. Rao %t2015 %cNIPS %f/NIPS/NIPS-2015-3621.pdf %*Path-SGD: Path-Normalized Optimization in Deep Neural Networks %@Behnam Neyshabur,Ruslan R. Salakhutdinov,Nati Srebro %t2015 %cNIPS %f/NIPS/NIPS-2015-3622.pdf %*On the consistency theory of high dimensional variable screening %@Xiangyu Wang,Chenlei Leng,David B. Dunson %t2015 %cNIPS %f/NIPS/NIPS-2015-3623.pdf %*End-To-End Memory Networks %@Sainbayar Sukhbaatar,arthur szlam,Jason Weston,Rob Fergus %t2015 %cNIPS %f/NIPS/NIPS-2015-3624.pdf %*Spectral Representations for Convolutional Neural Networks %@Oren Rippel,Jasper Snoek,Ryan P. Adams %t2015 %cNIPS %f/NIPS/NIPS-2015-3625.pdf %*Online Gradient Boosting %@Alina Beygelzimer,Elad Hazan,Satyen Kale,Haipeng Luo %t2015 %cNIPS %f/NIPS/NIPS-2015-3626.pdf %*Deep Temporal Sigmoid Belief Networks for Sequence Modeling %@Zhe Gan,Chunyuan Li,Ricardo Henao,David E. Carlson,Lawrence Carin %t2015 %cNIPS %f/NIPS/NIPS-2015-3627.pdf %*Recognizing retinal ganglion cells in the dark %@Emile Richard,Georges A. Goetz,E. J. Chichilnisky %t2015 %cNIPS %f/NIPS/NIPS-2015-3628.pdf %*A Theory of Decision Making Under Dynamic Context %@Michael Shvartsman,Vaibhav Srivastava,Jonathan D. Cohen %t2015 %cNIPS %f/NIPS/NIPS-2015-3629.pdf %*A Gaussian Process Model of Quasar Spectral Energy Distributions %@Andrew Miller,Albert Wu,Jeff Regier,Jon McAuliffe,Dustin Lang,Mr. Prabhat,David Schlegel,Ryan P. Adams %t2015 %cNIPS %f/NIPS/NIPS-2015-3630.pdf %*Hidden Technical Debt in Machine Learning Systems %@D. Sculley,Gary Holt,Daniel Golovin,Eugene Davydov,Todd Phillips,Dietmar Ebner,Vinay Chaudhary,Michael Young,Jean-François Crespo,Dan Dennison %t2015 %cNIPS %f/NIPS/NIPS-2015-3631.pdf %*Local Causal Discovery of Direct Causes and Effects %@Tian Gao,Qiang Ji %t2015 %cNIPS %f/NIPS/NIPS-2015-3632.pdf %*High Dimensional EM Algorithm: Statistical Optimization and Asymptotic Normality %@Zhaoran Wang,Quanquan Gu,Yang Ning,Han Liu %t2015 %cNIPS %f/NIPS/NIPS-2015-3633.pdf %*Revenue Optimization against Strategic Buyers %@Mehryar Mohri,Andres Munoz %t2015 %cNIPS %f/NIPS/NIPS-2015-3634.pdf %*Deep Convolutional Inverse Graphics Network %@Tejas D. Kulkarni,William F. Whitney,Pushmeet Kohli,Josh Tenenbaum %t2015 %cNIPS %f/NIPS/NIPS-2015-3635.pdf %*Sparse and Low-Rank Tensor Decomposition %@Parikshit Shah,Nikhil Rao,Gongguo Tang %t2015 %cNIPS %f/NIPS/NIPS-2015-3636.pdf %*Minimax Time Series Prediction %@Wouter M. Koolen,Alan Malek,Peter L. Bartlett,Yasin Abbasi %t2015 %cNIPS %f/NIPS/NIPS-2015-3637.pdf %*Differentially Private Learning of Structured Discrete Distributions %@Ilias Diakonikolas,Moritz Hardt,Ludwig Schmidt %t2015 %cNIPS %f/NIPS/NIPS-2015-3638.pdf %*Variational Dropout and the Local Reparameterization Trick %@Diederik P. Kingma,Tim Salimans,Max Welling %t2015 %cNIPS %f/NIPS/NIPS-2015-3639.pdf %*Sample Complexity of Learning Mahalanobis Distance Metrics %@Nakul Verma,Kristin Branson %t2015 %cNIPS %f/NIPS/NIPS-2015-3640.pdf %*Learning Wake-Sleep Recurrent Attention Models %@Jimmy Ba,Ruslan R. Salakhutdinov,Roger B. Grosse,Brendan J. Frey %t2015 %cNIPS %f/NIPS/NIPS-2015-3641.pdf %*Robust Gaussian Graphical Modeling with the Trimmed Graphical Lasso %@Eunho Yang,Aurelie C. Lozano %t2015 %cNIPS %f/NIPS/NIPS-2015-3642.pdf %*Testing Closeness With Unequal Sized Samples %@Bhaswar Bhattacharya,Gregory Valiant %t2015 %cNIPS %f/NIPS/NIPS-2015-3643.pdf %*Neural Adaptive Sequential Monte Carlo %@Shixiang Gu,Zoubin Ghahramani,Richard E. Turner %t2015 %cNIPS %f/NIPS/NIPS-2015-3644.pdf %*Local Expectation Gradients for Black Box Variational Inference %@Michalis Titsias,Miguel Lázaro-Gredilla %t2015 %cNIPS %f/NIPS/NIPS-2015-3645.pdf %*On Variance Reduction in Stochastic Gradient Descent and its Asynchronous Variants %@Sashank J. Reddi,Ahmed Hefny,Suvrit Sra,Barnabas Poczos,Alex J. Smola %t2015 %cNIPS %f/NIPS/NIPS-2015-3646.pdf %*NEXT: A System for Real-World Development, Evaluation, and Application of Active Learning %@Kevin G. Jamieson,Lalit Jain,Chris Fernandez,Nicholas J. Glattard,Rob Nowak %t2015 %cNIPS %f/NIPS/NIPS-2015-3647.pdf %*Super-Resolution Off the Grid %@Qingqing Huang,Sham M. Kakade %t2015 %cNIPS %f/NIPS/NIPS-2015-3648.pdf %*Taming the Wild: A Unified Analysis of Hogwild-Style Algorithms %@Christopher M. De Sa,Ce Zhang,Kunle Olukotun,Christopher Ré,Christopher Ré %t2015 %cNIPS %f/NIPS/NIPS-2015-3649.pdf %*The Return of the Gating Network: Combining Generative Models and Discriminative Training in Natural Image Priors %@Dan Rosenbaum,Yair Weiss %t2015 %cNIPS %f/NIPS/NIPS-2015-3650.pdf %*Pointer Networks %@Oriol Vinyals,Meire Fortunato,Navdeep Jaitly %t2015 %cNIPS %f/NIPS/NIPS-2015-3651.pdf %*Associative Memory via a Sparse Recovery Model %@Arya Mazumdar,Ankit Singh Rawat %t2015 %cNIPS %f/NIPS/NIPS-2015-3652.pdf %*Robust Spectral Inference for Joint Stochastic Matrix Factorization %@Moontae Lee,David Bindel,David Mimno %t2015 %cNIPS %f/NIPS/NIPS-2015-3653.pdf %*Fast, Provable Algorithms for Isotonic Regression in all L_p-norms %@Rasmus Kyng,Anup Rao,Sushant Sachdeva %t2015 %cNIPS %f/NIPS/NIPS-2015-3654.pdf %*Adversarial Prediction Games for Multivariate Losses %@Hong Wang,Wei Xing,Kaiser Asif,Brian Ziebart %t2015 %cNIPS %f/NIPS/NIPS-2015-3655.pdf %*Asynchronous Parallel Stochastic Gradient for Nonconvex Optimization %@Xiangru Lian,Yijun Huang,Yuncheng Li,Ji Liu %t2015 %cNIPS %f/NIPS/NIPS-2015-3656.pdf %*Embed to Control: A Locally Linear Latent Dynamics Model for Control from Raw Images %@Manuel Watter,Jost Springenberg,Joschka Boedecker,Martin Riedmiller %t2015 %cNIPS %f/NIPS/NIPS-2015-3657.pdf %*Efficient and Parsimonious Agnostic Active Learning %@Tzu-Kuo Huang,Alekh Agarwal,Daniel J. Hsu,John Langford,Robert E. Schapire %t2015 %cNIPS %f/NIPS/NIPS-2015-3658.pdf %*Softstar: Heuristic-Guided Probabilistic Inference %@Mathew Monfort,Brenden M. Lake,Brenden M. Lake,Brian Ziebart,Patrick Lucey,Josh Tenenbaum %t2015 %cNIPS %f/NIPS/NIPS-2015-3659.pdf %*Grammar as a Foreign Language %@Oriol Vinyals,Łukasz Kaiser,Terry Koo,Slav Petrov,Ilya Sutskever,Geoffrey Hinton %t2015 %cNIPS %f/NIPS/NIPS-2015-3660.pdf %*Regularization-Free Estimation in Trace Regression with Symmetric Positive Semidefinite Matrices %@Martin Slawski,Ping Li,Matthias Hein %t2015 %cNIPS %f/NIPS/NIPS-2015-3661.pdf %*Winner-Take-All Autoencoders %@Alireza Makhzani,Brendan J. Frey %t2015 %cNIPS %f/NIPS/NIPS-2015-3662.pdf %*Deep Poisson Factor Modeling %@Ricardo Henao,Zhe Gan,James Lu,Lawrence Carin %t2015 %cNIPS %f/NIPS/NIPS-2015-3663.pdf %*Bayesian Optimization with Exponential Convergence %@Kenji Kawaguchi,Leslie Pack Kaelbling,Tomás Lozano-Pérez %t2015 %cNIPS %f/NIPS/NIPS-2015-3664.pdf %*Sample Complexity of Episodic Fixed-Horizon Reinforcement Learning %@Christoph Dann,Emma Brunskill %t2015 %cNIPS %f/NIPS/NIPS-2015-3665.pdf %*Learning with Relaxed Supervision %@Jacob Steinhardt,Percy S. Liang %t2015 %cNIPS %f/NIPS/NIPS-2015-3666.pdf %*Subsampled Power Iteration: a Unified Algorithm for Block Models and Planted CSP's %@Vitaly Feldman,Will Perkins,Santosh Vempala %t2015 %cNIPS %f/NIPS/NIPS-2015-3667.pdf %*Accelerated Mirror Descent in Continuous and Discrete Time %@Walid Krichene,Alexandre Bayen,Peter L. Bartlett %t2015 %cNIPS %f/NIPS/NIPS-2015-3668.pdf %*The Human Kernel %@Andrew G. Wilson,Christoph Dann,Chris Lucas,Eric P. Xing %t2015 %cNIPS %f/NIPS/NIPS-2015-3669.pdf %*Action-Conditional Video Prediction using Deep Networks in Atari Games %@Junhyuk Oh,Xiaoxiao Guo,Honglak Lee,Richard L. Lewis,Satinder Singh %t2015 %cNIPS %f/NIPS/NIPS-2015-3670.pdf %*A Pseudo-Euclidean Iteration for Optimal Recovery in Noisy ICA %@James R. Voss,Mikhail Belkin,Luis Rademacher %t2015 %cNIPS %f/NIPS/NIPS-2015-3671.pdf %*Distributed Submodular Cover: Succinctly Summarizing Massive Data %@Baharan Mirzasoleiman,Amin Karbasi,Ashwinkumar Badanidiyuru,Andreas Krause %t2015 %cNIPS %f/NIPS/NIPS-2015-3672.pdf %*Community Detection via Measure Space Embedding %@Mark Kozdoba,Shie Mannor %t2015 %cNIPS %f/NIPS/NIPS-2015-3673.pdf %*Basis refinement strategies for linear value function approximation in MDPs %@Gheorghe Comanici,Doina Precup,Prakash Panangaden %t2015 %cNIPS %f/NIPS/NIPS-2015-3674.pdf %*Structured Estimation with Atomic Norms: General Bounds and Applications %@Sheng Chen,Arindam Banerjee %t2015 %cNIPS %f/NIPS/NIPS-2015-3675.pdf %*A Complete Recipe for Stochastic Gradient MCMC %@Yi-An Ma,Tianqi Chen,Emily Fox %t2015 %cNIPS %f/NIPS/NIPS-2015-3676.pdf %*Bandit Smooth Convex Optimization: Improving the Bias-Variance Tradeoff %@Ofer Dekel,Ronen Eldan,Tomer Koren %t2015 %cNIPS %f/NIPS/NIPS-2015-3677.pdf %*Online Prediction at the Limit of Zero Temperature %@Mark Herbster,Stephen Pasteris,Shaona Ghosh %t2015 %cNIPS %f/NIPS/NIPS-2015-3678.pdf %*Learning Continuous Control Policies by Stochastic Value Gradients %@Nicolas Heess,Gregory Wayne,David Silver,Tim Lillicrap,Tom Erez,Yuval Tassa %t2015 %cNIPS %f/NIPS/NIPS-2015-3679.pdf %*Exploring Models and Data for Image Question Answering %@Mengye Ren,Ryan Kiros,Richard Zemel %t2015 %cNIPS %f/NIPS/NIPS-2015-3680.pdf %*Efficient and Robust Automated Machine Learning %@Matthias Feurer,Aaron Klein,Katharina Eggensperger,Jost Springenberg,Manuel Blum,Frank Hutter %t2015 %cNIPS %f/NIPS/NIPS-2015-3681.pdf %*Preconditioned Spectral Descent for Deep Learning %@David E. Carlson,Edo Collins,Ya-Ping Hsieh,Lawrence Carin,Volkan Cevher %t2015 %cNIPS %f/NIPS/NIPS-2015-3682.pdf %*A Recurrent Latent Variable Model for Sequential Data %@Junyoung Chung,Kyle Kastner,Laurent Dinh,Kratarth Goel,Aaron C. Courville,Yoshua Bengio %t2015 %cNIPS %f/NIPS/NIPS-2015-3683.pdf %*Fast Convergence of Regularized Learning in Games %@Vasilis Syrgkanis,Alekh Agarwal,Haipeng Luo,Robert E. Schapire %t2015 %cNIPS %f/NIPS/NIPS-2015-3684.pdf %*Parallel Multi-Dimensional LSTM, With Application to Fast Biomedical Volumetric Image Segmentation %@Marijn F. Stollenga,Wonmin Byeon,Marcus Liwicki,Juergen Schmidhuber %t2015 %cNIPS %f/NIPS/NIPS-2015-3685.pdf %*Reflection, Refraction, and Hamiltonian Monte Carlo %@Hadi Mohasel Afshar,Justin Domke %t2015 %cNIPS %f/NIPS/NIPS-2015-3686.pdf %*The Consistency of Common Neighbors for Link Prediction in Stochastic Blockmodels %@Purnamrita Sarkar,Deepayan Chakrabarti,peter j. bickel %t2015 %cNIPS %f/NIPS/NIPS-2015-3687.pdf %*Nearly Optimal Private LASSO %@Kunal Talwar,Abhradeep Thakurta,Li Zhang %t2015 %cNIPS %f/NIPS/NIPS-2015-3688.pdf %*Convergence Analysis of Prediction Markets via Randomized Subspace Descent %@Rafael Frongillo,Mark D. Reid %t2015 %cNIPS %f/NIPS/NIPS-2015-3689.pdf %*The Poisson Gamma Belief Network %@Mingyuan Zhou,Yulai Cong,Bo Chen %t2015 %cNIPS %f/NIPS/NIPS-2015-3690.pdf %*Convergence rates of sub-sampled Newton methods %@Murat A. Erdogdu,Andrea Montanari %t2015 %cNIPS %f/NIPS/NIPS-2015-3691.pdf %*No-Regret Learning in Bayesian Games %@Jason Hartline,Vasilis Syrgkanis,Eva Tardos %t2015 %cNIPS %f/NIPS/NIPS-2015-3692.pdf %*Statistical Topological Data Analysis - A Kernel Perspective %@Roland Kwitt,Stefan Huber,Marc Niethammer,Weili Lin,Ulrich Bauer %t2015 %cNIPS %f/NIPS/NIPS-2015-3693.pdf %*Semi-supervised Sequence Learning %@Andrew M. Dai,Quoc V. Le %t2015 %cNIPS %f/NIPS/NIPS-2015-3694.pdf %*Structured Transforms for Small-Footprint Deep Learning %@Vikas Sindhwani,Tara Sainath,Sanjiv Kumar %t2015 %cNIPS %f/NIPS/NIPS-2015-3695.pdf %*Rapidly Mixing Gibbs Sampling for a Class of Factor Graphs Using Hierarchy Width %@Christopher M. De Sa,Ce Zhang,Kunle Olukotun,Christopher Ré %t2015 %cNIPS %f/NIPS/NIPS-2015-3696.pdf %*Interpolating Convex and Non-Convex Tensor Decompositions via the Subspace Norm %@Qinqing Zheng,Ryota Tomioka %t2015 %cNIPS %f/NIPS/NIPS-2015-3697.pdf %*BinaryConnect: Training Deep Neural Networks with binary weights during propagations %@Matthieu Courbariaux,Yoshua Bengio,Jean-Pierre David %t2015 %cNIPS %f/NIPS/NIPS-2015-3698.pdf %*Interactive Control of Diverse Complex Characters with Neural Networks %@Igor Mordatch,Kendall Lowrey,Galen Andrew,Zoran Popovic,Emanuel V. Todorov %t2015 %cNIPS %f/NIPS/NIPS-2015-3699.pdf %*Submodular Hamming Metrics %@Jennifer A. Gillenwater,Rishabh K. Iyer,Bethany Lusch,Rahul Kidambi,Jeff A. Bilmes %t2015 %cNIPS %f/NIPS/NIPS-2015-3700.pdf %*A Universal Primal-Dual Convex Optimization Framework %@Alp Yurtsever,Quoc Tran Dinh,Volkan Cevher %t2015 %cNIPS %f/NIPS/NIPS-2015-3701.pdf %*Learning From Small Samples: An Analysis of Simple Decision Heuristics %@Özgür Şimşek,Marcus Buckmann %t2015 %cNIPS %f/NIPS/NIPS-2015-3702.pdf %*Fast and Memory Optimal Low-Rank Matrix Approximation %@Se-Young Yun,marc lelarge,Alexandre Proutiere %t2015 %cNIPS %f/NIPS/NIPS-2015-3703.pdf %*Learnability of Influence in Networks %@Harikrishna Narasimhan,David C. Parkes,Yaron Singer %t2015 %cNIPS %f/NIPS/NIPS-2015-3704.pdf %*Learning Causal Graphs with Small Interventions %@Karthikeyan Shanmugam,Murat Kocaoglu,Alexandros G. Dimakis,Sriram Vishwanath %t2015 %cNIPS %f/NIPS/NIPS-2015-3705.pdf %*Information-theoretic lower bounds for convex optimization with erroneous oracles %@Yaron Singer,Jan Vondrak %t2015 %cNIPS %f/NIPS/NIPS-2015-3706.pdf %*Fixed-Length Poisson MRF: Adding Dependencies to the Multinomial %@David I. Inouye,Pradeep K. Ravikumar,Inderjit S. Dhillon %t2015 %cNIPS %f/NIPS/NIPS-2015-3707.pdf %*Large-Scale Bayesian Multi-Label Learning via Topic-Based Label Embeddings %@Piyush Rai,Changwei Hu,Ricardo Henao,Lawrence Carin %t2015 %cNIPS %f/NIPS/NIPS-2015-3708.pdf %*The Self-Normalized Estimator for Counterfactual Learning %@Adith Swaminathan,Thorsten Joachims %t2015 %cNIPS %f/NIPS/NIPS-2015-3709.pdf %*Fast Lifted MAP Inference via Partitioning %@Somdeb Sarkhel,Parag Singla,Vibhav G. Gogate %t2015 %cNIPS %f/NIPS/NIPS-2015-3710.pdf %*Data Generation as Sequential Decision Making %@Philip Bachman,Doina Precup %t2015 %cNIPS %f/NIPS/NIPS-2015-3711.pdf %*On Elicitation Complexity %@Rafael Frongillo,Ian Kash %t2015 %cNIPS %f/NIPS/NIPS-2015-3712.pdf %*Decomposition Bounds for Marginal MAP %@Wei Ping,Qiang Liu,Alexander T. Ihler %t2015 %cNIPS %f/NIPS/NIPS-2015-3713.pdf %*Discrete Rényi Classifiers %@Meisam Razaviyayn,Farzan Farnia,David Tse %t2015 %cNIPS %f/NIPS/NIPS-2015-3714.pdf %*A class of network models recoverable by spectral clustering %@Yali Wan,Marina Meila %t2015 %cNIPS %f/NIPS/NIPS-2015-3715.pdf %*Skip-Thought Vectors %@Ryan Kiros,Yukun Zhu,Ruslan R. Salakhutdinov,Richard Zemel,Raquel Urtasun,Antonio Torralba,Sanja Fidler %t2015 %cNIPS %f/NIPS/NIPS-2015-3716.pdf %*Rate-Agnostic (Causal) Structure Learning %@Sergey Plis,David Danks,Cynthia Freeman,Vince Calhoun %t2015 %cNIPS %f/NIPS/NIPS-2015-3717.pdf %*Principal Geodesic Analysis for Probability Measures under the Optimal Transport Metric %@Vivien Seguy,Marco Cuturi %t2015 %cNIPS %f/NIPS/NIPS-2015-3718.pdf %*Consistent Multilabel Classification %@Oluwasanmi O. Koyejo,Nagarajan Natarajan,Pradeep K. Ravikumar,Inderjit S. Dhillon %t2015 %cNIPS %f/NIPS/NIPS-2015-3719.pdf %*Parallel Predictive Entropy Search for Batch Global Optimization of Expensive Objective Functions %@Amar Shah,Zoubin Ghahramani %t2015 %cNIPS %f/NIPS/NIPS-2015-3720.pdf %*Cornering Stationary and Restless Mixing Bandits with Remix-UCB %@Julien Audiffren,Liva Ralaivola %t2015 %cNIPS %f/NIPS/NIPS-2015-3721.pdf %*Semi-Supervised Factored Logistic Regression for High-Dimensional Neuroimaging Data %@Danilo Bzdok,Michael Eickenberg,Olivier Grisel,Bertrand Thirion,Gael Varoquaux %t2015 %cNIPS %f/NIPS/NIPS-2015-3722.pdf %*Gaussian Process Random Fields %@David Moore,Stuart J. Russell %t2015 %cNIPS %f/NIPS/NIPS-2015-3723.pdf %*M-Statistic for Kernel Change-Point Detection %@Shuang Li,Yao Xie,Hanjun Dai,Le Song %t2015 %cNIPS %f/NIPS/NIPS-2015-3724.pdf %*Adaptive Online Learning %@Dylan J. Foster,Alexander Rakhlin,Karthik Sridharan %t2015 %cNIPS %f/NIPS/NIPS-2015-3725.pdf %*A Universal Catalyst for First-Order Optimization %@Hongzhou Lin,Julien Mairal,Zaid Harchaoui %t2015 %cNIPS %f/NIPS/NIPS-2015-3726.pdf %*Inference for determinantal point processes without spectral knowledge %@Rémi Bardenet,Michalis Titsias %t2015 %cNIPS %f/NIPS/NIPS-2015-3727.pdf %*Kullback-Leibler Proximal Variational Inference %@Mohammad E. Khan,Pierre Baque,François Fleuret,Pascal Fua %t2015 %cNIPS %f/NIPS/NIPS-2015-3728.pdf %*Semi-Proximal Mirror-Prox for Nonsmooth Composite Minimization %@Niao He,Zaid Harchaoui %t2015 %cNIPS %f/NIPS/NIPS-2015-3729.pdf %*LASSO with Non-linear Measurements is Equivalent to One With Linear Measurements %@CHRISTOS THRAMPOULIDIS,Ehsan Abbasi,Babak Hassibi %t2015 %cNIPS %f/NIPS/NIPS-2015-3730.pdf %*From random walks to distances on unweighted graphs %@Tatsunori Hashimoto,Yi Sun,Tommi Jaakkola %t2015 %cNIPS %f/NIPS/NIPS-2015-3731.pdf %*Bayesian dark knowledge %@Anoop Korattikara Balan,Vivek Rathod,Kevin P. Murphy,Max Welling %t2015 %cNIPS %f/NIPS/NIPS-2015-3732.pdf %*Matrix Completion with Noisy Side Information %@Kai-Yang Chiang,Cho-Jui Hsieh,Inderjit S. Dhillon %t2015 %cNIPS %f/NIPS/NIPS-2015-3733.pdf %*Dependent Multinomial Models Made Easy: Stick-Breaking with the Polya-gamma Augmentation %@Scott Linderman,Matthew Johnson,Ryan P. Adams %t2015 %cNIPS %f/NIPS/NIPS-2015-3734.pdf %*On-the-Job Learning with Bayesian Decision Theory %@Keenon Werling,Arun Tejasvi Chaganty,Percy S. Liang,Christopher D. Manning %t2015 %cNIPS %f/NIPS/NIPS-2015-3735.pdf %*Calibrated Structured Prediction %@Volodymyr Kuleshov,Percy S. Liang %t2015 %cNIPS %f/NIPS/NIPS-2015-3736.pdf %*Learning Structured Output Representation using Deep Conditional Generative Models %@Kihyuk Sohn,Honglak Lee,Xinchen Yan %t2015 %cNIPS %f/NIPS/NIPS-2015-3737.pdf %*Time-Sensitive Recommendation From Recurrent User Activities %@Nan Du,Yichen Wang,Niao He,Jimeng Sun,Le Song %t2015 %cNIPS %f/NIPS/NIPS-2015-3738.pdf %*Learning Stationary Time Series using Gaussian Processes with Nonparametric Kernels %@Felipe Tobar,Thang D. Bui,Richard E. Turner %t2015 %cNIPS %f/NIPS/NIPS-2015-3739.pdf %*A Market Framework for Eliciting Private Data %@Bo Waggoner,Rafael Frongillo,Jacob D. Abernethy %t2015 %cNIPS %f/NIPS/NIPS-2015-3740.pdf %*Lifted Inference Rules With Constraints %@Happy Mittal,Anuj Mahajan,Vibhav G. Gogate,Parag Singla %t2015 %cNIPS %f/NIPS/NIPS-2015-3741.pdf %*Gradient Estimation Using Stochastic Computation Graphs %@John Schulman,Nicolas Heess,Theophane Weber,Pieter Abbeel %t2015 %cNIPS %f/NIPS/NIPS-2015-3742.pdf %*Model-Based Relative Entropy Stochastic Search %@Abbas Abdolmaleki,Rudolf Lioutikov,Jan R. Peters,Nuno Lau,Luis Pualo Reis,Gerhard Neumann %t2015 %cNIPS %f/NIPS/NIPS-2015-3743.pdf %*Semi-supervised Learning with Ladder Networks %@Antti Rasmus,Mathias Berglund,Mikko Honkala,Harri Valpola,Tapani Raiko %t2015 %cNIPS %f/NIPS/NIPS-2015-3744.pdf %*Embedding Inference for Structured Multilabel Prediction %@Farzaneh Mirzazadeh,Siamak Ravanbakhsh,Nan Ding,Dale Schuurmans %t2015 %cNIPS %f/NIPS/NIPS-2015-3745.pdf %*Copula variational inference %@Dustin Tran,David Blei,Edo M. Airoldi %t2015 %cNIPS %f/NIPS/NIPS-2015-3746.pdf %*Recursive Training of 2D-3D Convolutional Networks for Neuronal Boundary Prediction %@Kisuk Lee,Aleksandar Zlateski,Vishwanathan Ashwin,H. Sebastian Seung %t2015 %cNIPS %f/NIPS/NIPS-2015-3747.pdf %*A Dual Augmented Block Minimization Framework for Learning with Limited Memory %@Ian En-Hsu Yen,Shan-Wei Lin,Shou-De Lin %t2015 %cNIPS %f/NIPS/NIPS-2015-3748.pdf %*Optimal Testing for Properties of Distributions %@Jayadev Acharya,Constantinos Daskalakis,Gautam C. Kamath %t2015 %cNIPS %f/NIPS/NIPS-2015-3749.pdf %*Efficient Learning of Continuous-Time Hidden Markov Models for Disease Progression %@Yu-Ying Liu,Shuang Li,Fuxin Li,Le Song,James M. Rehg %t2015 %cNIPS %f/NIPS/NIPS-2015-3750.pdf %*Expectation Particle Belief Propagation %@Thibaut Lienart,Yee Whye Teh,Arnaud Doucet %t2015 %cNIPS %f/NIPS/NIPS-2015-3751.pdf %*Latent Bayesian melding for integrating individual and population models %@Mingjun Zhong,Nigel Goddard,Charles Sutton %t2015 %cNIPS %f/NIPS/NIPS-2015-3752.pdf %*Repeated Games against Budgeted Adversaries %@Jacob D. Abernethy,Manfred K. Warmuth %t2010 %cNIPS %f/NIPS/NIPS-2010-3753.pdf %*Towards Property-Based Classification of Clustering Paradigms %@Margareta Ackerman,Shai Ben-David,David Loker %t2010 %cNIPS %f/NIPS/NIPS-2010-3754.pdf %*Tree-Structured Stick Breaking for Hierarchical Data %@Zoubin Ghahramani,Michael I. Jordan,Ryan P. Adams %t2010 %cNIPS %f/NIPS/NIPS-2010-3755.pdf %*Sparse Instrumental Variables (SPIV) for Genome-Wide Studies %@Paul Mckeigue,Jon Krohn,Amos J. Storkey,Felix V. Agakov %t2010 %cNIPS %f/NIPS/NIPS-2010-3756.pdf %*Fast global convergence rates of gradient methods for high-dimensional statistical recovery %@Alekh Agarwal,Sahand Negahban,Martin J. Wainwright %t2010 %cNIPS %f/NIPS/NIPS-2010-3757.pdf %*Learning Multiple Tasks using Manifold Regularization %@Arvind Agarwal,Samuel Gerber,Hal Daume %t2010 %cNIPS %f/NIPS/NIPS-2010-3758.pdf %*Switched Latent Force Models for Movement Segmentation %@Mauricio Alvarez,Jan R. Peters,Neil D. Lawrence,Bernhard Schölkopf %t2010 %cNIPS %f/NIPS/NIPS-2010-3759.pdf %*A POMDP Extension with Belief-dependent Rewards %@Mauricio Araya,Olivier Buffet,Vincent Thomas,Françcois Charpillet %t2010 %cNIPS %f/NIPS/NIPS-2010-3760.pdf %*Global seismic monitoring as probabilistic inference %@Nimar Arora,Stuart J. Russell,Paul Kidwell,Erik B. Sudderth %t2010 %cNIPS %f/NIPS/NIPS-2010-3761.pdf %*Learning invariant features using the Transformed Indian Buffet Process %@Joseph L. Austerweil,Thomas L. Griffiths %t2010 %cNIPS %f/NIPS/NIPS-2010-3762.pdf %*Supervised Clustering %@Pranjal Awasthi,Reza B. Zadeh %t2010 %cNIPS %f/NIPS/NIPS-2010-3763.pdf %*Occlusion Detection and Motion Estimation with Convex Optimization %@Alper Ayvaci,Michalis Raptis,Stefano Soatto %t2010 %cNIPS %f/NIPS/NIPS-2010-3764.pdf %*Batch Bayesian Optimization via Simulation Matching %@Javad Azimi,Alan Fern,Xiaoli Z. Fern %t2010 %cNIPS %f/NIPS/NIPS-2010-3765.pdf %*A Bayesian Approach to Concept Drift %@Stephen Bach,Mark Maloof %t2010 %cNIPS %f/NIPS/NIPS-2010-3766.pdf %*Auto-Regressive HMM Inference with Incomplete Data for Short-Horizon Wind Forecasting %@Chris Barber,Joseph Bockhorst,Paul Roebber %t2010 %cNIPS %f/NIPS/NIPS-2010-3767.pdf %*The LASSO risk: asymptotic results and real world examples %@Mohsen Bayati,José Pereira,Andrea Montanari %t2010 %cNIPS %f/NIPS/NIPS-2010-3768.pdf %*Extensions of Generalized Binary Search to Group Identification and Exponential Costs %@Gowtham Bellala,Suresh Bhavnani,Clayton Scott %t2010 %cNIPS %f/NIPS/NIPS-2010-3769.pdf %*Label Embedding Trees for Large Multi-Class Tasks %@Samy Bengio,Jason Weston,David Grangier %t2010 %cNIPS %f/NIPS/NIPS-2010-3770.pdf %*Learning Networks of Stochastic Differential Equations %@José Pereira,Morteza Ibrahimi,Andrea Montanari %t2010 %cNIPS %f/NIPS/NIPS-2010-3771.pdf %*Exploiting weakly-labeled Web images to improve object classification: a domain adaptation approach %@Alessandro Bergamo,Lorenzo Torresani %t2010 %cNIPS %f/NIPS/NIPS-2010-3772.pdf %*Online Classification with Specificity Constraints %@Andrey Bernstein,Shie Mannor,Nahum Shimkin %t2010 %cNIPS %f/NIPS/NIPS-2010-3773.pdf %*Agnostic Active Learning Without Constraints %@Alina Beygelzimer,Daniel J. Hsu,John Langford,Tong Zhang %t2010 %cNIPS %f/NIPS/NIPS-2010-3774.pdf %*Inference with Multivariate Heavy-Tails in Linear Models %@Danny Bickson,Carlos Guestrin %t2010 %cNIPS %f/NIPS/NIPS-2010-3775.pdf %*CUR from a Sparse Optimization Viewpoint %@Jacob Bien,Ya Xu,Michael W. Mahoney %t2010 %cNIPS %f/NIPS/NIPS-2010-3776.pdf %*Optimal learning rates for Kernel Conjugate Gradient regression %@Gilles Blanchard,Nicole Krämer %t2010 %cNIPS %f/NIPS/NIPS-2010-3777.pdf %*Simultaneous Object Detection and Ranking with Weak Supervision %@Matthew Blaschko,Andrea Vedaldi,Andrew Zisserman %t2010 %cNIPS %f/NIPS/NIPS-2010-3778.pdf %*Kernel Descriptors for Visual Recognition %@Liefeng Bo,Xiaofeng Ren,Dieter Fox %t2010 %cNIPS %f/NIPS/NIPS-2010-3779.pdf %*Fractionally Predictive Spiking Neurons %@Jaldert Rombouts,Sander M. Bohte %t2010 %cNIPS %f/NIPS/NIPS-2010-3780.pdf %*Gaussian Process Preference Elicitation %@Shengbo Guo,Scott Sanner,Edwin V. Bonilla %t2010 %cNIPS %f/NIPS/NIPS-2010-3781.pdf %*Predictive State Temporal Difference Learning %@Byron Boots,Geoffrey J. Gordon %t2010 %cNIPS %f/NIPS/NIPS-2010-3782.pdf %*Variational Inference over Combinatorial Spaces %@Alexandre Bouchard-côté,Michael I. Jordan %t2010 %cNIPS %f/NIPS/NIPS-2010-3783.pdf %*Bootstrapping Apprenticeship Learning %@Abdeslam Boularias,Brahim Chaib-draa %t2010 %cNIPS %f/NIPS/NIPS-2010-3784.pdf %*Random Projections for k-means Clustering %@Christos Boutsidis,Anastasios Zouzias,Petros Drineas %t2010 %cNIPS %f/NIPS/NIPS-2010-3785.pdf %*Segmentation as Maximum-Weight Independent Set %@William Brendel,Sinisa Todorovic %t2010 %cNIPS %f/NIPS/NIPS-2010-3786.pdf %*Computing Marginal Distributions over Continuous Markov Networks for Statistical Relational Learning %@Matthias Broecheler,Lise Getoor %t2010 %cNIPS %f/NIPS/NIPS-2010-3787.pdf %*Multi-label Multiple Kernel Learning by Stochastic Approximation: Application to Visual Object Recognition %@Serhat Bucak,Rong Jin,Anil K. Jain %t2010 %cNIPS %f/NIPS/NIPS-2010-3788.pdf %*Learning concept graphs from text with stick-breaking priors %@America Chambers,Padhraic Smyth,Mark Steyvers %t2010 %cNIPS %f/NIPS/NIPS-2010-3789.pdf %*Rates of convergence for the cluster tree %@Kamalika Chaudhuri,Sanjoy Dasgupta %t2010 %cNIPS %f/NIPS/NIPS-2010-3790.pdf %*Evidence-Specific Structures for Rich Tractable CRFs %@Anton Chechetka,Carlos Guestrin %t2010 %cNIPS %f/NIPS/NIPS-2010-3791.pdf %*Predictive Subspace Learning for Multi-view Data: a Large Margin Approach %@Ning Chen,Jun Zhu,Eric P. Xing %t2010 %cNIPS %f/NIPS/NIPS-2010-3792.pdf %*Two-Layer Generalization Analysis for Ranking Using Rademacher Average %@Wei Chen,Tie-yan Liu,Zhi-ming Ma %t2010 %cNIPS %f/NIPS/NIPS-2010-3793.pdf %*SpikeAnts, a spiking neuron network modelling the emergence of organization in a complex system %@Sylvain Chevallier,Hél\`ene Paugam-moisy,Michele Sebag %t2010 %cNIPS %f/NIPS/NIPS-2010-3794.pdf %*Movement extraction by detecting dynamics switches and repetitions %@Silvia Chiappa,Jan R. Peters %t2010 %cNIPS %f/NIPS/NIPS-2010-3795.pdf %*Learning sparse dynamic linear systems using stable spline kernels and exponential hyperpriors %@Alessandro Chiuso,Gianluigi Pillonetto %t2010 %cNIPS %f/NIPS/NIPS-2010-3796.pdf %*Universal Kernels on Non-Standard Input Spaces %@Andreas Christmann,Ingo Steinwart %t2010 %cNIPS %f/NIPS/NIPS-2010-3797.pdf %*Causal discovery in multiple models from different experiments %@Tom Claassen,Tom Heskes %t2010 %cNIPS %f/NIPS/NIPS-2010-3798.pdf %*Empirical Risk Minimization with Approximations of Probabilistic Grammars %@Noah A. Smith,Shay B. Cohen %t2010 %cNIPS %f/NIPS/NIPS-2010-3799.pdf %*Mixture of time-warped trajectory models for movement decoding %@Elaine Corbett,Eric Perreault,Konrad Koerding %t2010 %cNIPS %f/NIPS/NIPS-2010-3800.pdf %*Learning Bounds for Importance Weighting %@Corinna Cortes,Yishay Mansour,Mehryar Mohri %t2010 %cNIPS %f/NIPS/NIPS-2010-3801.pdf %*Learning via Gaussian Herding %@Koby Crammer,Daniel D. Lee %t2010 %cNIPS %f/NIPS/NIPS-2010-3802.pdf %*Spatial and anatomical regularization of SVM for brain image analysis %@Remi Cuingnet,Marie Chupin,Habib Benali,Olivier Colliot %t2010 %cNIPS %f/NIPS/NIPS-2010-3803.pdf %*Phone Recognition with the Mean-Covariance Restricted Boltzmann Machine %@George Dahl,Marc'aurelio Ranzato,Abdel-rahman Mohamed,Geoffrey E. Hinton %t2010 %cNIPS %f/NIPS/NIPS-2010-3804.pdf %*Co-regularization Based Semi-supervised Domain Adaptation %@Abhishek Kumar,Avishek Saha,Hal Daume %t2010 %cNIPS %f/NIPS/NIPS-2010-3805.pdf %*Spectral Regularization for Support Estimation %@Ernesto D. Vito,Lorenzo Rosasco,Alessandro Toigo %t2010 %cNIPS %f/NIPS/NIPS-2010-3806.pdf %*Random Projection Trees Revisited %@Aman Dhesi,Purushottam Kar %t2010 %cNIPS %f/NIPS/NIPS-2010-3807.pdf %*Throttling Poisson Processes %@Uwe Dick,Peter Haider,Thomas Vanck,Michael Brückner,Tobias Scheffer %t2010 %cNIPS %f/NIPS/NIPS-2010-3808.pdf %*t-logistic regression %@Nan Ding,S.v.n. Vishwanathan %t2010 %cNIPS %f/NIPS/NIPS-2010-3809.pdf %*Nonparametric Bayesian Policy Priors for Reinforcement Learning %@Finale Doshi-velez,David Wingate,Nicholas Roy,Joshua B. Tenenbaum %t2010 %cNIPS %f/NIPS/NIPS-2010-3810.pdf %*Over-complete representations on recurrent neural networks can support persistent percepts %@Shaul Druckmann,Dmitri B. Chklovskii %t2010 %cNIPS %f/NIPS/NIPS-2010-3811.pdf %*Distributed Dual Averaging In Networks %@Alekh Agarwal,Martin J. Wainwright,John C. Duchi %t2010 %cNIPS %f/NIPS/NIPS-2010-3812.pdf %*Error Propagation for Approximate Policy and Value Iteration %@Amir-massoud Farahmand,Csaba Szepesvári,Rémi Munos %t2010 %cNIPS %f/NIPS/NIPS-2010-3813.pdf %*A Computational Decision Theory for Interactive Assistants %@Alan Fern,Prasad Tadepalli %t2010 %cNIPS %f/NIPS/NIPS-2010-3814.pdf %*Parametric Bandits: The Generalized Linear Case %@Sarah Filippi,Olivier Cappe,Aurélien Garivier,Csaba Szepesvári %t2010 %cNIPS %f/NIPS/NIPS-2010-3815.pdf %*A Novel Kernel for Learning a Neuron Model from Spike Train Data %@Nicholas Fisher,Arunava Banerjee %t2010 %cNIPS %f/NIPS/NIPS-2010-3816.pdf %*Extended Bayesian Information Criteria for Gaussian Graphical Models %@Rina Foygel,Mathias Drton %t2010 %cNIPS %f/NIPS/NIPS-2010-3817.pdf %*Shadow Dirichlet for Restricted Probability Modeling %@Bela Frigyik,Maya Gupta,Yihua Chen %t2010 %cNIPS %f/NIPS/NIPS-2010-3818.pdf %*Size Matters: Metric Visual Search Constraints from Monocular Metadata %@Mario Fritz,Kate Saenko,Trevor Darrell %t2010 %cNIPS %f/NIPS/NIPS-2010-3819.pdf %*A Bayesian Framework for Figure-Ground Interpretation %@Vicky Froyen,Jacob Feldman,Manish Singh %t2010 %cNIPS %f/NIPS/NIPS-2010-3820.pdf %*Attractor Dynamics with Synaptic Depression %@K. Wong,He Wang,Si Wu,Chi Fung %t2010 %cNIPS %f/NIPS/NIPS-2010-3821.pdf %*Learning Kernels with Radiuses of Minimum Enclosing Balls %@Kun Gai,Guangyun Chen,Chang-shui Zhang %t2010 %cNIPS %f/NIPS/NIPS-2010-3822.pdf %*Implicit encoding of prior probabilities in optimal neural populations %@Deep Ganguli,Eero P. Simoncelli %t2010 %cNIPS %f/NIPS/NIPS-2010-3823.pdf %*Short-term memory in neuronal networks through dynamical compressed sensing %@Surya Ganguli,Haim Sompolinsky %t2010 %cNIPS %f/NIPS/NIPS-2010-3824.pdf %*Group Sparse Coding with a Laplacian Scale Mixture Prior %@Pierre Garrigues,Bruno A. Olshausen %t2010 %cNIPS %f/NIPS/NIPS-2010-3825.pdf %*Improvements to the Sequence Memoizer %@Jan Gasthaus,Yee W. Teh %t2010 %cNIPS %f/NIPS/NIPS-2010-3826.pdf %*On Herding and the Perceptron Cycling Theorem %@Andrew Gelfand,Yutian Chen,Laurens Maaten,Max Welling %t2010 %cNIPS %f/NIPS/NIPS-2010-3827.pdf %*Rescaling, thinning or complementing? On goodness-of-fit procedures for point process models and Generalized Linear Models %@Felipe Gerhard,Wulfram Gerstner %t2010 %cNIPS %f/NIPS/NIPS-2010-3828.pdf %*The Neural Costs of Optimal Control %@Samuel Gershman,Robert Wilson %t2010 %cNIPS %f/NIPS/NIPS-2010-3829.pdf %*LSTD with Random Projections %@Mohammad Ghavamzadeh,Alessandro Lazaric,Odalric Maillard,Rémi Munos %t2010 %cNIPS %f/NIPS/NIPS-2010-3830.pdf %*Humans Learn Using Manifolds, Reluctantly %@Tim Rogers,Chuck Kalish,Joseph Harrison,Xiaojin Zhu,Bryan R. Gibson %t2010 %cNIPS %f/NIPS/NIPS-2010-3831.pdf %*Learning Efficient Markov Networks %@Vibhav Gogate,William Webb,Pedro Domingos %t2010 %cNIPS %f/NIPS/NIPS-2010-3832.pdf %*Transduction with Matrix Completion: Three Birds with One Stone %@Andrew Goldberg,Ben Recht,Junming Xu,Robert Nowak,Xiaojin Zhu %t2010 %cNIPS %f/NIPS/NIPS-2010-3833.pdf %*Near-Optimal Bayesian Active Learning with Noisy Observations %@Daniel Golovin,Andreas Krause,Debajyoti Ray %t2010 %cNIPS %f/NIPS/NIPS-2010-3834.pdf %*Discriminative Clustering by Regularized Information Maximization %@Andreas Krause,Pietro Perona,Ryan G. Gomes %t2010 %cNIPS %f/NIPS/NIPS-2010-3835.pdf %*Learning to localise sounds with spiking neural networks %@Dan Goodman,Romain Brette %t2010 %cNIPS %f/NIPS/NIPS-2010-3836.pdf %*Feature Set Embedding for Incomplete Data %@David Grangier,Iain Melvin %t2010 %cNIPS %f/NIPS/NIPS-2010-3837.pdf %*Avoiding False Positive in Multi-Instance Learning %@Yanjun Han,Qing Tao,Jue Wang %t2010 %cNIPS %f/NIPS/NIPS-2010-3838.pdf %*Nonparametric Density Estimation for Stochastic Optimization with an Observable State Variable %@Lauren Hannah,Warren Powell,David M. Blei %t2010 %cNIPS %f/NIPS/NIPS-2010-3839.pdf %*Space-Variant Single-Image Blind Deconvolution for Removing Camera Shake %@Stefan Harmeling,Hirsch Michael,Bernhard Schölkopf %t2010 %cNIPS %f/NIPS/NIPS-2010-3840.pdf %*A Primal-Dual Message-Passing Algorithm for Approximated Large Scale Structured Prediction %@Tamir Hazan,Raquel Urtasun %t2010 %cNIPS %f/NIPS/NIPS-2010-3841.pdf %*An Inverse Power Method for Nonlinear Eigenproblems with Applications in 1-Spectral Clustering and Sparse PCA %@Matthias Hein,Thomas Bühler %t2010 %cNIPS %f/NIPS/NIPS-2010-3842.pdf %*Online Learning for Latent Dirichlet Allocation %@Matthew Hoffman,Francis R. Bach,David M. Blei %t2010 %cNIPS %f/NIPS/NIPS-2010-3843.pdf %*Latent Variable Models for Predicting File Dependencies in Large-Scale Software Development %@Diane Hu,Laurens Maaten,Youngmin Cho,Sorin Lerner,Lawrence K. Saul %t2010 %cNIPS %f/NIPS/NIPS-2010-3844.pdf %*Exact inference and learning for cumulative distribution functions on loopy graphs %@Nebojsa Jojic,Chris Meek,Jim C. Huang %t2010 %cNIPS %f/NIPS/NIPS-2010-3845.pdf %*Predicting Execution Time of Computer Programs Using Sparse Polynomial Regression %@Ling Huang,Jinzhu Jia,Bin Yu,Byung-gon Chun,Petros Maniatis,Mayur Naik %t2010 %cNIPS %f/NIPS/NIPS-2010-3846.pdf %*Active Learning by Querying Informative and Representative Examples %@Sheng-jun Huang,Rong Jin,Zhi-hua Zhou %t2010 %cNIPS %f/NIPS/NIPS-2010-3847.pdf %*Inter-time segment information sharing for non-homogeneous dynamic Bayesian networks %@Dirk Husmeier,Frank Dondelinger,Sophie Lebre %t2010 %cNIPS %f/NIPS/NIPS-2010-3848.pdf %*Deciphering subsampled data: adaptive compressive sampling as a principle of brain communication %@Guy Isely,Christopher Hillar,Fritz Sommer %t2010 %cNIPS %f/NIPS/NIPS-2010-3849.pdf %*Dynamic Infinite Relational Model for Time-varying Relational Data Analysis %@Katsuhiko Ishiguro,Tomoharu Iwata,Naonori Ueda,Joshua B. Tenenbaum %t2010 %cNIPS %f/NIPS/NIPS-2010-3850.pdf %*Hashing Hyperplane Queries to Near Points with Applications to Large-Scale Active Learning %@Prateek Jain,Sudheendra Vijayanarasimhan,Kristen Grauman %t2010 %cNIPS %f/NIPS/NIPS-2010-3851.pdf %*Guaranteed Rank Minimization via Singular Value Projection %@Prateek Jain,Raghu Meka,Inderjit S. Dhillon %t2010 %cNIPS %f/NIPS/NIPS-2010-3852.pdf %*Inductive Regularized Learning of Kernel Functions %@Prateek Jain,Brian Kulis,Inderjit S. Dhillon %t2010 %cNIPS %f/NIPS/NIPS-2010-3853.pdf %*MAP estimation in Binary MRFs via Bipartite Multi-cuts %@Sashank J. Reddi,Sunita Sarawagi,Sundar Vishwanathan %t2010 %cNIPS %f/NIPS/NIPS-2010-3854.pdf %*A Dirty Model for Multi-task Learning %@Ali Jalali,Sujay Sanghavi,Chao Ruan,Pradeep K. Ravikumar %t2010 %cNIPS %f/NIPS/NIPS-2010-3855.pdf %*Lifted Inference Seen from the Other Side : The Tractable Features %@Abhay Jha,Vibhav Gogate,Alexandra Meliou,Dan Suciu %t2010 %cNIPS %f/NIPS/NIPS-2010-3856.pdf %*Factorized Latent Spaces with Structured Sparsity %@Yangqing Jia,Mathieu Salzmann,Trevor Darrell %t2010 %cNIPS %f/NIPS/NIPS-2010-3857.pdf %*Bayesian Action-Graph Games %@Albert X. Jiang,Kevin Leyton-brown %t2010 %cNIPS %f/NIPS/NIPS-2010-3858.pdf %*On a Connection between Importance Sampling and the Likelihood Ratio Policy Gradient %@Tang Jie,Pieter Abbeel %t2010 %cNIPS %f/NIPS/NIPS-2010-3859.pdf %*Linear Complementarity for Regularized Policy Evaluation and Improvement %@Jeffrey Johns,Christopher Painter-wakefield,Ronald Parr %t2010 %cNIPS %f/NIPS/NIPS-2010-3860.pdf %*Synergies in learning words and their referents %@Mark Johnson,Katherine Demuth,Bevan Jones,Michael J. Black %t2010 %cNIPS %f/NIPS/NIPS-2010-3861.pdf %*Structural epitome: a way to summarize one’s visual experience %@Nebojsa Jojic,Alessandro Perina,Vittorio Murino %t2010 %cNIPS %f/NIPS/NIPS-2010-3862.pdf %*Probabilistic Belief Revision with Structural Constraints %@Peter Jones,Venkatesh Saligrama,Sanjoy Mitter %t2010 %cNIPS %f/NIPS/NIPS-2010-3863.pdf %*Efficient Optimization for Discriminative Latent Class Models %@Armand Joulin,Jean Ponce,Francis R. Bach %t2010 %cNIPS %f/NIPS/NIPS-2010-3864.pdf %*Non-Stochastic Bandit Slate Problems %@Satyen Kale,Lev Reyzin,Robert E. Schapire %t2010 %cNIPS %f/NIPS/NIPS-2010-3865.pdf %*Using body-anchored priors for identifying actions in single images %@Leonid Karlinsky,Michael Dinerstein,Shimon Ullman %t2010 %cNIPS %f/NIPS/NIPS-2010-3866.pdf %*Effects of Synaptic Weight Diffusion on Learning in Decision Making Networks %@Kentaro Katahira,Kazuo Okanoya,Masato Okada %t2010 %cNIPS %f/NIPS/NIPS-2010-3867.pdf %*Learning Convolutional Feature Hierarchies for Visual Recognition %@Koray Kavukcuoglu,Pierre Sermanet,Y-lan Boureau,Karol Gregor,Michael Mathieu,Yann L. Cun %t2010 %cNIPS %f/NIPS/NIPS-2010-3868.pdf %*Accounting for network effects in neuronal responses using L1 regularized point process models %@Ryan Kelly,Matthew Smith,Robert Kass,Tai S. Lee %t2010 %cNIPS %f/NIPS/NIPS-2010-3869.pdf %*Variational bounds for mixed-data factor analysis %@Mohammad E. Khan,Guillaume Bouchard,Kevin P. Murphy,Benjamin M. Marlin %t2010 %cNIPS %f/NIPS/NIPS-2010-3870.pdf %*Sparse Coding for Learning Interpretable Spatio-Temporal Primitives %@Taehwan Kim,Gregory Shakhnarovich,Raquel Urtasun %t2010 %cNIPS %f/NIPS/NIPS-2010-3871.pdf %*Regularized estimation of image statistics by Score Matching %@Diederik P. Kingma,Yann L. Cun %t2010 %cNIPS %f/NIPS/NIPS-2010-3872.pdf %*Random Conic Pursuit for Semidefinite Programming %@Ariel Kleiner,Ali Rahimi,Michael I. Jordan %t2010 %cNIPS %f/NIPS/NIPS-2010-3873.pdf %*Energy Disaggregation via Discriminative Sparse Coding %@J. Z. Kolter,Siddharth Batra,Andrew Y. Ng %t2010 %cNIPS %f/NIPS/NIPS-2010-3874.pdf %*Constructing Skill Trees for Reinforcement Learning Agents from Demonstration Trajectories %@George Konidaris,Scott Kuindersma,Roderic Grupen,Andre S. Barreto %t2010 %cNIPS %f/NIPS/NIPS-2010-3875.pdf %*Structured Determinantal Point Processes %@Alex Kulesza,Ben Taskar %t2010 %cNIPS %f/NIPS/NIPS-2010-3876.pdf %*MAP Estimation for Graphical Models by Likelihood Maximization %@Akshat Kumar,Shlomo Zilberstein %t2010 %cNIPS %f/NIPS/NIPS-2010-3877.pdf %*Self-Paced Learning for Latent Variable Models %@M. P. Kumar,Benjamin Packer,Daphne Koller %t2010 %cNIPS %f/NIPS/NIPS-2010-3878.pdf %*Efficient algorithms for learning kernels from multiple similarity matrices with general convex loss functions %@Achintya Kundu,Vikram Tankasali,Chiranjib Bhattacharyya,Aharon Ben-tal %t2010 %cNIPS %f/NIPS/NIPS-2010-3879.pdf %*Evaluation of Rarity of Fingerprints in Forensics %@Chang Su,Sargur Srihari %t2010 %cNIPS %f/NIPS/NIPS-2010-3880.pdf %*Beyond Actions: Discriminative Models for Contextual Group Activities %@Tian Lan,Yang Wang,Weilong Yang,Greg Mori %t2010 %cNIPS %f/NIPS/NIPS-2010-3881.pdf %*Functional Geometry Alignment and Localization of Brain Areas %@Georg Langs,Yanmei Tie,Laura Rigolo,Alexandra Golby,Polina Golland %t2010 %cNIPS %f/NIPS/NIPS-2010-3882.pdf %*Efficient Relational Learning with Hidden Variable Detection %@Ni Lao,Jun Zhu,Liu Xinwang,Yandong Liu,William W. Cohen %t2010 %cNIPS %f/NIPS/NIPS-2010-3883.pdf %*Learning to combine foveal glimpses with a third-order Boltzmann machine %@Hugo Larochelle,Geoffrey E. Hinton %t2010 %cNIPS %f/NIPS/NIPS-2010-3884.pdf %*Categories and Functional Units: An Infinite Hierarchical Model for Brain Activations %@Danial Lashkari,Ramesh Sridharan,Polina Golland %t2010 %cNIPS %f/NIPS/NIPS-2010-3885.pdf %*Identifying Dendritic Processing %@Aurel A. Lazar,Yevgeniy Slutskiy %t2010 %cNIPS %f/NIPS/NIPS-2010-3886.pdf %*Cross Species Expression Analysis using a Dirichlet Process Mixture Model with Latent Matchings %@Ziv Bar-joseph,Hai-son P. Le %t2010 %cNIPS %f/NIPS/NIPS-2010-3887.pdf %*Tiled convolutional neural networks %@Jiquan Ngiam,Zhenghao Chen,Daniel Chia,Pang W. Koh,Quoc V. Le,Andrew Y. Ng %t2010 %cNIPS %f/NIPS/NIPS-2010-3888.pdf %*Estimating Spatial Layout of Rooms using Volumetric Reasoning about Objects and Surfaces %@Abhinav Gupta,Martial Hebert,Takeo Kanade,David M. Blei %t2010 %cNIPS %f/NIPS/NIPS-2010-3889.pdf %*Practical Large-Scale Optimization for Max-norm Regularization %@Jason D. Lee,Ben Recht,Nathan Srebro,Joel Tropp,Ruslan R. Salakhutdinov %t2010 %cNIPS %f/NIPS/NIPS-2010-3890.pdf %*Adaptive Multi-Task Lasso: with Application to eQTL Detection %@Seunghak Lee,Jun Zhu,Eric P. Xing %t2010 %cNIPS %f/NIPS/NIPS-2010-3891.pdf %*Joint Cascade Optimization Using A Product Of Boosted Classifiers %@Leonidas Lefakis,Francois Fleuret %t2010 %cNIPS %f/NIPS/NIPS-2010-3892.pdf %*Learning To Count Objects in Images %@Victor Lempitsky,Andrew Zisserman %t2010 %cNIPS %f/NIPS/NIPS-2010-3893.pdf %*Optimal Web-Scale Tiering as a Flow Problem %@Gilbert Leung,Novi Quadrianto,Kostas Tsioutsiouliklis,Alex J. Smola %t2010 %cNIPS %f/NIPS/NIPS-2010-3894.pdf %*Feature Construction for Inverse Reinforcement Learning %@Sergey Levine,Zoran Popovic,Vladlen Koltun %t2010 %cNIPS %f/NIPS/NIPS-2010-3895.pdf %*Towards Holistic Scene Understanding: Feedback Enabled Cascaded Classification Models %@Congcong Li,Adarsh Kowdle,Ashutosh Saxena,Tsuhan Chen %t2010 %cNIPS %f/NIPS/NIPS-2010-3896.pdf %*Convex Multiple-Instance Learning by Estimating Likelihood Ratio %@Fuxin Li,Cristian Sminchisescu %t2010 %cNIPS %f/NIPS/NIPS-2010-3897.pdf %*Individualized ROI Optimization via Maximization of Group-wise Consistency of Structural and Functional Profiles %@Kaiming Li,Lei Guo,Carlos Faraco,Dajiang Zhu,Fan Deng,Tuo Zhang,Xi Jiang,Degang Zhang,Hanbo Chen,Xintao Hu,Steve Miller,Tianming Liu %t2010 %cNIPS %f/NIPS/NIPS-2010-3898.pdf %*Object Bank: A High-Level Image Representation for Scene Classification & Semantic Feature Sparsification %@Li-jia Li,Hao Su,Li Fei-fei,Eric P. Xing %t2010 %cNIPS %f/NIPS/NIPS-2010-3899.pdf %*b-Bit Minwise Hashing for Estimating Three-Way Similarities %@Ping Li,Arnd Konig,Wenhao Gui %t2010 %cNIPS %f/NIPS/NIPS-2010-3900.pdf %*Construction of Dependent Dirichlet Processes based on Poisson Processes %@Dahua Lin,Eric Grimson,John W. Fisher %t2010 %cNIPS %f/NIPS/NIPS-2010-3901.pdf %*Deep Coding Network %@Yuanqing Lin,Tong Zhang,Shenghuo Zhu,Kai Yu %t2010 %cNIPS %f/NIPS/NIPS-2010-3902.pdf %*Robust Clustering as Ensembles of Affinity Relations %@Hairong Liu,Longin J. Latecki,Shuicheng Yan %t2010 %cNIPS %f/NIPS/NIPS-2010-3903.pdf %*Graph-Valued Regression %@Han Liu,Xi Chen,Larry Wasserman,John D. Lafferty %t2010 %cNIPS %f/NIPS/NIPS-2010-3904.pdf %*Stability Approach to Regularization Selection (StARS) for High Dimensional Graphical Models %@Han Liu,Kathryn Roeder,Larry Wasserman %t2010 %cNIPS %f/NIPS/NIPS-2010-3905.pdf %*Multivariate Dyadic Regression Trees for Sparse Learning Problems %@Han Liu,Xi Chen %t2010 %cNIPS %f/NIPS/NIPS-2010-3906.pdf %*Multi-Stage Dantzig Selector %@Ji Liu,Peter Wonka,Jieping Ye %t2010 %cNIPS %f/NIPS/NIPS-2010-3907.pdf %*Moreau-Yosida Regularization for Grouped Tree Structure Learning %@Jun Liu,Jieping Ye %t2010 %cNIPS %f/NIPS/NIPS-2010-3908.pdf %*Decoding Ipsilateral Finger Movements from ECoG Signals in Humans %@Yuzong Liu,Mohit Sharma,Charles Gaona,Jonathan Breshears,Jarod Roland,Zachary Freudenburg,Eric Leuthardt,Kilian Q. Weinberger %t2010 %cNIPS %f/NIPS/NIPS-2010-3909.pdf %*Approximate Inference by Compilation to Arithmetic Circuits %@Daniel Lowd,Pedro Domingos %t2010 %cNIPS %f/NIPS/NIPS-2010-3910.pdf %*Block Variable Selection in Multivariate Regression and High-dimensional Causal Inference %@Vikas Sindhwani,Aurelie C. Lozano %t2010 %cNIPS %f/NIPS/NIPS-2010-3911.pdf %*Functional form of motion priors in human motion perception %@Hongjing Lu,Tungyou Lin,Alan Lee,Luminita Vese,Alan L. Yuille %t2010 %cNIPS %f/NIPS/NIPS-2010-3912.pdf %*Learning from Candidate Labeling Sets %@Jie Luo,Francesco Orabona %t2010 %cNIPS %f/NIPS/NIPS-2010-3913.pdf %*Decomposing Isotonic Regression for Efficiently Solving Large Problems %@Ronny Luss,Saharon Rosset,Moni Shahar %t2010 %cNIPS %f/NIPS/NIPS-2010-3914.pdf %*Basis Construction from Power Series Expansions of Value Functions %@Sridhar Mahadevan,Bo Liu %t2010 %cNIPS %f/NIPS/NIPS-2010-3915.pdf %*Scrambled Objects for Least-Squares Regression %@Odalric Maillard,Rémi Munos %t2010 %cNIPS %f/NIPS/NIPS-2010-3916.pdf %*Network Flow Algorithms for Structured Sparsity %@Julien Mairal,Rodolphe Jenatton,Francis R. Bach,Guillaume R. Obozinski %t2010 %cNIPS %f/NIPS/NIPS-2010-3917.pdf %*Sphere Embedding: An Application to Part-of-Speech Induction %@Yariv Maron,Elie Bienenstock,Michael James %t2010 %cNIPS %f/NIPS/NIPS-2010-3918.pdf %*Variable margin losses for classifier design %@Hamed Masnadi-shirazi,Nuno Vasconcelos %t2010 %cNIPS %f/NIPS/NIPS-2010-3919.pdf %*Why are some word orders more common than others? A uniform information density account %@Luke Maurits,Dan Navarro,Amy Perfors %t2010 %cNIPS %f/NIPS/NIPS-2010-3920.pdf %*Direct Loss Minimization for Structured Prediction %@Tamir Hazan,Joseph Keshet,David A. McAllester %t2010 %cNIPS %f/NIPS/NIPS-2010-3921.pdf %*Gated Softmax Classification %@Roland Memisevic,Christopher Zach,Marc Pollefeys,Geoffrey E. Hinton %t2010 %cNIPS %f/NIPS/NIPS-2010-3922.pdf %*A Family of Penalty Functions for Structured Sparsity %@Jean Morales,Charles A. Micchelli,Massimiliano Pontil %t2010 %cNIPS %f/NIPS/NIPS-2010-3923.pdf %*PAC-Bayesian Model Selection for Reinforcement Learning %@Mahdi M. Fard,Joelle Pineau %t2010 %cNIPS %f/NIPS/NIPS-2010-3924.pdf %*Subgraph Detection Using Eigenvector L1 Norms %@Benjamin Miller,Nadya Bliss,Patrick J. Wolfe %t2010 %cNIPS %f/NIPS/NIPS-2010-3925.pdf %*A VLSI Implementation of the Adaptive Exponential Integrate-and-Fire Neuron Model %@Sebastian Millner,Andreas Grübl,Karlheinz Meier,Johannes Schemmel,Marc-olivier Schwartz %t2010 %cNIPS %f/NIPS/NIPS-2010-3926.pdf %*Large-Scale Matrix Factorization with Missing Data under Additional Constraints %@Kaushik Mitra,Sameer Sheorey,Rama Chellappa %t2010 %cNIPS %f/NIPS/NIPS-2010-3927.pdf %*Natural Policy Gradient Methods with Parameter-based Exploration for Control Tasks %@Atsushi Miyamae,Yuichi Nagata,Isao Ono,Shigenobu Kobayashi %t2010 %cNIPS %f/NIPS/NIPS-2010-3928.pdf %*An analysis on negative curvature induced by singularity in multi-layer neural-network learning %@Eiji Mizutani,Stuart Dreyfus %t2010 %cNIPS %f/NIPS/NIPS-2010-3929.pdf %*Layer-wise analysis of deep networks with Gaussian kernels %@Grégoire Montavon,Klaus-Robert Müller,Mikio L. Braun %t2010 %cNIPS %f/NIPS/NIPS-2010-3930.pdf %*Probabilistic latent variable models for distinguishing between cause and effect %@Oliver Stegle,Dominik Janzing,Kun Zhang,Joris M. Mooij,Bernhard Schölkopf %t2010 %cNIPS %f/NIPS/NIPS-2010-3931.pdf %*Epitome driven 3-D Diffusion Tensor image segmentation: on extracting specific structures %@Kamiya Motwani,Nagesh Adluru,Chris Hinrichs,Andrew Alexander,Vikas Singh %t2010 %cNIPS %f/NIPS/NIPS-2010-3932.pdf %*Improving Human Judgments by Decontaminating Sequential Dependencies %@Michael C. Mozer,Harold Pashler,Matthew Wilder,Robert V. Lindsey,Matt Jones,Michael N. Jones %t2010 %cNIPS %f/NIPS/NIPS-2010-3933.pdf %*A Theory of Multiclass Boosting %@Indraneel Mukherjee,Robert E. Schapire %t2010 %cNIPS %f/NIPS/NIPS-2010-3934.pdf %*A biologically plausible network for the computation of orientation dominance %@Kritika Muralidharan,Nuno Vasconcelos %t2010 %cNIPS %f/NIPS/NIPS-2010-3935.pdf %*Slice sampling covariance hyperparameters of latent Gaussian models %@Iain Murray,Ryan P. Adams %t2010 %cNIPS %f/NIPS/NIPS-2010-3936.pdf %*On the Convexity of Latent Social Network Inference %@Seth Myers,Jure Leskovec %t2010 %cNIPS %f/NIPS/NIPS-2010-3937.pdf %*Infinite Relational Modeling of Functional Connectivity in Resting State fMRI %@Morten Mørup,Kristoffer Madsen,Anne-marie Dogonowski,Hartwig Siebner,Lars K. Hansen %t2010 %cNIPS %f/NIPS/NIPS-2010-3938.pdf %*Minimum Average Cost Clustering %@Kiyohito Nagano,Yoshinobu Kawahara,Satoru Iwata %t2010 %cNIPS %f/NIPS/NIPS-2010-3939.pdf %*Global Analytic Solution for Variational Bayesian Matrix Factorization %@Shinichi Nakajima,Masashi Sugiyama,Ryota Tomioka %t2010 %cNIPS %f/NIPS/NIPS-2010-3940.pdf %*Random Walk Approach to Regret Minimization %@Hariharan Narayanan,Alexander Rakhlin %t2010 %cNIPS %f/NIPS/NIPS-2010-3941.pdf %*Sample Complexity of Testing the Manifold Hypothesis %@Hariharan Narayanan,Sanjoy Mitter %t2010 %cNIPS %f/NIPS/NIPS-2010-3942.pdf %*Online Markov Decision Processes under Bandit Feedback %@Gergely Neu,Andras Antos,András György,Csaba Szepesvári %t2010 %cNIPS %f/NIPS/NIPS-2010-3943.pdf %*Efficient and Robust Feature Selection via Joint ℓ2,1-Norms Minimization %@Feiping Nie,Heng Huang,Xiao Cai,Chris H. Ding %t2010 %cNIPS %f/NIPS/NIPS-2010-3944.pdf %*Generative Local Metric Learning for Nearest Neighbor Classification %@Yung-kyun Noh,Byoung-tak Zhang,Daniel D. Lee %t2010 %cNIPS %f/NIPS/NIPS-2010-3945.pdf %*Approximate inference in continuous time Gaussian-Jump processes %@Manfred Opper,Andreas Ruttor,Guido Sanguinetti %t2010 %cNIPS %f/NIPS/NIPS-2010-3946.pdf %*New Adaptive Algorithms for Online Classification %@Francesco Orabona,Koby Crammer %t2010 %cNIPS %f/NIPS/NIPS-2010-3947.pdf %*Estimation of Rényi Entropy and Mutual Information Based on Generalized Nearest-Neighbor Graphs %@Dávid Pál,Barnabás Póczos,Csaba Szepesvári %t2010 %cNIPS %f/NIPS/NIPS-2010-3948.pdf %*Gaussian sampling by local perturbations %@George Papandreou,Alan L. Yuille %t2010 %cNIPS %f/NIPS/NIPS-2010-3949.pdf %*Large Margin Multi-Task Metric Learning %@Shibin Parameswaran,Kilian Q. Weinberger %t2010 %cNIPS %f/NIPS/NIPS-2010-3950.pdf %*Multiparty Differential Privacy via Aggregation of Locally Trained Classifiers %@Manas Pathak,Shantanu Rane,Bhiksha Raj %t2010 %cNIPS %f/NIPS/NIPS-2010-3951.pdf %*(RF)^2 -- Random Forest Random Field %@Nadia Payet,Sinisa Todorovic %t2010 %cNIPS %f/NIPS/NIPS-2010-3952.pdf %*On the Theory of Learnining with Privileged Information %@Dmitry Pechyony,Vladimir Vapnik %t2010 %cNIPS %f/NIPS/NIPS-2010-3953.pdf %*Empirical Bernstein Inequalities for U-Statistics %@Thomas Peel,Sandrine Anthoine,Liva Ralaivola %t2010 %cNIPS %f/NIPS/NIPS-2010-3954.pdf %*Reverse Multi-Label Learning %@James Petterson,Tibério S. Caetano %t2010 %cNIPS %f/NIPS/NIPS-2010-3955.pdf %*Word Features for Latent Dirichlet Allocation %@James Petterson,Wray Buntine,Shravan M. Narayanamurthy,Tibério S. Caetano,Alex J. Smola %t2010 %cNIPS %f/NIPS/NIPS-2010-3956.pdf %*Probabilistic Deterministic Infinite Automata %@David Pfau,Nicholas Bartlett,Frank Wood %t2010 %cNIPS %f/NIPS/NIPS-2010-3957.pdf %*The Maximal Causes of Natural Scenes are Edge Filters %@Jose Puertas,Joerg Bornschein,Joerg Luecke %t2010 %cNIPS %f/NIPS/NIPS-2010-3958.pdf %*A New Probabilistic Model for Rank Aggregation %@Tao Qin,Xiubo Geng,Tie-yan Liu %t2010 %cNIPS %f/NIPS/NIPS-2010-3959.pdf %*Multitask Learning without Label Correspondences %@Novi Quadrianto,James Petterson,Tibério S. Caetano,Alex J. Smola,S.v.n. Vishwanathan %t2010 %cNIPS %f/NIPS/NIPS-2010-3960.pdf %*Link Discovery using Graph Feature Tracking %@Emile Richard,Nicolas Baskiotis,Theodoros Evgeniou,Nicolas Vayatis %t2010 %cNIPS %f/NIPS/NIPS-2010-3961.pdf %*Inferring Stimulus Selectivity from the Spatial Structure of Neural Network Dynamics %@Kanaka Rajan,L Abbott,Haim Sompolinsky %t2010 %cNIPS %f/NIPS/NIPS-2010-3962.pdf %*Online Learning: Random Averages, Combinatorial Parameters, and Learnability %@Alexander Rakhlin,Karthik Sridharan,Ambuj Tewari %t2010 %cNIPS %f/NIPS/NIPS-2010-3963.pdf %*Evaluating neuronal codes for inference using Fisher information %@Haefner Ralf,Matthias Bethge %t2010 %cNIPS %f/NIPS/NIPS-2010-3964.pdf %*Generating more realistic images using gated MRF's %@Marc'aurelio Ranzato,Volodymyr Mnih,Geoffrey E. Hinton %t2010 %cNIPS %f/NIPS/NIPS-2010-3965.pdf %*An Approximate Inference Approach to Temporal Optimization in Optimal Control %@Konrad Rawlik,Marc Toussaint,Sethu Vijayakumar %t2010 %cNIPS %f/NIPS/NIPS-2010-3966.pdf %*Hallucinations in Charles Bonnet Syndrome Induced by Homeostasis: a Deep Boltzmann Machine Model %@Peggy Series,David P. Reichert,Amos J. Storkey %t2010 %cNIPS %f/NIPS/NIPS-2010-3967.pdf %*An Alternative to Low-level-Sychrony-Based Methods for Speech Detection %@Javier R. Movellan,Paul L. Ruvolo %t2010 %cNIPS %f/NIPS/NIPS-2010-3968.pdf %*Tight Sample Complexity of Large-Margin Learning %@Sivan Sabato,Nathan Srebro,Naftali Tishby %t2010 %cNIPS %f/NIPS/NIPS-2010-3969.pdf %*Boosting Classifier Cascades %@Nuno Vasconcelos,Mohammad J. Saberian %t2010 %cNIPS %f/NIPS/NIPS-2010-3970.pdf %*Collaborative Filtering in a Non-Uniform World: Learning with the Weighted Trace Norm %@Nathan Srebro,Ruslan R. Salakhutdinov %t2010 %cNIPS %f/NIPS/NIPS-2010-3971.pdf %*Implicitly Constrained Gaussian Process Regression for Monocular Non-Rigid Pose Estimation %@Mathieu Salzmann,Raquel Urtasun %t2010 %cNIPS %f/NIPS/NIPS-2010-3972.pdf %*Deterministic Single-Pass Algorithm for LDA %@Issei Sato,Kenichi Kurihara,Hiroshi Nakagawa %t2010 %cNIPS %f/NIPS/NIPS-2010-3973.pdf %*Active Estimation of F-Measures %@Christoph Sawade,Niels Landwehr,Tobias Scheffer %t2010 %cNIPS %f/NIPS/NIPS-2010-3974.pdf %*Trading off Mistakes and Don't-Know Predictions %@Amin Sayedi,Morteza Zadimoghaddam,Avrim Blum %t2010 %cNIPS %f/NIPS/NIPS-2010-3975.pdf %*Sparse Inverse Covariance Selection via Alternating Linearization Methods %@Katya Scheinberg,Shiqian Ma,Donald Goldfarb %t2010 %cNIPS %f/NIPS/NIPS-2010-3976.pdf %*Spike timing-dependent plasticity as dynamic filter %@Joscha Schmiedt,Christian Albers,Klaus Pawelzik %t2010 %cNIPS %f/NIPS/NIPS-2010-3977.pdf %*A novel family of non-parametric cumulative based divergences for point processes %@Sohan Seth,Park Il,Austin Brockmeier,Mulugeta Semework,John Choi,Joseph Francis,Jose Principe %t2010 %cNIPS %f/NIPS/NIPS-2010-3978.pdf %*Online Learning in The Manifold of Low-Rank Matrices %@Uri Shalit,Daphna Weinshall,Gal Chechik %t2010 %cNIPS %f/NIPS/NIPS-2010-3979.pdf %*Identifying graph-structured activation patterns in networks %@James Sharpnack,Aarti Singh %t2010 %cNIPS %f/NIPS/NIPS-2010-3980.pdf %*A rational decision making framework for inhibitory control %@Pradeep Shenoy,Angela J. Yu,Rajesh P. Rao %t2010 %cNIPS %f/NIPS/NIPS-2010-3981.pdf %*Penalized Principal Component Regression on Graphs for Analysis of Subnetworks %@Ali Shojaie,George Michailidis %t2010 %cNIPS %f/NIPS/NIPS-2010-3982.pdf %*Monte-Carlo Planning in Large POMDPs %@David Silver,Joel Veness %t2010 %cNIPS %f/NIPS/NIPS-2010-3983.pdf %*Sodium entry efficiency during action potentials: A novel single-parameter family of Hodgkin-Huxley models %@Anand Singh,Renaud Jolivet,Pierre Magistretti,Bruno Weber %t2010 %cNIPS %f/NIPS/NIPS-2010-3984.pdf %*More data means less inference: A pseudo-max approach to structured learning %@David Sontag,Ofer Meshi,Amir Globerson,Tommi S. Jaakkola %t2010 %cNIPS %f/NIPS/NIPS-2010-3985.pdf %*Reward Design via Online Gradient Ascent %@Jonathan Sorg,Richard L. Lewis,Satinder P. Singh %t2010 %cNIPS %f/NIPS/NIPS-2010-3986.pdf %*Smoothness, Low Noise and Fast Rates %@Nathan Srebro,Karthik Sridharan,Ambuj Tewari %t2010 %cNIPS %f/NIPS/NIPS-2010-3987.pdf %*Efficient Minimization of Decomposable Submodular Functions %@Peter Stobbe,Andreas Krause %t2010 %cNIPS %f/NIPS/NIPS-2010-3988.pdf %*Learning from Logged Implicit Exploration Data %@Alex Strehl,John Langford,Lihong Li,Sham M. Kakade %t2010 %cNIPS %f/NIPS/NIPS-2010-3989.pdf %*Layered image motion with explicit occlusions, temporal consistency, and depth ordering %@Deqing Sun,Erik B. Sudderth,Michael J. Black %t2010 %cNIPS %f/NIPS/NIPS-2010-3990.pdf %*Improving the Asymptotic Performance of Markov Chain Monte-Carlo by Inserting Vortices %@Yi Sun,Juergen Schmidhuber,Faustino J. Gomez %t2010 %cNIPS %f/NIPS/NIPS-2010-3991.pdf %*Semi-Supervised Learning with Adversarially Missing Label Information %@Umar Syed,Ben Taskar %t2010 %cNIPS %f/NIPS/NIPS-2010-3992.pdf %*A Reduction from Apprenticeship Learning to Classification %@Umar Syed,Robert E. Schapire %t2010 %cNIPS %f/NIPS/NIPS-2010-3993.pdf %*Identifying Patients at Risk of Major Adverse Cardiovascular Events Using Symbolic Mismatch %@Zeeshan Syed,John V. Guttag %t2010 %cNIPS %f/NIPS/NIPS-2010-3994.pdf %*Switching state space model for simultaneously estimating state transitions and nonstationary firing rates %@Ken Takiyama,Masato Okada %t2010 %cNIPS %f/NIPS/NIPS-2010-3995.pdf %*Pose-Sensitive Embedding by Nonlinear NCA Regression %@Graham W. Taylor,Rob Fergus,George Williams,Ian Spiro,Christoph Bregler %t2010 %cNIPS %f/NIPS/NIPS-2010-3996.pdf %*Fast Large-scale Mixture Modeling with Component-specific Data Partitions %@Bo Thiesson,Chong Wang %t2010 %cNIPS %f/NIPS/NIPS-2010-3997.pdf %*Phoneme Recognition with Large Hierarchical Reservoirs %@Fabian Triefenbach,Azarakhsh Jalalvand,Benjamin Schrauwen,Jean-pierre Martens %t2010 %cNIPS %f/NIPS/NIPS-2010-3998.pdf %*Exact learning curves for Gaussian process regression on large random graphs %@Matthew Urry,Peter Sollich %t2010 %cNIPS %f/NIPS/NIPS-2010-3999.pdf %*Worst-case bounds on the quality of max-product fixed-points %@Meritxell Vinyals,Jes\'us Cerquides,Alessandro Farinelli,Juan A. Rodríguez-aguilar %t2010 %cNIPS %f/NIPS/NIPS-2010-4000.pdf %*Brain covariance selection: better individual functional connectivity models using population prior %@Gael Varoquaux,Alexandre Gramfort,Jean-baptiste Poline,Bertrand Thirion %t2010 %cNIPS %f/NIPS/NIPS-2010-4001.pdf %*Fast detection of multiple change-points shared by many signals using group LARS %@Jean-philippe Vert,Kevin Bleakley %t2010 %cNIPS %f/NIPS/NIPS-2010-4002.pdf %*Optimal Bayesian Recommendation Sets and Myopically Optimal Choice Query Sets %@Paolo Viappiani,Craig Boutilier %t2010 %cNIPS %f/NIPS/NIPS-2010-4003.pdf %*Multiple Kernel Learning and the SMO Algorithm %@Zhaonan Sun,Nawanol Ampornpunt,Manik Varma,S.v.n. Vishwanathan %t2010 %cNIPS %f/NIPS/NIPS-2010-4004.pdf %*Joint Analysis of Time-Evolving Binary Matrices and Associated Documents %@Eric Wang,Dehong Liu,Jorge Silva,Lawrence Carin,David B. Dunson %t2010 %cNIPS %f/NIPS/NIPS-2010-4005.pdf %*Unsupervised Kernel Dimension Reduction %@Meihong Wang,Fei Sha,Michael I. Jordan %t2010 %cNIPS %f/NIPS/NIPS-2010-4006.pdf %*Multi-View Active Learning in the Non-Realizable Case %@Wei Wang,Zhi-hua Zhou %t2010 %cNIPS %f/NIPS/NIPS-2010-4007.pdf %*A Discriminative Latent Model of Image Region and Object Tag Correspondence %@Yang Wang,Greg Mori %t2010 %cNIPS %f/NIPS/NIPS-2010-4008.pdf %*Heavy-Tailed Process Priors for Selective Shrinkage %@Fabian L. Wauthier,Michael I. Jordan %t2010 %cNIPS %f/NIPS/NIPS-2010-4009.pdf %*Sidestepping Intractable Inference with Structured Ensemble Cascades %@David Weiss,Benjamin Sapp,Ben Taskar %t2010 %cNIPS %f/NIPS/NIPS-2010-4010.pdf %*The Multidimensional Wisdom of Crowds %@Peter Welinder,Steve Branson,Pietro Perona,Serge J. Belongie %t2010 %cNIPS %f/NIPS/NIPS-2010-4011.pdf %*Interval Estimation for Reinforcement-Learning Algorithms in Continuous-State Domains %@Martha White,Adam White %t2010 %cNIPS %f/NIPS/NIPS-2010-4012.pdf %*Active Learning Applied to Patient-Adaptive Heartbeat Classification %@Jenna Wiens,John V. Guttag %t2010 %cNIPS %f/NIPS/NIPS-2010-4013.pdf %*Probabilistic Inference and Differential Privacy %@Oliver Williams,Frank Mcsherry %t2010 %cNIPS %f/NIPS/NIPS-2010-4014.pdf %*Copula Processes %@Andrew Wilson,Zoubin Ghahramani %t2010 %cNIPS %f/NIPS/NIPS-2010-4015.pdf %*Linear readout from a neural population with partial correlation data %@Adrien Wohrer,Ranulfo Romo,Christian K. Machens %t2010 %cNIPS %f/NIPS/NIPS-2010-4016.pdf %*A unified model of short-range and long-range motion perception %@Shuang Wu,Xuming He,Hongjing Lu,Alan L. Yuille %t2010 %cNIPS %f/NIPS/NIPS-2010-4017.pdf %*A Log-Domain Implementation of the Diffusion Network in Very Large Scale Integration %@Yi-da Wu,Shi-jie Lin,Hsin Chen %t2010 %cNIPS %f/NIPS/NIPS-2010-4018.pdf %*Robust PCA via Outlier Pursuit %@Huan Xu,Constantine Caramanis,Sujay Sanghavi %t2010 %cNIPS %f/NIPS/NIPS-2010-4019.pdf %*Distributionally Robust Markov Decision Processes %@Huan Xu,Shie Mannor %t2010 %cNIPS %f/NIPS/NIPS-2010-4020.pdf %*Inference and communication in the game of Password %@Yang Xu,Charles Kemp %t2010 %cNIPS %f/NIPS/NIPS-2010-4021.pdf %*Relaxed Clipping: A Global Training Method for Robust Regression and Classification %@Min Yang,Linli Xu,Martha White,Dale Schuurmans,Yao-liang Yu %t2010 %cNIPS %f/NIPS/NIPS-2010-4022.pdf %*Lower Bounds on Rate of Convergence of Cutting Plane Methods %@Xinhua Zhang,Ankan Saha,S.v.n. Vishwanathan %t2010 %cNIPS %f/NIPS/NIPS-2010-4023.pdf %*Learning Multiple Tasks with a Sparse Matrix-Normal Penalty %@Yi Zhang,Jeff G. Schneider %t2010 %cNIPS %f/NIPS/NIPS-2010-4024.pdf %*Probabilistic Multi-Task Feature Selection %@Yu Zhang,Dit-Yan Yeung,Qian Xu %t2010 %cNIPS %f/NIPS/NIPS-2010-4025.pdf %*Worst-Case Linear Discriminant Analysis %@Yu Zhang,Dit-Yan Yeung %t2010 %cNIPS %f/NIPS/NIPS-2010-4026.pdf %*Sufficient Conditions for Generating Group Level Sparsity in a Robust Minimax Framework %@Hongbo Zhou,Qiang Cheng %t2010 %cNIPS %f/NIPS/NIPS-2010-4027.pdf %*Large Margin Learning of Upstream Scene Understanding Models %@Jun Zhu,Li-jia Li,Li Fei-fei,Eric P. Xing %t2010 %cNIPS %f/NIPS/NIPS-2010-4028.pdf %*Parallelized Stochastic Gradient Descent %@Martin Zinkevich,Markus Weimer,Lihong Li,Alex J. Smola %t2010 %cNIPS %f/NIPS/NIPS-2010-4029.pdf %*A Primal-Dual Algorithm for Group Sparse Regularization with Overlapping Groups %@Sofia Mosci,Silvia Villa,Alessandro Verri,Lorenzo Rosasco %t2010 %cNIPS %f/NIPS/NIPS-2010-4030.pdf %*Getting lost in space: Large sample analysis of the resistance distance %@Ulrike V. Luxburg,Agnes Radl,Matthias Hein %t2010 %cNIPS %f/NIPS/NIPS-2010-4031.pdf %*Information-theoretic lower bounds on the oracle complexity of convex optimization %@Alekh Agarwal,Martin J. Wainwright,Peter L. Bartlett,Pradeep K. Ravikumar %t2009 %cNIPS %f/NIPS/NIPS-2009-4032.pdf %*Streaming k-means approximation %@Nir Ailon,Ragesh Jaiswal,Claire Monteleoni %t2009 %cNIPS %f/NIPS/NIPS-2009-4033.pdf %*Complexity of Decentralized Control: Special Cases %@Martin Allen,Shlomo Zilberstein %t2009 %cNIPS %f/NIPS/NIPS-2009-4034.pdf %*Learning from Multiple Partially Observed Views - an Application to Multilingual Text Categorization %@Massih Amini,Nicolas Usunier,Cyril Goutte %t2009 %cNIPS %f/NIPS/NIPS-2009-4035.pdf %*Constructing Topological Maps using Markov Random Fields and Loop-Closure Detection %@Roy Anati,Kostas Daniilidis %t2009 %cNIPS %f/NIPS/NIPS-2009-4036.pdf %*Data-driven calibration of linear estimators with minimal penalties %@Sylvain Arlot,Francis R. Bach %t2009 %cNIPS %f/NIPS/NIPS-2009-4037.pdf %*Polynomial Semantic Indexing %@Bing Bai,Jason Weston,David Grangier,Ronan Collobert,Kunihiko Sadamasa,Yanjun Qi,Corinna Cortes,Mehryar Mohri %t2009 %cNIPS %f/NIPS/NIPS-2009-4038.pdf %*Nonparametric Bayesian Models for Unsupervised Event Coreference Resolution %@Cosmin Bejan,Matthew Titsworth,Andrew Hickl,Sanda Harabagiu %t2009 %cNIPS %f/NIPS/NIPS-2009-4039.pdf %*Group Sparse Coding %@Samy Bengio,Fernando Pereira,Yoram Singer,Dennis Strelow %t2009 %cNIPS %f/NIPS/NIPS-2009-4040.pdf %*Neurometric function analysis of population codes %@Philipp Berens,Sebastian Gerwinn,Alexander Ecker,Matthias Bethge %t2009 %cNIPS %f/NIPS/NIPS-2009-4041.pdf %*Slow, Decorrelated Features for Pretraining Complex Cell-like Networks %@Yoshua Bengio,James S. Bergstra %t2009 %cNIPS %f/NIPS/NIPS-2009-4042.pdf %*No evidence for active sparsification in the visual cortex %@Pietro Berkes,Ben White,Jozsef Fiser %t2009 %cNIPS %f/NIPS/NIPS-2009-4043.pdf %*Manifold Regularization for SIR with Rate Root-n Convergence %@Wei Bian,Dacheng Tao %t2009 %cNIPS %f/NIPS/NIPS-2009-4044.pdf %*Augmenting Feature-driven fMRI Analyses: Semi-supervised learning and resting state activity %@Andreas Bartels,Matthew Blaschko,Jacquelyn A. Shelton %t2009 %cNIPS %f/NIPS/NIPS-2009-4045.pdf %*Efficient Match Kernel between Sets of Features for Visual Recognition %@Liefeng Bo,Cristian Sminchisescu %t2009 %cNIPS %f/NIPS/NIPS-2009-4046.pdf %*Randomized Pruning: Efficiently Calculating Expectations in Large Dynamic Programs %@Alexandre Bouchard-côté,Slav Petrov,Dan Klein %t2009 %cNIPS %f/NIPS/NIPS-2009-4047.pdf %*Unsupervised Feature Selection for the k-means Clustering Problem %@Christos Boutsidis,Petros Drineas,Michael W. Mahoney %t2009 %cNIPS %f/NIPS/NIPS-2009-4048.pdf %*On Invariance in Hierarchical Models %@Jake Bouvrie,Lorenzo Rosasco,Tomaso Poggio %t2009 %cNIPS %f/NIPS/NIPS-2009-4049.pdf %*Nash Equilibria of Static Prediction Games %@Michael Brückner,Tobias Scheffer %t2009 %cNIPS %f/NIPS/NIPS-2009-4050.pdf %*Optimal context separation of spiking haptic signals by second-order somatosensory neurons %@Romain Brasselet,Roland Johansson,Angelo Arleo %t2009 %cNIPS %f/NIPS/NIPS-2009-4051.pdf %*Manifold Embeddings for Model-Based Reinforcement Learning under Partial Observability %@Keith Bush,Joelle Pineau %t2009 %cNIPS %f/NIPS/NIPS-2009-4052.pdf %*Learning to Explore and Exploit in POMDPs %@Chenghui Cai,Xuejun Liao,Lawrence Carin %t2009 %cNIPS %f/NIPS/NIPS-2009-4053.pdf %*Speaker Comparison with Inner Product Discriminant Functions %@Zahi Karam,Douglas Sturim,William M. Campbell %t2009 %cNIPS %f/NIPS/NIPS-2009-4054.pdf %*A Stochastic approximation method for inference in probabilistic graphical models %@Peter Carbonetto,Matthew King,Firas Hamze %t2009 %cNIPS %f/NIPS/NIPS-2009-4055.pdf %*Bayesian Nonparametric Models on Decomposable Graphs %@Francois Caron,Arnaud Doucet %t2009 %cNIPS %f/NIPS/NIPS-2009-4056.pdf %*Adaptive Design Optimization in Experiments with People %@Daniel Cavagnaro,Jay Myung,Mark A. Pitt %t2009 %cNIPS %f/NIPS/NIPS-2009-4057.pdf %*Discriminative Network Models of Schizophrenia %@Irina Rish,Benjamin Thyreau,Bertrand Thirion,Marion Plaze,Marie-laure Paillere-martinot,Catherine Martelli,Jean-luc Martinot,Jean-baptiste Poline,Guillermo A. Cecchi %t2009 %cNIPS %f/NIPS/NIPS-2009-4058.pdf %*Exploring Functional Connectivities of the Human Brain using Multivariate Information Analysis %@Barry Chai,Dirk Walther,Diane Beck,Li Fei-fei %t2009 %cNIPS %f/NIPS/NIPS-2009-4059.pdf %*Reading Tea Leaves: How Humans Interpret Topic Models %@Jonathan Chang,Sean Gerrish,Chong Wang,Jordan L. Boyd-graber,David M. Blei %t2009 %cNIPS %f/NIPS/NIPS-2009-4060.pdf %*A Parameter-free Hedging Algorithm %@Kamalika Chaudhuri,Yoav Freund,Daniel J. Hsu %t2009 %cNIPS %f/NIPS/NIPS-2009-4061.pdf %*An Online Algorithm for Large Scale Image Similarity Learning %@Gal Chechik,Uri Shalit,Varun Sharma,Samy Bengio %t2009 %cNIPS %f/NIPS/NIPS-2009-4062.pdf %*Ranking Measures and Loss Functions in Learning to Rank %@Wei Chen,Tie-yan Liu,Yanyan Lan,Zhi-ming Ma,Hang Li %t2009 %cNIPS %f/NIPS/NIPS-2009-4063.pdf %*Factor Modeling for Advertisement Targeting %@Ye Chen,Michael Kapralov,John Canny,Dmitry Y. Pavlov %t2009 %cNIPS %f/NIPS/NIPS-2009-4064.pdf %*The Ordered Residual Kernel for Robust Motion Subspace Clustering %@Tat-jun Chin,Hanzi Wang,David Suter %t2009 %cNIPS %f/NIPS/NIPS-2009-4065.pdf %*Kernel Methods for Deep Learning %@Youngmin Cho,Lawrence K. Saul %t2009 %cNIPS %f/NIPS/NIPS-2009-4066.pdf %*Approximating MAP by Compensating for Structural Relaxations %@Arthur Choi,Adnan Darwiche %t2009 %cNIPS %f/NIPS/NIPS-2009-4067.pdf %*AUC optimization and the two-sample problem %@Nicolas Vayatis,Marine Depecker,Stéphan J. Clémençcon %t2009 %cNIPS %f/NIPS/NIPS-2009-4068.pdf %*Statistical Models of Linear and Nonlinear Contextual Interactions in Early Visual Processing %@Ruben Coen-cagli,Peter Dayan,Odelia Schwartz %t2009 %cNIPS %f/NIPS/NIPS-2009-4069.pdf %*fMRI-Based Inter-Subject Cortical Alignment Using Functional Connectivity %@Bryan Conroy,Ben Singer,James Haxby,Peter J. Ramadge %t2009 %cNIPS %f/NIPS/NIPS-2009-4070.pdf %*Sensitivity analysis in HMMs with application to likelihood maximization %@Pierre-arnaud Coquelin,Romain Deguest,Rémi Munos %t2009 %cNIPS %f/NIPS/NIPS-2009-4071.pdf %*Learning Non-Linear Combinations of Kernels %@Corinna Cortes,Mehryar Mohri,Afshin Rostamizadeh %t2009 %cNIPS %f/NIPS/NIPS-2009-4072.pdf %*An Infinite Factor Model Hierarchy Via a Noisy-Or Mechanism %@Douglas Eck,Yoshua Bengio,Aaron C. Courville %t2009 %cNIPS %f/NIPS/NIPS-2009-4073.pdf %*Adaptive Regularization of Weight Vectors %@Koby Crammer,Alex Kulesza,Mark Dredze %t2009 %cNIPS %f/NIPS/NIPS-2009-4074.pdf %*Learning transport operators for image manifolds %@Benjamin Culpepper,Bruno A. Olshausen %t2009 %cNIPS %f/NIPS/NIPS-2009-4075.pdf %*White Functionals for Anomaly Detection in Dynamical Systems %@Marco Cuturi,Jean-philippe Vert,Alexandre D'aspremont %t2009 %cNIPS %f/NIPS/NIPS-2009-4076.pdf %*L_1-Penalized Robust Estimation for a Class of Inverse Problems Arising in Multiview Geometry %@Arnak Dalalyan,Renaud Keriven %t2009 %cNIPS %f/NIPS/NIPS-2009-4077.pdf %*A Smoothed Approximate Linear Program %@Vijay Desai,Vivek Farias,Ciamac C. Moallemi %t2009 %cNIPS %f/NIPS/NIPS-2009-4078.pdf %*Localizing Bugs in Program Executions with Graphical Models %@Laura Dietz,Valentin Dallmeier,Andreas Zeller,Tobias Scheffer %t2009 %cNIPS %f/NIPS/NIPS-2009-4079.pdf %*A Bayesian Model for Simultaneous Image Clustering, Annotation and Object Segmentation %@Lan Du,Lu Ren,Lawrence Carin,David B. Dunson %t2009 %cNIPS %f/NIPS/NIPS-2009-4080.pdf %*Efficient Learning using Forward-Backward Splitting %@Yoram Singer,John C. Duchi %t2009 %cNIPS %f/NIPS/NIPS-2009-4081.pdf %*A Data-Driven Approach to Modeling Choice %@Vivek Farias,Srikanth Jagabathula,Devavrat Shah %t2009 %cNIPS %f/NIPS/NIPS-2009-4082.pdf %*Subject independent EEG-based BCI decoding %@Siamac Fazli,Cristian Grozea,Marton Danoczy,Benjamin Blankertz,Florin Popescu,Klaus-Robert Müller %t2009 %cNIPS %f/NIPS/NIPS-2009-4083.pdf %*Semi-Supervised Learning in Gigantic Image Collections %@Rob Fergus,Yair Weiss,Antonio Torralba %t2009 %cNIPS %f/NIPS/NIPS-2009-4084.pdf %*Evaluating multi-class learning strategies in a generative hierarchical framework for object detection %@Sanja Fidler,Marko Boben,Ales Leonardis %t2009 %cNIPS %f/NIPS/NIPS-2009-4085.pdf %*Orthogonal Matching Pursuit From Noisy Random Measurements: A New Analysis %@Sundeep Rangan,Alyson K. Fletcher %t2009 %cNIPS %f/NIPS/NIPS-2009-4086.pdf %*Sharing Features among Dynamical Systems with Beta Processes %@Emily Fox,Michael I. Jordan,Erik B. Sudderth,Alan S. Willsky %t2009 %cNIPS %f/NIPS/NIPS-2009-4087.pdf %*An Additive Latent Feature Model for Transparent Object Recognition %@Mario Fritz,Gary Bradski,Sergey Karayev,Trevor Darrell,Michael J. Black %t2009 %cNIPS %f/NIPS/NIPS-2009-4088.pdf %*An LP View of the M-best MAP problem %@Menachem Fromer,Amir Globerson %t2009 %cNIPS %f/NIPS/NIPS-2009-4089.pdf %*Estimating image bases for visual image reconstruction from human brain activity %@Yusuke Fujiwara,Yoichi Miyawaki,Yukiyasu Kamitani %t2009 %cNIPS %f/NIPS/NIPS-2009-4090.pdf %*Graph-based Consensus Maximization among Multiple Supervised and Unsupervised Models %@Jing Gao,Feng Liang,Wei Fan,Yizhou Sun,Jiawei Han %t2009 %cNIPS %f/NIPS/NIPS-2009-4091.pdf %*Lattice Regression %@Eric Garcia,Maya Gupta %t2009 %cNIPS %f/NIPS/NIPS-2009-4092.pdf %*From PAC-Bayes Bounds to KL Regularization %@Pascal Germain,Alexandre Lacasse,Mario Marchand,Sara Shanian,François Laviolette %t2009 %cNIPS %f/NIPS/NIPS-2009-4093.pdf %*Perceptual Multistability as Markov Chain Monte Carlo Inference %@Samuel Gershman,Ed Vul,Joshua B. Tenenbaum %t2009 %cNIPS %f/NIPS/NIPS-2009-4094.pdf %*A joint maximum-entropy model for binary neural population patterns and continuous signals %@Sebastian Gerwinn,Philipp Berens,Matthias Bethge %t2009 %cNIPS %f/NIPS/NIPS-2009-4095.pdf %*A Biologically Plausible Model for Rapid Natural Scene Identification %@Sennay Ghebreab,Steven Scholte,Victor Lamme,Arnold Smeulders %t2009 %cNIPS %f/NIPS/NIPS-2009-4096.pdf %*A Gaussian Tree Approximation for Integer Least-Squares %@Jacob Goldberger,Amir Leshem %t2009 %cNIPS %f/NIPS/NIPS-2009-4097.pdf %*Measuring Invariances in Deep Networks %@Ian Goodfellow,Honglak Lee,Quoc V. Le,Andrew Saxe,Andrew Y. Ng %t2009 %cNIPS %f/NIPS/NIPS-2009-4098.pdf %*Region-based Segmentation and Object Detection %@Stephen Gould,Tianshi Gao,Daphne Koller %t2009 %cNIPS %f/NIPS/NIPS-2009-4099.pdf %*Posterior vs Parameter Sparsity in Latent Variable Models %@Kuzman Ganchev,Ben Taskar,Fernando Pereira,João Gama %t2009 %cNIPS %f/NIPS/NIPS-2009-4100.pdf %*A Fast, Consistent Kernel Two-Sample Test %@Arthur Gretton,Kenji Fukumizu,Zaïd Harchaoui,Bharath K. Sriperumbudur %t2009 %cNIPS %f/NIPS/NIPS-2009-4101.pdf %*Non-stationary continuous dynamic Bayesian networks %@Marco Grzegorczyk,Dirk Husmeier %t2009 %cNIPS %f/NIPS/NIPS-2009-4102.pdf %*Label Selection on Graphs %@Andrew Guillory,Jeff A. Bilmes %t2009 %cNIPS %f/NIPS/NIPS-2009-4103.pdf %*Beyond Convexity: Online Submodular Minimization %@Elad Hazan,Satyen Kale %t2009 %cNIPS %f/NIPS/NIPS-2009-4104.pdf %*On Stochastic and Worst-case Models for Investing %@Elad Hazan,Satyen Kale %t2009 %cNIPS %f/NIPS/NIPS-2009-4105.pdf %*Hierarchical Learning of Dimensional Biases in Human Categorization %@Adam Sanborn,Nick Chater,Katherine A. Heller %t2009 %cNIPS %f/NIPS/NIPS-2009-4106.pdf %*Bayesian Sparse Factor Models and DAGs Inference and Comparison %@Ricardo Henao,Ole Winther %t2009 %cNIPS %f/NIPS/NIPS-2009-4107.pdf %*Sparse and Locally Constant Gaussian Graphical Models %@Jean Honorio,Dimitris Samaras,Nikos Paragios,Rita Goldstein,Luis E. Ortiz %t2009 %cNIPS %f/NIPS/NIPS-2009-4108.pdf %*Differential Use of Implicit Negative Evidence in Generative and Discriminative Language Learning %@Anne Hsu,Thomas L. Griffiths %t2009 %cNIPS %f/NIPS/NIPS-2009-4109.pdf %*Periodic Step Size Adaptation for Single Pass On-line Learning %@Chun-nan Hsu,Yu-ming Chang,Hanshen Huang,Yuh-jye Lee %t2009 %cNIPS %f/NIPS/NIPS-2009-4110.pdf %*Multi-Label Prediction via Compressed Sensing %@Daniel J. Hsu,Sham M. Kakade,John Langford,Tong Zhang %t2009 %cNIPS %f/NIPS/NIPS-2009-4111.pdf %*Accelerated Gradient Methods for Stochastic Optimization and Online Learning %@Chonghai Hu,Weike Pan,James T. Kwok %t2009 %cNIPS %f/NIPS/NIPS-2009-4112.pdf %*Reconstruction of Sparse Circuits Using Multi-neuronal Excitation (RESCUME) %@Tao Hu,Anthony Leonardo,Dmitri B. Chklovskii %t2009 %cNIPS %f/NIPS/NIPS-2009-4113.pdf %*Riffled Independence for Ranked Data %@Jonathan Huang,Carlos Guestrin %t2009 %cNIPS %f/NIPS/NIPS-2009-4114.pdf %*Learning Brain Connectivity of Alzheimer's Disease from Neuroimaging Data %@Shuai Huang,Jing Li,Liang Sun,Jun Liu,Teresa Wu,Kewei Chen,Adam Fleisher,Eric Reiman,Jieping Ye %t2009 %cNIPS %f/NIPS/NIPS-2009-4115.pdf %*Particle-based Variational Inference for Continuous Systems %@Andrew Frank,Padhraic Smyth,Alexander T. Ihler %t2009 %cNIPS %f/NIPS/NIPS-2009-4116.pdf %*Modeling Social Annotation Data with Content Relevance using a Topic Model %@Tomoharu Iwata,Takeshi Yamada,Naonori Ueda %t2009 %cNIPS %f/NIPS/NIPS-2009-4117.pdf %*On the Algorithmics and Applications of a Mixed-norm based Kernel Learning Formulation %@Saketha N. Jagarlapudi,Dinesh G,Raman S,Chiranjib Bhattacharyya,Aharon Ben-tal,Ramakrishnan K.r. %t2009 %cNIPS %f/NIPS/NIPS-2009-4118.pdf %*Bayesian Belief Polarization %@Alan Jern,Kai-min Chang,Charles Kemp %t2009 %cNIPS %f/NIPS/NIPS-2009-4119.pdf %*Regularized Distance Metric Learning:Theory and Algorithm %@Rong Jin,Shijun Wang,Yang Zhou %t2009 %cNIPS %f/NIPS/NIPS-2009-4120.pdf %*Local Rules for Global MAP: When Do They Work ? %@Kyomin Jung,Pushmeet Kohli,Devavrat Shah %t2009 %cNIPS %f/NIPS/NIPS-2009-4121.pdf %*Potential-Based Agnostic Boosting %@Varun Kanade,Adam Kalai %t2009 %cNIPS %f/NIPS/NIPS-2009-4122.pdf %*Directed Regression %@Yi-hao Kao,Benjamin V. Roy,Xiang Yan %t2009 %cNIPS %f/NIPS/NIPS-2009-4123.pdf %*Breaking Boundaries Between Induction Time and Diagnosis Time Active Information Acquisition %@Ashish Kapoor,Eric Horvitz %t2009 %cNIPS %f/NIPS/NIPS-2009-4124.pdf %*Multiple Incremental Decremental Learning of Support Vector Machines %@Masayuki Karasuyama,Ichiro Takeuchi %t2009 %cNIPS %f/NIPS/NIPS-2009-4125.pdf %*Submodularity Cuts and Applications %@Yoshinobu Kawahara,Kiyohito Nagano,Koji Tsuda,Jeff A. Bilmes %t2009 %cNIPS %f/NIPS/NIPS-2009-4126.pdf %*Individuation, Identification and Object Discovery %@Charles Kemp,Alan Jern,Fei Xu %t2009 %cNIPS %f/NIPS/NIPS-2009-4127.pdf %*Abstraction and Relational learning %@Charles Kemp,Alan Jern %t2009 %cNIPS %f/NIPS/NIPS-2009-4128.pdf %*Matrix Completion from Noisy Entries %@Raghunandan Keshavan,Andrea Montanari,Sewoong Oh %t2009 %cNIPS %f/NIPS/NIPS-2009-4129.pdf %*Unsupervised Detection of Regions of Interest Using Iterative Link Analysis %@Gunhee Kim,Antonio Torralba %t2009 %cNIPS %f/NIPS/NIPS-2009-4130.pdf %*Clustering sequence sets for motif discovery %@Jong K. Kim,Seungjin Choi %t2009 %cNIPS %f/NIPS/NIPS-2009-4131.pdf %*Semi-supervised Regression using Hessian energy with an application to semi-supervised dimensionality reduction %@Kwang I. Kim,Florian Steinke,Matthias Hein %t2009 %cNIPS %f/NIPS/NIPS-2009-4132.pdf %*Replacing supervised classification learning by Slow Feature Analysis in spiking neural networks %@Stefan Klampfl,Wolfgang Maass %t2009 %cNIPS %f/NIPS/NIPS-2009-4133.pdf %*Efficient and Accurate Lp-Norm Multiple Kernel Learning %@Marius Kloft,Ulf Brefeld,Pavel Laskov,Klaus-Robert Müller,Alexander Zien,Sören Sonnenburg %t2009 %cNIPS %f/NIPS/NIPS-2009-4134.pdf %*Sparsistent Learning of Varying-coefficient Models with Structural Changes %@Mladen Kolar,Le Song,Eric P. Xing %t2009 %cNIPS %f/NIPS/NIPS-2009-4135.pdf %*Skill Discovery in Continuous Reinforcement Learning Domains using Skill Chaining %@George Konidaris,Andre S. Barreto %t2009 %cNIPS %f/NIPS/NIPS-2009-4136.pdf %*Fast Image Deconvolution using Hyper-Laplacian Priors %@Dilip Krishnan,Rob Fergus %t2009 %cNIPS %f/NIPS/NIPS-2009-4137.pdf %*Learning to Hash with Binary Reconstructive Embeddings %@Brian Kulis,Trevor Darrell %t2009 %cNIPS %f/NIPS/NIPS-2009-4138.pdf %*Learning a Small Mixture of Trees %@M. P. Kumar,Daphne Koller %t2009 %cNIPS %f/NIPS/NIPS-2009-4139.pdf %*Ensemble Nystrom Method %@Sanjiv Kumar,Mehryar Mohri,Ameet Talwalkar %t2009 %cNIPS %f/NIPS/NIPS-2009-4140.pdf %*Occlusive Components Analysis %@Jörg Lücke,Richard Turner,Maneesh Sahani,Marc Henniges %t2009 %cNIPS %f/NIPS/NIPS-2009-4141.pdf %*Monte Carlo Sampling for Regret Minimization in Extensive Games %@Marc Lanctot,Kevin Waugh,Martin Zinkevich,Michael Bowling %t2009 %cNIPS %f/NIPS/NIPS-2009-4142.pdf %*Inter-domain Gaussian Processes for Sparse Inference using Inducing Features %@Miguel Lázaro-Gredilla,Aníbal Figueiras-Vidal %t2009 %cNIPS %f/NIPS/NIPS-2009-4143.pdf %*Unsupervised feature learning for audio classification using convolutional deep belief networks %@Honglak Lee,Peter Pham,Yan Largman,Andrew Y. Ng %t2009 %cNIPS %f/NIPS/NIPS-2009-4144.pdf %*Functional network reorganization in motor cortex can be explained by reward-modulated Hebbian learning %@Steven Chase,Andrew Schwartz,Wolfgang Maass,Robert A. Legenstein %t2009 %cNIPS %f/NIPS/NIPS-2009-4145.pdf %*An Integer Projected Fixed Point Method for Graph Matching and MAP Inference %@Marius Leordeanu,Martial Hebert,Rahul Sukthankar %t2009 %cNIPS %f/NIPS/NIPS-2009-4146.pdf %*Probabilistic Relational PCA %@Wu-jun Li,Dit-Yan Yeung,Zhihua Zhang %t2009 %cNIPS %f/NIPS/NIPS-2009-4147.pdf %*Asymptotically Optimal Regularization in Smooth Parametric Models %@Percy S. Liang,Guillaume Bouchard,Francis R. Bach,Michael I. Jordan %t2009 %cNIPS %f/NIPS/NIPS-2009-4148.pdf %*Nonparametric Greedy Algorithms for the Sparse Learning Problem %@Han Liu,Xi Chen %t2009 %cNIPS %f/NIPS/NIPS-2009-4149.pdf %*Grouped Orthogonal Matching Pursuit for Variable Selection and Prediction %@Grzegorz Swirszcz,Naoki Abe,Aurelie C. Lozano %t2009 %cNIPS %f/NIPS/NIPS-2009-4150.pdf %*Modeling the spacing effect in sequential category learning %@Hongjing Lu,Matthew Weiden,Alan L. Yuille %t2009 %cNIPS %f/NIPS/NIPS-2009-4151.pdf %*Who’s Doing What: Joint Modeling of Names and Verbs for Simultaneous Face and Pose Annotation %@Jie Luo,Barbara Caputo,Vittorio Ferrari %t2009 %cNIPS %f/NIPS/NIPS-2009-4152.pdf %*Variational Gaussian-process factor analysis for modeling spatio-temporal data %@Jaakko Luttinen,Alexander Ilin %t2009 %cNIPS %f/NIPS/NIPS-2009-4153.pdf %*Solving Stochastic Games %@Liam M. Dermed,Charles L. Isbell %t2009 %cNIPS %f/NIPS/NIPS-2009-4154.pdf %*Bayesian estimation of orientation preference maps %@Sebastian Gerwinn,Leonard White,Matthias Kaschube,Matthias Bethge,Jakob H. Macke %t2009 %cNIPS %f/NIPS/NIPS-2009-4155.pdf %*Convergent Temporal-Difference Learning with Arbitrary Smooth Function Approximation %@Shalabh Bhatnagar,Doina Precup,David Silver,Richard S. Sutton,Hamid R. Maei,Csaba Szepesvári %t2009 %cNIPS %f/NIPS/NIPS-2009-4156.pdf %*Compressed Least-Squares Regression %@Odalric Maillard,Rémi Munos %t2009 %cNIPS %f/NIPS/NIPS-2009-4157.pdf %*Beyond Categories: The Visual Memex Model for Reasoning About Object Relationships %@Tomasz Malisiewicz,Alyosha Efros %t2009 %cNIPS %f/NIPS/NIPS-2009-4158.pdf %*Efficient Large-Scale Distributed Training of Conditional Maximum Entropy Models %@Ryan Mcdonald,Mehryar Mohri,Nathan Silberman,Dan Walker,Gideon S. Mann %t2009 %cNIPS %f/NIPS/NIPS-2009-4159.pdf %*FACTORIE: Probabilistic Programming via Imperatively Defined Factor Graphs %@Andrew McCallum,Karl Schultz,Sameer Singh %t2009 %cNIPS %f/NIPS/NIPS-2009-4160.pdf %*Matrix Completion from Power-Law Distributed Samples %@Raghu Meka,Prateek Jain,Inderjit S. Dhillon %t2009 %cNIPS %f/NIPS/NIPS-2009-4161.pdf %*Extending Phase Mechanism to Differential Motion Opponency for Motion Pop-out %@Yicong Meng,Bertram E. Shi %t2009 %cNIPS %f/NIPS/NIPS-2009-4162.pdf %*Nonparametric Latent Feature Models for Link Prediction %@Kurt Miller,Michael I. Jordan,Thomas L. Griffiths %t2009 %cNIPS %f/NIPS/NIPS-2009-4163.pdf %*Accelerating Bayesian Structural Inference for Non-Decomposable Gaussian Graphical Models %@Baback Moghaddam,Emtiyaz Khan,Kevin P. Murphy,Benjamin M. Marlin %t2009 %cNIPS %f/NIPS/NIPS-2009-4164.pdf %*Large Scale Nonparametric Bayesian Inference: Data Parallelisation in the Indian Buffet Process %@Finale Doshi-velez,Shakir Mohamed,Zoubin Ghahramani,David A. Knowles %t2009 %cNIPS %f/NIPS/NIPS-2009-4165.pdf %*Which graphical models are difficult to learn? %@Andrea Montanari,Jose A. Pereira %t2009 %cNIPS %f/NIPS/NIPS-2009-4166.pdf %*A Generalized Natural Actor-Critic Algorithm %@Tetsuro Morimura,Eiji Uchibe,Junichiro Yoshimoto,Kenji Doya %t2009 %cNIPS %f/NIPS/NIPS-2009-4167.pdf %*Predicting the Optimal Spacing of Study: A Multiscale Context Model of Memory %@Harold Pashler,Nicholas Cepeda,Robert V. Lindsey,Ed Vul,Michael C. Mozer %t2009 %cNIPS %f/NIPS/NIPS-2009-4168.pdf %*Statistical Analysis of Semi-Supervised Learning: The Limit of Infinite Unlabelled Data %@Boaz Nadler,Nathan Srebro,Xueyuan Zhou %t2009 %cNIPS %f/NIPS/NIPS-2009-4169.pdf %*3D Object Recognition with Deep Belief Nets %@Vinod Nair,Geoffrey E. Hinton %t2009 %cNIPS %f/NIPS/NIPS-2009-4170.pdf %*A unified framework for high-dimensional analysis of M-estimators with decomposable regularizers %@Sahand Negahban,Bin Yu,Martin J. Wainwright,Pradeep K. Ravikumar %t2009 %cNIPS %f/NIPS/NIPS-2009-4171.pdf %*STDP enables spiking neurons to detect hidden causes of their inputs %@Bernhard Nessler,Michael Pfeiffer,Wolfgang Maass %t2009 %cNIPS %f/NIPS/NIPS-2009-4172.pdf %*Submanifold density estimation %@Arkadas Ozakin,Alexander G. Gray %t2009 %cNIPS %f/NIPS/NIPS-2009-4173.pdf %*Correlation Coefficients are Insufficient for Analyzing Spike Count Dependencies %@Arno Onken,Steffen Grünewälder,Klaus Obermayer %t2009 %cNIPS %f/NIPS/NIPS-2009-4174.pdf %*Learning from Neighboring Strokes: Combining Appearance and Context for Multi-Domain Sketch Recognition %@Tom Ouyang,Randall Davis %t2009 %cNIPS %f/NIPS/NIPS-2009-4175.pdf %*Zero-shot Learning with Semantic Output Codes %@Mark Palatucci,Dean Pomerleau,Geoffrey E. Hinton,Tom M. Mitchell %t2009 %cNIPS %f/NIPS/NIPS-2009-4176.pdf %*Conditional Neural Fields %@Jian Peng,Liefeng Bo,Jinbo Xu %t2009 %cNIPS %f/NIPS/NIPS-2009-4177.pdf %*Free energy score space %@Alessandro Perina,Marco Cristani,Umberto Castellani,Vittorio Murino,Nebojsa Jojic %t2009 %cNIPS %f/NIPS/NIPS-2009-4178.pdf %*Robust Value Function Approximation Using Bilinear Programming %@Marek Petrik,Shlomo Zilberstein %t2009 %cNIPS %f/NIPS/NIPS-2009-4179.pdf %*Exponential Family Graph Matching and Ranking %@James Petterson,Jin Yu,Julian J. Mcauley,Tibério S. Caetano %t2009 %cNIPS %f/NIPS/NIPS-2009-4180.pdf %*Know Thy Neighbour: A Normative Theory of Synaptic Depression %@Jean-pascal Pfister,Peter Dayan,Máté Lengyel %t2009 %cNIPS %f/NIPS/NIPS-2009-4181.pdf %*Bilinear classifiers for visual recognition %@Hamed Pirsiavash,Deva Ramanan,Charless C. Fowlkes %t2009 %cNIPS %f/NIPS/NIPS-2009-4182.pdf %*Convex Relaxation of Mixture Regression with Efficient Algorithms %@Novi Quadrianto,John Lim,Dale Schuurmans,Tibério S. Caetano %t2009 %cNIPS %f/NIPS/NIPS-2009-4183.pdf %*Distribution Matching for Transduction %@Novi Quadrianto,James Petterson,Alex J. Smola %t2009 %cNIPS %f/NIPS/NIPS-2009-4184.pdf %*Locality-sensitive binary codes from shift-invariant kernels %@Maxim Raginsky,Svetlana Lazebnik %t2009 %cNIPS %f/NIPS/NIPS-2009-4185.pdf %*Multi-Label Prediction via Sparse Infinite CCA %@Piyush Rai,Hal Daume %t2009 %cNIPS %f/NIPS/NIPS-2009-4186.pdf %*Linear-time Algorithms for Pairwise Statistical Problems %@Parikshit Ram,Dongryeol Lee,William March,Alexander G. Gray %t2009 %cNIPS %f/NIPS/NIPS-2009-4187.pdf %*Rank-Approximate Nearest Neighbor Search: Retaining Meaning and Speed in High Dimensions %@Parikshit Ram,Dongryeol Lee,Hua Ouyang,Alexander G. Gray %t2009 %cNIPS %f/NIPS/NIPS-2009-4188.pdf %*Asymptotic Analysis of MAP Estimation via the Replica Method and Compressed Sensing %@Sundeep Rangan,Vivek Goyal,Alyson K. Fletcher %t2009 %cNIPS %f/NIPS/NIPS-2009-4189.pdf %*Spatial Normalized Gamma Processes %@Vinayak Rao,Yee W. Teh %t2009 %cNIPS %f/NIPS/NIPS-2009-4190.pdf %*Lower bounds on minimax rates for nonparametric regression with additive sparsity and smoothness %@Garvesh Raskutti,Bin Yu,Martin J. Wainwright %t2009 %cNIPS %f/NIPS/NIPS-2009-4191.pdf %*A Game-Theoretic Approach to Hypergraph Clustering %@Samuel R. Bulò,Marcello Pelillo %t2009 %cNIPS %f/NIPS/NIPS-2009-4192.pdf %*Segmenting Scenes by Matching Image Composites %@Bryan Russell,Alyosha Efros,Josef Sivic,Bill Freeman,Andrew Zisserman %t2009 %cNIPS %f/NIPS/NIPS-2009-4193.pdf %*Filtering Abstract Senses From Image Search Results %@Kate Saenko,Trevor Darrell %t2009 %cNIPS %f/NIPS/NIPS-2009-4194.pdf %*Replicated Softmax: an Undirected Topic Model %@Geoffrey E. Hinton,Ruslan R. Salakhutdinov %t2009 %cNIPS %f/NIPS/NIPS-2009-4195.pdf %*Learning models of object structure %@Joseph Schlecht,Kobus Barnard %t2009 %cNIPS %f/NIPS/NIPS-2009-4196.pdf %*Improving Existing Fault Recovery Policies %@Guy Shani,Christopher Meek %t2009 %cNIPS %f/NIPS/NIPS-2009-4197.pdf %*Positive Semidefinite Metric Learning with Boosting %@Chunhua Shen,Junae Kim,Lei Wang,Anton Hengel %t2009 %cNIPS %f/NIPS/NIPS-2009-4198.pdf %*Fast subtree kernels on graphs %@Nino Shervashidze,Karsten M. Borgwardt %t2009 %cNIPS %f/NIPS/NIPS-2009-4199.pdf %*Neural Implementation of Hierarchical Bayesian Inference by Importance Sampling %@Lei Shi,Thomas L. Griffiths %t2009 %cNIPS %f/NIPS/NIPS-2009-4200.pdf %*Learning Label Embeddings for Nearest-Neighbor Multi-class Classification with an Application to Speech Recognition %@Natasha Singh-miller,Michael Collins %t2009 %cNIPS %f/NIPS/NIPS-2009-4201.pdf %*Semi-supervised Learning using Sparse Eigenfunction Bases %@Kaushik Sinha,Mikhail Belkin %t2009 %cNIPS %f/NIPS/NIPS-2009-4202.pdf %*Hierarchical Modeling of Local Image Features through L_p-Nested Symmetric Distributions %@Matthias Bethge,Eero P. Simoncelli,Fabian H. Sinz %t2009 %cNIPS %f/NIPS/NIPS-2009-4203.pdf %*A Sparse Non-Parametric Approach for Single Channel Separation of Known Sounds %@Paris Smaragdis,Madhusudana Shashanka,Bhiksha Raj %t2009 %cNIPS %f/NIPS/NIPS-2009-4204.pdf %*A Bayesian Analysis of Dynamics in Free Recall %@Richard Socher,Samuel Gershman,Per Sederberg,Kenneth Norman,Adler J. Perotte,David M. Blei %t2009 %cNIPS %f/NIPS/NIPS-2009-4205.pdf %*Kernels and learning curves for Gaussian process regression on random graphs %@Peter Sollich,Matthew Urry,Camille Coti %t2009 %cNIPS %f/NIPS/NIPS-2009-4206.pdf %*Time-Varying Dynamic Bayesian Networks %@Le Song,Mladen Kolar,Eric P. Xing %t2009 %cNIPS %f/NIPS/NIPS-2009-4207.pdf %*Code-specific policy gradient rules for spiking neurons %@Henning Sprekeler,Guillaume Hennequin,Wulfram Gerstner %t2009 %cNIPS %f/NIPS/NIPS-2009-4208.pdf %*Kernel Choice and Classifiability for RKHS Embeddings of Probability Distributions %@Kenji Fukumizu,Arthur Gretton,Gert R. Lanckriet,Bernhard Schölkopf,Bharath K. Sriperumbudur %t2009 %cNIPS %f/NIPS/NIPS-2009-4209.pdf %*On the Convergence of the Concave-Convex Procedure %@Gert R. Lanckriet,Bharath K. Sriperumbudur %t2009 %cNIPS %f/NIPS/NIPS-2009-4210.pdf %*Fast Learning from Non-i.i.d. Observations %@Ingo Steinwart,Andreas Christmann %t2009 %cNIPS %f/NIPS/NIPS-2009-4211.pdf %*Structural inference affects depth perception in the context of potential occlusion %@Ian Stevenson,Konrad Koerding %t2009 %cNIPS %f/NIPS/NIPS-2009-4212.pdf %*The Wisdom of Crowds in the Recollection of Order Information %@Mark Steyvers,Brent Miller,Pernille Hemmer,Michael D. Lee %t2009 %cNIPS %f/NIPS/NIPS-2009-4213.pdf %*Online Learning of Assignments %@Matthew Streeter,Daniel Golovin,Andreas Krause %t2009 %cNIPS %f/NIPS/NIPS-2009-4214.pdf %*Entropic Graph Regularization in Non-Parametric Semi-Supervised Classification %@Amarnag Subramanya,Jeff A. Bilmes %t2009 %cNIPS %f/NIPS/NIPS-2009-4215.pdf %*Efficient Recovery of Jointly Sparse Vectors %@Liang Sun,Jun Liu,Jianhui Chen,Jieping Ye %t2009 %cNIPS %f/NIPS/NIPS-2009-4216.pdf %*Modelling Relational Data using Bayesian Clustered Tensor Factorization %@Ilya Sutskever,Joshua B. Tenenbaum,Ruslan R. Salakhutdinov %t2009 %cNIPS %f/NIPS/NIPS-2009-4217.pdf %*Adapting to the Shifting Intent of Search Queries %@Umar Syed,Aleksandrs Slivkins,Nina Mishra %t2009 %cNIPS %f/NIPS/NIPS-2009-4218.pdf %*Indian Buffet Processes with Power-law Behavior %@Yee W. Teh,Dilan Gorur %t2009 %cNIPS %f/NIPS/NIPS-2009-4219.pdf %*Nonlinear directed acyclic structure learning with weakly additive noise models %@Arthur Gretton,Peter Spirtes,Robert E. Tillman %t2009 %cNIPS %f/NIPS/NIPS-2009-4220.pdf %*Maximin affinity learning of image segmentation %@Kevin Briggman,Winfried Denk,Sebastian Seung,Moritz N. Helmstaedter,Srinivas C. Turaga %t2009 %cNIPS %f/NIPS/NIPS-2009-4221.pdf %*Help or Hinder: Bayesian Models of Social Goal Inference %@Tomer Ullman,Chris Baker,Owen Macindoe,Owain Evans,Noah Goodman,Joshua B. Tenenbaum %t2009 %cNIPS %f/NIPS/NIPS-2009-4222.pdf %*Learning to Rank by Optimizing NDCG Measure %@Hamed Valizadegan,Rong Jin,Ruofei Zhang,Jianchang Mao %t2009 %cNIPS %f/NIPS/NIPS-2009-4223.pdf %*Streaming Pointwise Mutual Information %@Benjamin V. Durme,Ashwin Lall %t2009 %cNIPS %f/NIPS/NIPS-2009-4224.pdf %*Bayesian Source Localization with the Multivariate Laplace Prior %@Marcel V. Gerven,Botond Cseke,Robert Oostenveld,Tom Heskes %t2009 %cNIPS %f/NIPS/NIPS-2009-4225.pdf %*Gaussian process regression with Student-t likelihood %@Jarno Vanhatalo,Pasi Jylänki,Aki Vehtari %t2009 %cNIPS %f/NIPS/NIPS-2009-4226.pdf %*Structured output regression for detection with partial truncation %@Andrea Vedaldi,Andrew Zisserman %t2009 %cNIPS %f/NIPS/NIPS-2009-4227.pdf %*Bootstrapping from Game Tree Search %@Joel Veness,David Silver,Alan Blair,William Uther %t2009 %cNIPS %f/NIPS/NIPS-2009-4228.pdf %*Tracking Dynamic Sources of Malicious Activity at Internet Scale %@Shobha Venkataraman,Avrim Blum,Dawn Song,Subhabrata Sen,Oliver Spatscheck %t2009 %cNIPS %f/NIPS/NIPS-2009-4229.pdf %*Explaining human multiple object tracking as resource-constrained approximate inference in a dynamic probabilistic model %@Ed Vul,George Alvarez,Joshua B. Tenenbaum,Michael J. Black %t2009 %cNIPS %f/NIPS/NIPS-2009-4230.pdf %*Fast Graph Laplacian Regularized Kernel Learning via Semidefinite–Quadratic–Linear Programming %@Xiao-ming Wu,Anthony M. So,Zhenguo Li,Shuo-yen R. Li %t2009 %cNIPS %f/NIPS/NIPS-2009-4231.pdf %*Rethinking LDA: Why Priors Matter %@Hanna M. Wallach,David M. Mimno,Andrew McCallum %t2009 %cNIPS %f/NIPS/NIPS-2009-4232.pdf %*Decoupling Sparsity and Smoothness in the Discrete Hierarchical Dirichlet Process %@Chong Wang,David M. Blei %t2009 %cNIPS %f/NIPS/NIPS-2009-4233.pdf %*Variational Inference for the Nested Chinese Restaurant Process %@Chong Wang,David M. Blei %t2009 %cNIPS %f/NIPS/NIPS-2009-4234.pdf %*A Rate Distortion Approach for Semi-Supervised Conditional Random Fields %@Yang Wang,Gholamreza Haffari,Shaojun Wang,Greg Mori %t2009 %cNIPS %f/NIPS/NIPS-2009-4235.pdf %*Graph Zeta Function in the Bethe Free Energy and Loopy Belief Propagation %@Yusuke Watanabe,Kenji Fukumizu %t2009 %cNIPS %f/NIPS/NIPS-2009-4236.pdf %*Strategy Grafting in Extensive Games %@Kevin Waugh,Nolan Bard,Michael Bowling %t2009 %cNIPS %f/NIPS/NIPS-2009-4237.pdf %*Whose Vote Should Count More: Optimal Integration of Labels from Labelers of Unknown Expertise %@Jacob Whitehill,Ting-fan Wu,Jacob Bergsma,Javier R. Movellan,Paul L. Ruvolo %t2009 %cNIPS %f/NIPS/NIPS-2009-4238.pdf %*Training Factor Graphs with Reinforcement Learning for Efficient MAP Inference %@Khashayar Rohanimanesh,Sameer Singh,Andrew McCallum,Michael J. Black %t2009 %cNIPS %f/NIPS/NIPS-2009-4239.pdf %*Sequential effects reflect parallel learning of multiple environmental regularities %@Matthew Wilder,Matt Jones,Michael C. Mozer %t2009 %cNIPS %f/NIPS/NIPS-2009-4240.pdf %*A Neural Implementation of the Kalman Filter %@Robert Wilson,Leif Finkel %t2009 %cNIPS %f/NIPS/NIPS-2009-4241.pdf %*Sparse Estimation Using General Likelihoods and Non-Factorial Priors %@David P. Wipf,Srikantan S. Nagarajan %t2009 %cNIPS %f/NIPS/NIPS-2009-4242.pdf %*Robust Principal Component Analysis: Exact Recovery of Corrupted Low-Rank Matrices via Convex Optimization %@John Wright,Arvind Ganesh,Shankar Rao,Yigang Peng,Yi Ma %t2009 %cNIPS %f/NIPS/NIPS-2009-4243.pdf %*Learning Bregman Distance Functions and Its Application for Semi-Supervised Clustering %@Lei Wu,Rong Jin,Steven C. Hoi,Jianke Zhu,Nenghai Yu %t2009 %cNIPS %f/NIPS/NIPS-2009-4244.pdf %*Statistical Consistency of Top-k Ranking %@Fen Xia,Tie-yan Liu,Hang Li %t2009 %cNIPS %f/NIPS/NIPS-2009-4245.pdf %*Boosting with Spatial Regularization %@Yongxin Xi,Uri Hasson,Peter J. Ramadge,Zhen J. Xiang %t2009 %cNIPS %f/NIPS/NIPS-2009-4246.pdf %*Adaptive Regularization for Transductive Support Vector Machine %@Zenglin Xu,Rong Jin,Jianke Zhu,Irwin King,Michael Lyu,Zhirong Yang %t2009 %cNIPS %f/NIPS/NIPS-2009-4247.pdf %*Parallel Inference for Latent Dirichlet Allocation on Graphics Processing Units %@Feng Yan,Ningyi Xu,Yuan Qi %t2009 %cNIPS %f/NIPS/NIPS-2009-4248.pdf %*Dirichlet-Bernoulli Alignment: A Generative Model for Multi-Class Multi-Label Multi-Instance Corpora %@Shuang-hong Yang,Hongyuan Zha,Bao-gang Hu %t2009 %cNIPS %f/NIPS/NIPS-2009-4249.pdf %*Heterogeneous multitask learning with joint sparsity constraints %@Xiaolin Yang,Seyoung Kim,Eric P. Xing %t2009 %cNIPS %f/NIPS/NIPS-2009-4250.pdf %*Noise Characterization, Modeling, and Reduction for In Vivo Neural Recording %@Zhi Yang,Qi Zhao,Edward Keefer,Wentai Liu %t2009 %cNIPS %f/NIPS/NIPS-2009-4251.pdf %*Heavy-Tailed Symmetric Stochastic Neighbor Embedding %@Zhirong Yang,Irwin King,Zenglin Xu,Erkki Oja %t2009 %cNIPS %f/NIPS/NIPS-2009-4252.pdf %*Hierarchical Mixture of Classification Experts Uncovers Interactions between Brain Regions %@Bangpeng Yao,Dirk Walther,Diane Beck,Li Fei-fei %t2009 %cNIPS %f/NIPS/NIPS-2009-4253.pdf %*Multi-Step Dyna Planning for Policy Evaluation and Control %@Hengshuai Yao,Shalabh Bhatnagar,Dongcui Diao,Richard S. Sutton,Csaba Szepesvári %t2009 %cNIPS %f/NIPS/NIPS-2009-4254.pdf %*Conditional Random Fields with High-Order Features for Sequence Labeling %@Nan Ye,Wee S. Lee,Hai L. Chieu,Dan Wu %t2009 %cNIPS %f/NIPS/NIPS-2009-4255.pdf %*Analysis of SVM with Indefinite Kernels %@Yiming Ying,Colin Campbell,Mark Girolami %t2009 %cNIPS %f/NIPS/NIPS-2009-4256.pdf %*Sparse Metric Learning via Smooth Optimization %@Yiming Ying,Kaizhu Huang,Colin Campbell %t2009 %cNIPS %f/NIPS/NIPS-2009-4257.pdf %*Nonlinear Learning using Local Coordinate Coding %@Kai Yu,Tong Zhang,Yihong Gong %t2009 %cNIPS %f/NIPS/NIPS-2009-4258.pdf %*A General Projection Property for Distribution Families %@Yao-liang Yu,Yuxi Li,Dale Schuurmans,Csaba Szepesvári %t2009 %cNIPS %f/NIPS/NIPS-2009-4259.pdf %*Optimal Scoring for Unsupervised Learning %@Zhihua Zhang,Guang Dai %t2009 %cNIPS %f/NIPS/NIPS-2009-4260.pdf %*Anomaly Detection with Score functions based on Nearest Neighbor Graphs %@Manqi Zhao,Venkatesh Saligrama %t2009 %cNIPS %f/NIPS/NIPS-2009-4261.pdf %*DUOL: A Double Updating Approach for Online Learning %@Peilin Zhao,Steven C. Hoi,Rong Jin %t2009 %cNIPS %f/NIPS/NIPS-2009-4262.pdf %*Optimizing Multi-Class Spatio-Spectral Filters via Bayes Error Estimation for EEG Classification %@Wenming Zheng,Zhouchen Lin %t2009 %cNIPS %f/NIPS/NIPS-2009-4263.pdf %*Efficient Moments-based Permutation Tests %@Chunxiao Zhou,Huixia J. Wang,Yongmei M. Wang %t2009 %cNIPS %f/NIPS/NIPS-2009-4264.pdf %*Canonical Time Warping for Alignment of Human Behavior %@Feng Zhou,Fernando Torre %t2009 %cNIPS %f/NIPS/NIPS-2009-4265.pdf %*Non-Parametric Bayesian Dictionary Learning for Sparse Image Representations %@Mingyuan Zhou,Haojun Chen,Lu Ren,Guillermo Sapiro,Lawrence Carin,John W. Paisley %t2009 %cNIPS %f/NIPS/NIPS-2009-4266.pdf %*Nonparametric Bayesian Texture Learning and Synthesis %@Long Zhu,Yuanahao Chen,Bill Freeman,Antonio Torralba %t2009 %cNIPS %f/NIPS/NIPS-2009-4267.pdf %*Human Rademacher Complexity %@Xiaojin Zhu,Bryan R. Gibson,Timothy T. Rogers %t2009 %cNIPS %f/NIPS/NIPS-2009-4268.pdf %*Slow Learners are Fast %@Martin Zinkevich,John Langford,Alex J. Smola %t2009 %cNIPS %f/NIPS/NIPS-2009-4269.pdf %*The 'tree-dependent components' of natural scenes are edge filters %@Daniel Zoran,Yair Weiss %t2009 %cNIPS %f/NIPS/NIPS-2009-4270.pdf %*Structure Learning in Human Sequential Decision-Making %@Daniel Acuna,Paul R. Schrater %t2008 %cNIPS %f/NIPS/NIPS-2008-4271.pdf %*The Gaussian Process Density Sampler %@Iain Murray,David MacKay,Ryan P. Adams %t2008 %cNIPS %f/NIPS/NIPS-2008-4272.pdf %*Online Models for Content Optimization %@Deepak Agarwal,Bee-chung Chen,Pradheep Elango,Nitin Motgi,Seung-taek Park,Raghu Ramakrishnan,Scott Roy,Joe Zachariah %t2008 %cNIPS %f/NIPS/NIPS-2008-4273.pdf %*Mixed Membership Stochastic Blockmodels %@Edo M. Airoldi,David M. Blei,Stephen E. Fienberg,Eric P. Xing %t2008 %cNIPS %f/NIPS/NIPS-2008-4274.pdf %*Nonrigid Structure from Motion in Trajectory Space %@Ijaz Akhter,Yaser Sheikh,Sohaib Khan,Takeo Kanade %t2008 %cNIPS %f/NIPS/NIPS-2008-4275.pdf %*Probabilistic detection of short events, with application to critical care monitoring %@Norm Aleks,Stuart J. Russell,Michael G. Madden,Diane Morabito,Kristan Staudenmayer,Mitchell Cohen,Geoffrey T. Manley %t2008 %cNIPS %f/NIPS/NIPS-2008-4276.pdf %*Sparse Convolved Gaussian Processes for Multi-output Regression %@Mauricio Alvarez,Neil D. Lawrence %t2008 %cNIPS %f/NIPS/NIPS-2008-4277.pdf %*A Transductive Bound for the Voted Classifier with an Application to Semi-supervised Learning %@Massih Amini,Nicolas Usunier,François Laviolette %t2008 %cNIPS %f/NIPS/NIPS-2008-4278.pdf %*Sparse probabilistic projections %@Cédric Archambeau,Francis R. Bach %t2008 %cNIPS %f/NIPS/NIPS-2008-4279.pdf %*Asynchronous Distributed Learning of Topic Models %@Padhraic Smyth,Max Welling,Arthur U. Asuncion %t2008 %cNIPS %f/NIPS/NIPS-2008-4280.pdf %*Near-optimal Regret Bounds for Reinforcement Learning %@Peter Auer,Thomas Jaksch,Ronald Ortner %t2008 %cNIPS %f/NIPS/NIPS-2008-4281.pdf %*Analyzing human feature learning as nonparametric Bayesian inference %@Thomas L. Griffiths,Joseph L. Austerweil %t2008 %cNIPS %f/NIPS/NIPS-2008-4282.pdf %*Differentiable Sparse Coding %@J. A. Bagnell,David M. Bradley %t2008 %cNIPS %f/NIPS/NIPS-2008-4283.pdf %*Measures of Clustering Quality: A Working Set of Axioms for Clustering %@Shai Ben-David,Margareta Ackerman %t2008 %cNIPS %f/NIPS/NIPS-2008-4284.pdf %*Characterizing neural dependencies with copula models %@Pietro Berkes,Frank Wood,Jonathan W. Pillow %t2008 %cNIPS %f/NIPS/NIPS-2008-4285.pdf %*On Bootstrapping the ROC Curve %@Patrice Bertail,Stéphan J. Clémençcon,Nicolas Vayatis %t2008 %cNIPS %f/NIPS/NIPS-2008-4286.pdf %*Transfer Learning by Distribution Matching for Targeted Advertising %@Steffen Bickel,Christoph Sawade,Tobias Scheffer %t2008 %cNIPS %f/NIPS/NIPS-2008-4287.pdf %*Learning Taxonomies by Dependence Maximization %@Matthew Blaschko,Arthur Gretton %t2008 %cNIPS %f/NIPS/NIPS-2008-4288.pdf %*Bayesian Synchronous Grammar Induction %@Phil Blunsom,Trevor Cohn,Miles Osborne %t2008 %cNIPS %f/NIPS/NIPS-2008-4289.pdf %*Goal-directed decision making in prefrontal cortex: a computational framework %@Matthew Botvinick,James An %t2008 %cNIPS %f/NIPS/NIPS-2008-4290.pdf %*Efficient Inference in Phylogenetic InDel Trees %@Alexandre Bouchard-côté,Dan Klein,Michael I. Jordan %t2008 %cNIPS %f/NIPS/NIPS-2008-4291.pdf %*Syntactic Topic Models %@Jordan L. Boyd-graber,David M. Blei %t2008 %cNIPS %f/NIPS/NIPS-2008-4292.pdf %*A spatially varying two-sample recombinant coalescent, with applications to HIV escape response %@Alexander Braunstein,Zhi Wei,Shane T. Jensen,Jon D. Mcauliffe %t2008 %cNIPS %f/NIPS/NIPS-2008-4293.pdf %*Online Optimization in X-Armed Bandits %@Sébastien Bubeck,Gilles Stoltz,Csaba Szepesvári,Rémi Munos %t2008 %cNIPS %f/NIPS/NIPS-2008-4294.pdf %*Learning Transformational Invariants from Natural Movies %@Charles Cadieu,Bruno A. Olshausen %t2008 %cNIPS %f/NIPS/NIPS-2008-4295.pdf %*Accelerating Bayesian Inference over Nonlinear Differential Equations with Gaussian Processes %@Ben Calderhead,Mark Girolami,Neil D. Lawrence %t2008 %cNIPS %f/NIPS/NIPS-2008-4296.pdf %*Covariance Estimation for High Dimensional Data Vectors Using the Sparse Matrix Transform %@Guangzhi Cao,Charles Bouman %t2008 %cNIPS %f/NIPS/NIPS-2008-4297.pdf %*An interior-point stochastic approximation method and an L1-regularized delta rule %@Peter Carbonetto,Mark Schmidt,Nando D. Freitas %t2008 %cNIPS %f/NIPS/NIPS-2008-4298.pdf %*Human Active Learning %@Rui M. Castro,Charles Kalish,Robert Nowak,Ruichen Qian,Tim Rogers,Xiaojin Zhu %t2008 %cNIPS %f/NIPS/NIPS-2008-4299.pdf %*Linear Classification and Selective Sampling Under Low Noise Conditions %@Giovanni Cavallanti,Nicolò Cesa-bianchi,Claudio Gentile %t2008 %cNIPS %f/NIPS/NIPS-2008-4300.pdf %*Sparse Signal Recovery Using Markov Random Fields %@Volkan Cevher,Marco F. Duarte,Chinmay Hegde,Richard Baraniuk %t2008 %cNIPS %f/NIPS/NIPS-2008-4301.pdf %*Multi-task Gaussian Process Learning of Robot Inverse Dynamics %@Christopher Williams,Stefan Klanke,Sethu Vijayakumar,Kian M. Chai %t2008 %cNIPS %f/NIPS/NIPS-2008-4302.pdf %*Mortal Multi-Armed Bandits %@Deepayan Chakrabarti,Ravi Kumar,Filip Radlinski,Eli Upfal %t2008 %cNIPS %f/NIPS/NIPS-2008-4303.pdf %*Tighter Bounds for Structured Estimation %@Olivier Chapelle,Chuong B. Do,Choon H. Teo,Quoc V. Le,Alex J. Smola %t2008 %cNIPS %f/NIPS/NIPS-2008-4304.pdf %*Privacy-preserving logistic regression %@Kamalika Chaudhuri,Claire Monteleoni %t2008 %cNIPS %f/NIPS/NIPS-2008-4305.pdf %*Using Bayesian Dynamical Systems for Motion Template Libraries %@Silvia Chiappa,Jens Kober,Jan R. Peters %t2008 %cNIPS %f/NIPS/NIPS-2008-4306.pdf %*Empirical performance maximization for linear rank statistics %@Stéphan J. Clémençcon,Nicolas Vayatis %t2008 %cNIPS %f/NIPS/NIPS-2008-4307.pdf %*Overlaying classifiers: a practical approach for optimal ranking %@Stéphan J. Clémençcon,Nicolas Vayatis %t2008 %cNIPS %f/NIPS/NIPS-2008-4308.pdf %*Logistic Normal Priors for Unsupervised Probabilistic Grammar Induction %@Shay B. Cohen,Kevin Gimpel,Noah A. Smith %t2008 %cNIPS %f/NIPS/NIPS-2008-4309.pdf %*Particle Filter-based Policy Gradient in POMDPs %@Pierre-arnaud Coquelin,Romain Deguest,Rémi Munos %t2008 %cNIPS %f/NIPS/NIPS-2008-4310.pdf %*Exact Convex Confidence-Weighted Learning %@Koby Crammer,Mark Dredze,Fernando Pereira %t2008 %cNIPS %f/NIPS/NIPS-2008-4311.pdf %*Translated Learning: Transfer Learning across Different Feature Spaces %@Wenyuan Dai,Yuqiang Chen,Gui-rong Xue,Qiang Yang,Yong Yu %t2008 %cNIPS %f/NIPS/NIPS-2008-4312.pdf %*Adapting to a Market Shock: Optimal Sequential Market-Making %@Sanmay Das,Malik Magdon-Ismail %t2008 %cNIPS %f/NIPS/NIPS-2008-4313.pdf %*Temporal Difference Based Actor Critic Learning - Convergence and Neural Implementation %@Dotan D. Castro,Dmitry Volkinshtein,Ron Meir %t2008 %cNIPS %f/NIPS/NIPS-2008-4314.pdf %*Look Ma, No Hands: Analyzing the Monotonic Feature Abstraction for Text Classification %@Doug Downey,Oren Etzioni %t2008 %cNIPS %f/NIPS/NIPS-2008-4315.pdf %*Generative and Discriminative Learning with Unknown Labeling Bias %@Steven J. Phillips,Miroslav Dudík %t2008 %cNIPS %f/NIPS/NIPS-2008-4316.pdf %*A Convex Upper Bound on the Log-Partition Function for Binary Distributions %@Laurent E. Ghaoui,Assane Gueye %t2008 %cNIPS %f/NIPS/NIPS-2008-4317.pdf %*Learning Bounded Treewidth Bayesian Networks %@Gal Elidan,Stephen Gould %t2008 %cNIPS %f/NIPS/NIPS-2008-4318.pdf %*Interpreting the neural code with Formal Concept Analysis %@Dominik Endres,Peter Foldiak %t2008 %cNIPS %f/NIPS/NIPS-2008-4319.pdf %*ICA based on a Smooth Estimation of the Differential Entropy %@Lev Faivishevsky,Jacob Goldberger %t2008 %cNIPS %f/NIPS/NIPS-2008-4320.pdf %*Regularized Policy Iteration %@Amir M. Farahmand,Mohammad Ghavamzadeh,Shie Mannor,Csaba Szepesvári %t2008 %cNIPS %f/NIPS/NIPS-2008-4321.pdf %*Resolution Limits of Sparse Coding in High Dimensions %@Sundeep Rangan,Vivek Goyal,Alyson K. Fletcher %t2008 %cNIPS %f/NIPS/NIPS-2008-4322.pdf %*Nonparametric Bayesian Learning of Switching Linear Dynamical Systems %@Emily Fox,Erik B. Sudderth,Michael I. Jordan,Alan S. Willsky %t2008 %cNIPS %f/NIPS/NIPS-2008-4323.pdf %*Predicting the Geometry of Metal Binding Sites from Protein Sequence %@Paolo Frasconi,Andrea Passerini %t2008 %cNIPS %f/NIPS/NIPS-2008-4324.pdf %*Characteristic Kernels on Groups and Semigroups %@Kenji Fukumizu,Arthur Gretton,Bernhard Schölkopf,Bharath K. Sriperumbudur %t2008 %cNIPS %f/NIPS/NIPS-2008-4325.pdf %*Tracking Changing Stimuli in Continuous Attractor Neural Networks %@K. Wong,Si Wu,Chi Fung %t2008 %cNIPS %f/NIPS/NIPS-2008-4326.pdf %*An Homotopy Algorithm for the Lasso with Online Observations %@Pierre Garrigues,Laurent E. Ghaoui %t2008 %cNIPS %f/NIPS/NIPS-2008-4327.pdf %*Dependent Dirichlet Process Spike Sorting %@Jan Gasthaus,Frank Wood,Dilan Gorur,Yee W. Teh %t2008 %cNIPS %f/NIPS/NIPS-2008-4328.pdf %*Predictive Indexing for Fast Search %@Sharad Goel,John Langford,Alexander L. Strehl %t2008 %cNIPS %f/NIPS/NIPS-2008-4329.pdf %*Self-organization using synaptic plasticity %@Vicençc Gómez,Andreas Kaltenbrunner,Vicente López,Hilbert J. Kappen %t2008 %cNIPS %f/NIPS/NIPS-2008-4330.pdf %*An Efficient Sequential Monte Carlo Algorithm for Coalescent Clustering %@Dilan Gorur,Yee W. Teh %t2008 %cNIPS %f/NIPS/NIPS-2008-4331.pdf %*A Massively Parallel Digital Learning Processor %@Hans P. Graf,Srihari Cadambi,Venkata Jakkula,Murugan Sankaradass,Eric Cosatto,Srimat Chakradhar,Igor Dourdanovic %t2008 %cNIPS %f/NIPS/NIPS-2008-4332.pdf %*Support Vector Machines with a Reject Option %@Yves Grandvalet,Alain Rakotomamonjy,Joseph Keshet,Stéphane Canu %t2008 %cNIPS %f/NIPS/NIPS-2008-4333.pdf %*Offline Handwriting Recognition with Multidimensional Recurrent Neural Networks %@Alex Graves,Juergen Schmidhuber %t2008 %cNIPS %f/NIPS/NIPS-2008-4334.pdf %*Modeling human function learning with Gaussian processes %@Thomas L. Griffiths,Chris Lucas,Joseph Williams,Michael L. Kalish %t2008 %cNIPS %f/NIPS/NIPS-2008-4335.pdf %*A ``Shape Aware'' Model for semi-supervised Learning of Objects and its Context %@Abhinav Gupta,Jianbo Shi,Larry S. Davis %t2008 %cNIPS %f/NIPS/NIPS-2008-4336.pdf %*An improved estimator of Variance Explained in the presence of noise %@Ralf M. Haefner,Bruce G. Cumming %t2008 %cNIPS %f/NIPS/NIPS-2008-4337.pdf %*Unifying the Sensory and Motor Components of Sensorimotor Adaptation %@Adrian Haith,Carl P. Jackson,R. C. Miall,Sethu Vijayakumar %t2008 %cNIPS %f/NIPS/NIPS-2008-4338.pdf %*Extended Grassmann Kernels for Subspace-Based Learning %@Jihun Hamm,Daniel D. Lee %t2008 %cNIPS %f/NIPS/NIPS-2008-4339.pdf %*Kernel Change-point Analysis %@Zaïd Harchaoui,Eric Moulines,Francis R. Bach %t2008 %cNIPS %f/NIPS/NIPS-2008-4340.pdf %*Estimating vector fields using sparse basis field expansions %@Stefan Haufe,Vadim V. Nikulin,Andreas Ziehe,Klaus-Robert Müller,Guido Nolte %t2008 %cNIPS %f/NIPS/NIPS-2008-4341.pdf %*Learning Hybrid Models for Image Annotation with Partially Labeled Data %@Xuming He,Richard S. Zemel %t2008 %cNIPS %f/NIPS/NIPS-2008-4342.pdf %*Shape-Based Object Localization for Descriptive Classification %@Geremy Heitz,Gal Elidan,Benjamin Packer,Daphne Koller %t2008 %cNIPS %f/NIPS/NIPS-2008-4343.pdf %*Cascaded Classification Models: Combining Models for Holistic Scene Understanding %@Geremy Heitz,Stephen Gould,Ashutosh Saxena,Daphne Koller %t2008 %cNIPS %f/NIPS/NIPS-2008-4344.pdf %*Online Prediction on Large Diameter Graphs %@Mark Herbster,Guy Lever,Massimiliano Pontil %t2008 %cNIPS %f/NIPS/NIPS-2008-4345.pdf %*Fast Prediction on a Tree %@Mark Herbster,Massimiliano Pontil,Sergio R. Galeano %t2008 %cNIPS %f/NIPS/NIPS-2008-4346.pdf %*Effects of Stimulus Type and of Error-Correcting Code Design on BCI Speller Performance %@Jeremy Hill,Jason Farquhar,Suzanna Martens,Felix Biessmann,Bernhard Schölkopf %t2008 %cNIPS %f/NIPS/NIPS-2008-4347.pdf %*QUIC-SVD: Fast SVD Using Cosine Trees %@Michael P. Holmes,Jr. Isbell,Charles Lee,Alexander G. Gray %t2008 %cNIPS %f/NIPS/NIPS-2008-4348.pdf %*Dynamic visual attention: searching for coding length increments %@Xiaodi Hou,Liqing Zhang %t2008 %cNIPS %f/NIPS/NIPS-2008-4349.pdf %*Nonlinear causal discovery with additive noise models %@Patrik O. Hoyer,Dominik Janzing,Joris M. Mooij,Jonas Peters,Bernhard Schölkopf %t2008 %cNIPS %f/NIPS/NIPS-2008-4350.pdf %*Structured ranking learning using cumulative distribution networks %@Jim C. Huang,Brendan J. Frey %t2008 %cNIPS %f/NIPS/NIPS-2008-4351.pdf %*Spectral Clustering with Perturbed Data %@Ling Huang,Donghui Yan,Nina Taft,Michael I. Jordan %t2008 %cNIPS %f/NIPS/NIPS-2008-4352.pdf %*Bio-inspired Real Time Sensory Map Realignment in a Robotic Barn Owl %@Juan Huo,Zhijun Yang,Alan F. Murray %t2008 %cNIPS %f/NIPS/NIPS-2008-4353.pdf %*Theory of matching pursuit %@Zakria Hussain,John S. Shawe-taylor %t2008 %cNIPS %f/NIPS/NIPS-2008-4354.pdf %*Psychiatry: Insights into depression through normative decision-making models %@Quentin J. Huys,Joshua Vogelstein,Peter Dayan %t2008 %cNIPS %f/NIPS/NIPS-2008-4355.pdf %*Continuously-adaptive discretization for message-passing algorithms %@Michael Isard,John MacCormick,Kannan Achan %t2008 %cNIPS %f/NIPS/NIPS-2008-4356.pdf %*Clustered Multi-Task Learning: A Convex Formulation %@Laurent Jacob,Jean-philippe Vert,Francis R. Bach %t2008 %cNIPS %f/NIPS/NIPS-2008-4357.pdf %*Inferring rankings under constrained sensing %@Srikanth Jagabathula,Devavrat Shah %t2008 %cNIPS %f/NIPS/NIPS-2008-4358.pdf %*Online Metric Learning and Fast Similarity Search %@Prateek Jain,Brian Kulis,Inderjit S. Dhillon,Kristen Grauman %t2008 %cNIPS %f/NIPS/NIPS-2008-4359.pdf %*Natural Image Denoising with Convolutional Networks %@Viren Jain,Sebastian Seung %t2008 %cNIPS %f/NIPS/NIPS-2008-4360.pdf %*Multi-label Multiple Kernel Learning %@Shuiwang Ji,Liang Sun,Rong Jin,Jieping Ye %t2008 %cNIPS %f/NIPS/NIPS-2008-4361.pdf %*Optimal Response Initiation: Why Recent Experience Matters %@Matt Jones,Sachiko Kinoshita,Michael C. Mozer %t2008 %cNIPS %f/NIPS/NIPS-2008-4362.pdf %*On the Complexity of Linear Prediction: Risk Bounds, Margin Bounds, and Regularization %@Sham M. Kakade,Karthik Sridharan,Ambuj Tewari %t2008 %cNIPS %f/NIPS/NIPS-2008-4363.pdf %*On the Generalization Ability of Online Strongly Convex Programming Algorithms %@Sham M. Kakade,Ambuj Tewari %t2008 %cNIPS %f/NIPS/NIPS-2008-4364.pdf %*Efficient Direct Density Ratio Estimation for Non-stationarity Adaptation and Outlier Detection %@Takafumi Kanamori,Shohei Hido,Masashi Sugiyama %t2008 %cNIPS %f/NIPS/NIPS-2008-4365.pdf %*Extracting State Transition Dynamics from Multiple Spike Trains with Correlated Poisson HMM %@Kentaro Katahira,Jun Nishikawa,Kazuo Okanoya,Masato Okada %t2008 %cNIPS %f/NIPS/NIPS-2008-4366.pdf %*An ideal observer model of infant object perception %@Charles Kemp,Fei Xu %t2008 %cNIPS %f/NIPS/NIPS-2008-4367.pdf %*Performance analysis for L\_2 kernel classification %@Jooseuk Kim,Clayton Scott %t2008 %cNIPS %f/NIPS/NIPS-2008-4368.pdf %*MCBoost: Multiple Classifier Boosting for Perceptual Co-clustering of Images and Visual Features %@Tae-kyun Kim,Roberto Cipolla %t2008 %cNIPS %f/NIPS/NIPS-2008-4369.pdf %*Policy Search for Motor Primitives in Robotics %@Jens Kober,Jan R. Peters %t2008 %cNIPS %f/NIPS/NIPS-2008-4370.pdf %*On the asymptotic equivalence between differential Hebbian and temporal difference learning using a local third factor %@Christoph Kolodziejski,Bernd Porr,Minija Tamosiunaite,Florentin Wörgötter %t2008 %cNIPS %f/NIPS/NIPS-2008-4371.pdf %*Clustering via LP-based Stabilities %@Nikos Komodakis,Nikos Paragios,Georgios Tziritas %t2008 %cNIPS %f/NIPS/NIPS-2008-4372.pdf %*Counting Solution Clusters in Graph Coloring Problems Using Belief Propagation %@Lukas Kroc,Ashish Sabharwal,Bart Selman %t2008 %cNIPS %f/NIPS/NIPS-2008-4373.pdf %*Scalable Algorithms for String Kernels with Inexact Matching %@Pavel P. Kuksa,Pai-hsi Huang,Vladimir Pavlovic %t2008 %cNIPS %f/NIPS/NIPS-2008-4374.pdf %*Improved Moves for Truncated Convex Models %@Philip Torr,M. P. Kumar %t2008 %cNIPS %f/NIPS/NIPS-2008-4375.pdf %*DiscLDA: Discriminative Learning for Dimensionality Reduction and Classification %@Simon Lacoste-Julien,Fei Sha,Michael I. Jordan %t2008 %cNIPS %f/NIPS/NIPS-2008-4376.pdf %*Sparse Online Learning via Truncated Gradient %@John Langford,Lihong Li,Tong Zhang %t2008 %cNIPS %f/NIPS/NIPS-2008-4377.pdf %*Multiscale Random Fields with Application to Contour Grouping %@Longin J. Latecki,Chengen Lu,Marc Sobel,Xiang Bai %t2008 %cNIPS %f/NIPS/NIPS-2008-4378.pdf %*Adaptive Template Matching with Shift-Invariant Semi-NMF %@Jonathan L. Roux,Alain D. Cheveigné,Lucas C. Parra %t2008 %cNIPS %f/NIPS/NIPS-2008-4379.pdf %*Fast High-dimensional Kernel Summations Using the Monte Carlo Multipole Method %@Dongryeol Lee,Alexander G. Gray %t2008 %cNIPS %f/NIPS/NIPS-2008-4380.pdf %*Modeling the effects of memory on human online sentence processing with particle filters %@Roger P. Levy,Florencia Reali,Thomas L. Griffiths %t2008 %cNIPS %f/NIPS/NIPS-2008-4381.pdf %*Designing neurophysiology experiments to optimally constrain receptive field models along parametric submanifolds %@Jeremy Lewi,Robert Butera,David M. Schneider,Sarah Woolley,Liam Paninski %t2008 %cNIPS %f/NIPS/NIPS-2008-4382.pdf %*One sketch for all: Theory and Application of Conditional Random Sampling %@Ping Li,Kenneth W. Church,Trevor J. Hastie %t2008 %cNIPS %f/NIPS/NIPS-2008-4383.pdf %*Dimensionality Reduction for Data in Multiple Feature Representations %@Yen-yu Lin,Tyng-luh Liu,Chiou-shann Fuh %t2008 %cNIPS %f/NIPS/NIPS-2008-4384.pdf %*Nonparametric regression and classification with joint sparsity constraints %@Han Liu,Larry Wasserman,John D. Lafferty %t2008 %cNIPS %f/NIPS/NIPS-2008-4385.pdf %*Adaptive Martingale Boosting %@Phil Long,Rocco Servedio %t2008 %cNIPS %f/NIPS/NIPS-2008-4386.pdf %*A rational model of preference learning and choice prediction by children %@Christopher G. Lucas,Thomas L. Griffiths,Fei Xu,Christine Fawcett %t2008 %cNIPS %f/NIPS/NIPS-2008-4387.pdf %*A computational model of hippocampal function in trace conditioning %@Elliot A. Ludvig,Richard S. Sutton,Eric Verbeek,E. J. Kehoe %t2008 %cNIPS %f/NIPS/NIPS-2008-4388.pdf %*Stress, noradrenaline, and realistic prediction of mouse behaviour using reinforcement learning %@Carmen Sandi,Wulfram Gerstner,Gediminas Lukšys %t2008 %cNIPS %f/NIPS/NIPS-2008-4389.pdf %*Reducing statistical dependencies in natural signals using radial Gaussianization %@Siwei Lyu,Eero P. Simoncelli %t2008 %cNIPS %f/NIPS/NIPS-2008-4390.pdf %*Influence of graph construction on graph-based clustering measures %@Markus Maier,Ulrike V. Luxburg,Matthias Hein %t2008 %cNIPS %f/NIPS/NIPS-2008-4391.pdf %*Supervised Dictionary Learning %@Julien Mairal,Jean Ponce,Guillermo Sapiro,Andrew Zisserman,Francis R. Bach %t2008 %cNIPS %f/NIPS/NIPS-2008-4392.pdf %*Domain Adaptation with Multiple Sources %@Yishay Mansour,Mehryar Mohri,Afshin Rostamizadeh %t2008 %cNIPS %f/NIPS/NIPS-2008-4393.pdf %*On the Design of Loss Functions for Classification: theory, robustness to outliers, and SavageBoost %@Hamed Masnadi-shirazi,Nuno Vasconcelos %t2008 %cNIPS %f/NIPS/NIPS-2008-4394.pdf %*Robust Near-Isometric Matching via Structured Learning of Graphical Models %@Alex J. Smola,Julian J. Mcauley,Tibério S. Caetano %t2008 %cNIPS %f/NIPS/NIPS-2008-4395.pdf %*MDPs with Non-Deterministic Policies %@Mahdi M. Fard,Joelle Pineau %t2008 %cNIPS %f/NIPS/NIPS-2008-4396.pdf %*Gates %@Tom Minka,John Winn %t2008 %cNIPS %f/NIPS/NIPS-2008-4397.pdf %*A Scalable Hierarchical Distributed Language Model %@Andriy Mnih,Geoffrey E. Hinton %t2008 %cNIPS %f/NIPS/NIPS-2008-4398.pdf %*Bayesian Exponential Family PCA %@Shakir Mohamed,Zoubin Ghahramani,Katherine A. Heller %t2008 %cNIPS %f/NIPS/NIPS-2008-4399.pdf %*Rademacher Complexity Bounds for Non-I.I.D. Processes %@Mehryar Mohri,Afshin Rostamizadeh %t2008 %cNIPS %f/NIPS/NIPS-2008-4400.pdf %*Bounds on marginal probability distributions %@Joris M. Mooij,Hilbert J. Kappen %t2008 %cNIPS %f/NIPS/NIPS-2008-4401.pdf %*Automatic online tuning for fast Gaussian summation %@Vlad I. Morariu,Balaji V. Srinivasan,Vikas C. Raykar,Ramani Duraiswami,Larry S. Davis %t2008 %cNIPS %f/NIPS/NIPS-2008-4402.pdf %*Artificial Olfactory Brain for Mixture Identification %@Mehmet K. Muezzinoglu,Alexander Vergara,Ramon Huerta,Thomas Nowotny,Nikolai Rulkov,Henry Abarbanel,Allen Selverston,Mikhail Rabinovich %t2008 %cNIPS %f/NIPS/NIPS-2008-4403.pdf %*Relative Performance Guarantees for Approximate Inference in Latent Dirichlet Allocation %@Indraneel Mukherjee,David M. Blei %t2008 %cNIPS %f/NIPS/NIPS-2008-4404.pdf %*Evaluating probabilities under high-dimensional latent variable models %@Iain Murray,Ruslan R. Salakhutdinov %t2008 %cNIPS %f/NIPS/NIPS-2008-4405.pdf %*Implicit Mixtures of Restricted Boltzmann Machines %@Vinod Nair,Geoffrey E. Hinton %t2008 %cNIPS %f/NIPS/NIPS-2008-4406.pdf %*Characterizing response behavior in multisensory perception with conflicting cues %@Rama Natarajan,Iain Murray,Ladan Shams,Richard S. Zemel %t2008 %cNIPS %f/NIPS/NIPS-2008-4407.pdf %*Phase transitions for high-dimensional joint support recovery %@Sahand Negahban,Martin J. Wainwright %t2008 %cNIPS %f/NIPS/NIPS-2008-4408.pdf %*Hebbian Learning of Bayes Optimal Decisions %@Bernhard Nessler,Michael Pfeiffer,Wolfgang Maass %t2008 %cNIPS %f/NIPS/NIPS-2008-4409.pdf %*Fitted Q-iteration by Advantage Weighted Regression %@Gerhard Neumann,Jan R. Peters %t2008 %cNIPS %f/NIPS/NIPS-2008-4410.pdf %*Robust Kernel Principal Component Analysis %@Minh H. Nguyen,Fernando Torre %t2008 %cNIPS %f/NIPS/NIPS-2008-4411.pdf %*Local Gaussian Process Regression for Real Time Online Model Learning %@Duy Nguyen-tuong,Jan R. Peters,Matthias Seeger %t2008 %cNIPS %f/NIPS/NIPS-2008-4412.pdf %*On the Efficient Minimization of Classification Calibrated Surrogates %@Richard Nock,Frank Nielsen %t2008 %cNIPS %f/NIPS/NIPS-2008-4413.pdf %*Multi-resolution Exploration in Continuous Spaces %@Ali Nouri,Michael L. Littman %t2008 %cNIPS %f/NIPS/NIPS-2008-4414.pdf %*High-dimensional support union recovery in multivariate regression %@Guillaume R. Obozinski,Martin J. Wainwright,Michael I. Jordan %t2008 %cNIPS %f/NIPS/NIPS-2008-4415.pdf %*A general framework for investigating how far the decoding process in the brain can be simplified %@Masafumi Oizumi,Toshiyuki Ishii,Kazuya Ishibashi,Toshihiko Hosoya,Masato Okada %t2008 %cNIPS %f/NIPS/NIPS-2008-4416.pdf %*Modeling Short-term Noise Dependence of Spike Counts in Macaque Prefrontal Cortex %@Arno Onken,Steffen Grünewälder,Matthias Munk,Klaus Obermayer %t2008 %cNIPS %f/NIPS/NIPS-2008-4417.pdf %*Improving on Expectation Propagation %@Manfred Opper,Ulrich Paquet,Ole Winther %t2008 %cNIPS %f/NIPS/NIPS-2008-4418.pdf %*Finding Latent Causes in Causal Networks: an Efficient Approach Based on Markov Blankets %@Jean-philippe Pellet,André Elisseeff %t2008 %cNIPS %f/NIPS/NIPS-2008-4419.pdf %*Biasing Approximate Dynamic Programming with a Lower Discount Factor %@Marek Petrik,Bruno Scherrer %t2008 %cNIPS %f/NIPS/NIPS-2008-4420.pdf %*Cell Assemblies in Large Sparse Inhibitory Networks of Biologically Realistic Spiking Neurons %@Adam Ponzi,Jeff Wickens %t2008 %cNIPS %f/NIPS/NIPS-2008-4421.pdf %*Global Ranking Using Continuous Conditional Random Fields %@Tao Qin,Tie-yan Liu,Xu-dong Zhang,De-sheng Wang,Hang Li %t2008 %cNIPS %f/NIPS/NIPS-2008-4422.pdf %*Kernelized Sorting %@Novi Quadrianto,Le Song,Alex J. Smola %t2008 %cNIPS %f/NIPS/NIPS-2008-4423.pdf %*A mixture model for the evolution of gene expression in non-homogeneous datasets %@Gerald Quon,Yee W. Teh,Esther Chan,Timothy Hughes,Michael Brudno,Quaid D. Morris %t2008 %cNIPS %f/NIPS/NIPS-2008-4424.pdf %*Near-minimax recursive density estimation on the binary hypercube %@Maxim Raginsky,Svetlana Lazebnik,Rebecca Willett,Jorge Silva %t2008 %cNIPS %f/NIPS/NIPS-2008-4425.pdf %*Weighted Sums of Random Kitchen Sinks: Replacing minimization with randomization in learning %@Ali Rahimi,Benjamin Recht %t2008 %cNIPS %f/NIPS/NIPS-2008-4426.pdf %*The Infinite Hierarchical Factor Regression Model %@Piyush Rai,Hal Daume %t2008 %cNIPS %f/NIPS/NIPS-2008-4427.pdf %*Model Selection in Gaussian Graphical Models: High-Dimensional Consistency of \boldmath\ell_1-regularized MLE %@Garvesh Raskutti,Bin Yu,Martin J. Wainwright,Pradeep K. Ravikumar %t2008 %cNIPS %f/NIPS/NIPS-2008-4428.pdf %*Nonparametric sparse hierarchical models describe V1 fMRI responses to natural images %@Vincent Q. Vu,Bin Yu,Thomas Naselaris,Kendrick Kay,Jack Gallant,Pradeep K. Ravikumar %t2008 %cNIPS %f/NIPS/NIPS-2008-4429.pdf %*Bayesian Model of Behaviour in Economic Games %@Debajyoti Ray,Brooks King-casas,P. R. Montague,Peter Dayan %t2008 %cNIPS %f/NIPS/NIPS-2008-4430.pdf %*Temporal Dynamics of Cognitive Control %@Jeremy Reynolds,Michael C. Mozer %t2008 %cNIPS %f/NIPS/NIPS-2008-4431.pdf %*Signal-to-Noise Ratio Analysis of Policy Gradient Algorithms %@John W. Roberts,Russ Tedrake %t2008 %cNIPS %f/NIPS/NIPS-2008-4432.pdf %*Non-stationary dynamic Bayesian networks %@Joshua W. Robinson,Alexander J. Hartemink %t2008 %cNIPS %f/NIPS/NIPS-2008-4433.pdf %*The Mondrian Process %@Daniel M. Roy,Yee W. Teh %t2008 %cNIPS %f/NIPS/NIPS-2008-4434.pdf %*Optimization on a Budget: A Reinforcement Learning Approach %@Paul L. Ruvolo,Ian Fasel,Javier R. Movellan %t2008 %cNIPS %f/NIPS/NIPS-2008-4435.pdf %*Unsupervised Learning of Visual Sense Models for Polysemous Words %@Kate Saenko,Trevor Darrell %t2008 %cNIPS %f/NIPS/NIPS-2008-4436.pdf %*Regularized Learning with Networks of Features %@Ted Sandler,John Blitzer,Partha P. Talukdar,Lyle H. Ungar %t2008 %cNIPS %f/NIPS/NIPS-2008-4437.pdf %*Generative versus discriminative training of RBMs for classification of fMRI images %@Tanya Schmah,Geoffrey E. Hinton,Steven L. Small,Stephen Strother,Richard S. Zemel %t2008 %cNIPS %f/NIPS/NIPS-2008-4438.pdf %*Efficient Exact Inference in Planar Ising Models %@Nicol N. Schraudolph,Dmitry Kamenetsky %t2008 %cNIPS %f/NIPS/NIPS-2008-4439.pdf %*On Computational Power and the Order-Chaos Phase Transition in Reservoir Computing %@Benjamin Schrauwen,Lars Buesing,Robert A. Legenstein %t2008 %cNIPS %f/NIPS/NIPS-2008-4440.pdf %*An Empirical Analysis of Domain Adaptation Algorithms for Genomic Sequence Analysis %@Gabriele Schweikert,Gunnar Rätsch,Christian Widmer,Bernhard Schölkopf %t2008 %cNIPS %f/NIPS/NIPS-2008-4441.pdf %*Bayesian Experimental Design of Magnetic Resonance Imaging Sequences %@Hannes Nickisch,Rolf Pohmann,Bernhard Schölkopf,Matthias Seeger %t2008 %cNIPS %f/NIPS/NIPS-2008-4442.pdf %*Mind the Duality Gap: Logarithmic regret algorithms for online optimization %@Shai Shalev-shwartz,Sham M. Kakade %t2008 %cNIPS %f/NIPS/NIPS-2008-4443.pdf %*On the Reliability of Clustering Stability in the Large Sample Regime %@Ohad Shamir,Naftali Tishby %t2008 %cNIPS %f/NIPS/NIPS-2008-4444.pdf %*PSDBoost: Matrix-Generation Linear Programming for Positive Semidefinite Matrices Learning %@Chunhua Shen,Alan Welsh,Lei Wang %t2008 %cNIPS %f/NIPS/NIPS-2008-4445.pdf %*Relative Margin Machines %@Tony Jebara,Pannagadatta K. Shivaswamy %t2008 %cNIPS %f/NIPS/NIPS-2008-4446.pdf %*Kernel-ARMA for Hand Tracking and Brain-Machine interfacing During 3D Motor Control %@Lavi Shpigelman,Hagai Lalazar,Eilon Vaadia %t2008 %cNIPS %f/NIPS/NIPS-2008-4447.pdf %*Skill Characterization Based on Betweenness %@Özgür Şimşek,Andre S. Barreto %t2008 %cNIPS %f/NIPS/NIPS-2008-4448.pdf %*Regularized Co-Clustering with Dual Supervision %@Vikas Sindhwani,Jianying Hu,Aleksandra Mojsilovic %t2008 %cNIPS %f/NIPS/NIPS-2008-4449.pdf %*Unlabeled data: Now it helps, now it doesn't %@Aarti Singh,Robert Nowak,Xiaojin Zhu %t2008 %cNIPS %f/NIPS/NIPS-2008-4450.pdf %*The Conjoint Effect of Divisive Normalization and Orientation Selectivity on Redundancy Reduction %@Fabian H. Sinz,Matthias Bethge %t2008 %cNIPS %f/NIPS/NIPS-2008-4451.pdf %*Convergence and Rate of Convergence of a Manifold-Based Dimension Reduction Algorithm %@Andrew Smith,Hongyuan Zha,Xiao-ming Wu %t2008 %cNIPS %f/NIPS/NIPS-2008-4452.pdf %*Clusters and Coarse Partitions in LP Relaxations %@David Sontag,Amir Globerson,Tommi S. Jaakkola %t2008 %cNIPS %f/NIPS/NIPS-2008-4453.pdf %*Fast Rates for Regularized Objectives %@Karthik Sridharan,Shai Shalev-shwartz,Nathan Srebro %t2008 %cNIPS %f/NIPS/NIPS-2008-4454.pdf %*Grouping Contours Via a Related Image %@Praveen Srinivasan,Liming Wang,Jianbo Shi %t2008 %cNIPS %f/NIPS/NIPS-2008-4455.pdf %*Non-parametric Regression Between Manifolds %@Florian Steinke,Matthias Hein %t2008 %cNIPS %f/NIPS/NIPS-2008-4456.pdf %*Sparsity of SVMs that use the epsilon-insensitive loss %@Ingo Steinwart,Andreas Christmann %t2008 %cNIPS %f/NIPS/NIPS-2008-4457.pdf %*An Online Algorithm for Maximizing Submodular Functions %@Matthew Streeter,Daniel Golovin %t2008 %cNIPS %f/NIPS/NIPS-2008-4458.pdf %*Shared Segmentation of Natural Scenes Using Dependent Pitman-Yor Processes %@Erik B. Sudderth,Michael I. Jordan %t2008 %cNIPS %f/NIPS/NIPS-2008-4459.pdf %*Using matrices to model symbolic relationship %@Ilya Sutskever,Geoffrey E. Hinton %t2008 %cNIPS %f/NIPS/NIPS-2008-4460.pdf %*The Recurrent Temporal Restricted Boltzmann Machine %@Ilya Sutskever,Geoffrey E. Hinton,Graham W. Taylor %t2008 %cNIPS %f/NIPS/NIPS-2008-4461.pdf %*A Convergent O(n) Temporal-difference Algorithm for Off-policy Learning with Linear Function Approximation %@Richard S. Sutton,Hamid R. Maei,Csaba Szepesvári %t2008 %cNIPS %f/NIPS/NIPS-2008-4462.pdf %*Simple Local Models for Complex Dynamical Systems %@Erik Talvitie,Satinder P. Singh %t2008 %cNIPS %f/NIPS/NIPS-2008-4463.pdf %*Breaking Audio CAPTCHAs %@Jennifer Tam,Jiri Simsa,Sean Hyde,Luis V. Ahn %t2008 %cNIPS %f/NIPS/NIPS-2008-4464.pdf %*Correlated Bigram LSA for Unsupervised Language Model Adaptation %@Yik-cheung Tam,Tanja Schultz %t2008 %cNIPS %f/NIPS/NIPS-2008-4465.pdf %*Playing Pinball with non-invasive BCI %@Matthias Krauledat,Konrad Grzeska,Max Sagebaum,Benjamin Blankertz,Carmen Vidaurre,Klaus-Robert Müller,Michael Schröder %t2008 %cNIPS %f/NIPS/NIPS-2008-4466.pdf %*Bounding Performance Loss in Approximate MDP Homomorphisms %@Jonathan Taylor,Doina Precup,Prakash Panagaden %t2008 %cNIPS %f/NIPS/NIPS-2008-4467.pdf %*Hierarchical Semi-Markov Conditional Random Fields for Recursive Sequential Data %@Tran T. Truyen,Dinh Phung,Hung Bui,Svetha Venkatesh %t2008 %cNIPS %f/NIPS/NIPS-2008-4468.pdf %*Integrating Locally Learned Causal Structures with Overlapping Variables %@David Danks,Clark Glymour,Robert E. Tillman %t2008 %cNIPS %f/NIPS/NIPS-2008-4469.pdf %*Bayesian Kernel Shaping for Learning Control %@Jo-anne Ting,Mrinal Kalakrishnan,Sethu Vijayakumar,Stefan Schaal %t2008 %cNIPS %f/NIPS/NIPS-2008-4470.pdf %*Efficient Sampling for Gaussian Process Inference using Control Variables %@Neil D. Lawrence,Magnus Rattray,Michalis K. Titsias %t2008 %cNIPS %f/NIPS/NIPS-2008-4471.pdf %*Learning to Use Working Memory in Partially Observable Environments through Dopaminergic Reinforcement %@Michael T. Todd,Yael Niv,Jonathan D. Cohen %t2008 %cNIPS %f/NIPS/NIPS-2008-4472.pdf %*The Infinite Factorial Hidden Markov Model %@Jurgen V. Gael,Yee W. Teh,Zoubin Ghahramani %t2008 %cNIPS %f/NIPS/NIPS-2008-4473.pdf %*Multi-Level Active Prediction of Useful Image Annotations for Recognition %@Sudheendra Vijayanarasimhan,Kristen Grauman %t2008 %cNIPS %f/NIPS/NIPS-2008-4474.pdf %*Diffeomorphic Dimensionality Reduction %@Christian Walder,Bernhard Schölkopf %t2008 %cNIPS %f/NIPS/NIPS-2008-4475.pdf %*Learning a discriminative hidden part model for human action recognition %@Yang Wang,Greg Mori %t2008 %cNIPS %f/NIPS/NIPS-2008-4476.pdf %*Algorithms for Infinitely Many-Armed Bandits %@Yizao Wang,Jean-yves Audibert,Rémi Munos %t2008 %cNIPS %f/NIPS/NIPS-2008-4477.pdf %*Large Margin Taxonomy Embedding for Document Categorization %@Kilian Q. Weinberger,Olivier Chapelle %t2008 %cNIPS %f/NIPS/NIPS-2008-4478.pdf %*Beyond Novelty Detection: Incongruent Events, when General and Specific Classifiers Disagree %@Daphna Weinshall,Hynek Hermansky,Alon Zweig,Jie Luo,Holly Jimison,Frank Ohl,Misha Pavel %t2008 %cNIPS %f/NIPS/NIPS-2008-4479.pdf %*Spectral Hashing %@Yair Weiss,Antonio Torralba,Rob Fergus %t2008 %cNIPS %f/NIPS/NIPS-2008-4480.pdf %*MAS: a multiplicative approximation scheme for probabilistic inference %@Ydo Wexler,Christopher Meek %t2008 %cNIPS %f/NIPS/NIPS-2008-4481.pdf %*Dependence of Orientation Tuning on Recurrent Excitation and Inhibition in a Network Model of V1 %@Klaus Wimmer,Marcel Stimberg,Robert Martin,Lars Schwabe,Jorge Mariño,James Schummers,David C. Lyon,Mriganka Sur,Klaus Obermayer %t2008 %cNIPS %f/NIPS/NIPS-2008-4482.pdf %*Estimating the Location and Orientation of Complex, Correlated Neural Activity using MEG %@Julia Owen,Hagai T. Attias,Kensuke Sekihara,Srikantan S. Nagarajan,David P. Wipf %t2008 %cNIPS %f/NIPS/NIPS-2008-4483.pdf %*Localized Sliced Inverse Regression %@Qiang Wu,Sayan Mukherjee,Feng Liang %t2008 %cNIPS %f/NIPS/NIPS-2008-4484.pdf %*Model selection and velocity estimation using novel priors for motion patterns %@Shuang Wu,Hongjing Lu,Alan L. Yuille %t2008 %cNIPS %f/NIPS/NIPS-2008-4485.pdf %*Robust Regression and Lasso %@Huan Xu,Constantine Caramanis,Shie Mannor %t2008 %cNIPS %f/NIPS/NIPS-2008-4486.pdf %*How memory biases affect information transmission: A rational analysis of serial reproduction %@Jing Xu,Thomas L. Griffiths %t2008 %cNIPS %f/NIPS/NIPS-2008-4487.pdf %*Short-Term Depression in VLSI Stochastic Synapse %@Peng Xu,Timothy K. Horiuchi,Pamela A. Abshire %t2008 %cNIPS %f/NIPS/NIPS-2008-4488.pdf %*An Extended Level Method for Efficient Multiple Kernel Learning %@Zenglin Xu,Rong Jin,Irwin King,Michael Lyu %t2008 %cNIPS %f/NIPS/NIPS-2008-4489.pdf %*Bayesian Network Score Approximation using a Metagraph Kernel %@Benjamin Yackley,Eduardo Corona,Terran Lane %t2008 %cNIPS %f/NIPS/NIPS-2008-4490.pdf %*Learning with Consistency between Inductive Functions and Kernels %@Haixuan Yang,Irwin King,Michael Lyu %t2008 %cNIPS %f/NIPS/NIPS-2008-4491.pdf %*Semi-supervised Learning with Weakly-Related Unlabeled Data : Towards Better Text Categorization %@Liu Yang,Rong Jin,Rahul Sukthankar %t2008 %cNIPS %f/NIPS/NIPS-2008-4492.pdf %*Spike Feature Extraction Using Informative Samples %@Zhi Yang,Qi Zhao,Wentai Liu %t2008 %cNIPS %f/NIPS/NIPS-2008-4493.pdf %*Sequential effects: Superstition or rational behavior? %@Angela J. Yu,Jonathan D. Cohen %t2008 %cNIPS %f/NIPS/NIPS-2008-4494.pdf %*Gaussian-process factor analysis for low-dimensional single-trial analysis of neural population activity %@Byron M. Yu,John P. Cunningham,Gopal Santhanam,Stephen I. Ryu,Krishna V. Shenoy,Maneesh Sahani %t2008 %cNIPS %f/NIPS/NIPS-2008-4495.pdf %*Deep Learning with Kernel Regularization for Visual Recognition %@Kai Yu,Wei Xu,Yihong Gong %t2008 %cNIPS %f/NIPS/NIPS-2008-4496.pdf %*Variational Mixture of Gaussian Process Experts %@Chao Yuan,Claus Neubauer %t2008 %cNIPS %f/NIPS/NIPS-2008-4497.pdf %*Multi-Agent Filtering with Infinitely Nested Beliefs %@Luke Zettlemoyer,Brian Milch,Leslie P. Kaelbling %t2008 %cNIPS %f/NIPS/NIPS-2008-4498.pdf %*Fast Computation of Posterior Mode in Multi-Level Hierarchical Models %@Liang Zhang,Deepak Agarwal %t2008 %cNIPS %f/NIPS/NIPS-2008-4499.pdf %*Kernel Measures of Independence for non-iid Data %@Xinhua Zhang,Le Song,Arthur Gretton,Alex J. Smola %t2008 %cNIPS %f/NIPS/NIPS-2008-4500.pdf %*Learning the Semantic Correlation: An Alternative Way to Gain from Unlabeled Text %@Yi Zhang,Artur Dubrawski,Jeff G. Schneider %t2008 %cNIPS %f/NIPS/NIPS-2008-4501.pdf %*Cyclizing Clusters via Zeta Function of a Graph %@Deli Zhao,Xiaoou Tang %t2008 %cNIPS %f/NIPS/NIPS-2008-4502.pdf %*Hierarchical Fisher Kernels for Longitudinal Data %@Zhengdong Lu,Jeffrey Kaye,Todd K. Leen %t2008 %cNIPS %f/NIPS/NIPS-2008-4503.pdf %*Posterior Consistency of the Silverman g-prior in Bayesian Model Choice %@Zhihua Zhang,Michael I. Jordan,Dit-Yan Yeung %t2008 %cNIPS %f/NIPS/NIPS-2008-4504.pdf %*Partially Observed Maximum Entropy Discrimination Markov Networks %@Jun Zhu,Eric P. Xing,Bo Zhang %t2008 %cNIPS %f/NIPS/NIPS-2008-4505.pdf %*Recursive Segmentation and Recognition Templates for 2D Parsing %@Leo Zhu,Yuanhao Chen,Yuan Lin,Chenxi Lin,Alan L. Yuille %t2008 %cNIPS %f/NIPS/NIPS-2008-4506.pdf %*Stochastic Relational Models for Large-scale Dyadic Data using MCMC %@Shenghuo Zhu,Kai Yu,Yihong Gong %t2008 %cNIPS %f/NIPS/NIPS-2008-4507.pdf %*Inferring Elapsed Time from Stochastic Neural Processes %@Misha Ahrens,Maneesh Sahani %t2007 %cNIPS %f/NIPS/NIPS-2007-4508.pdf %*Fitted Q-iteration in continuous action-space MDPs %@András Antos,Csaba Szepesvári,Rémi Munos %t2007 %cNIPS %f/NIPS/NIPS-2007-4509.pdf %*Variational Inference for Diffusion Processes %@Cédric Archambeau,Manfred Opper,Yuan Shen,Dan Cornford,John S. Shawe-taylor %t2007 %cNIPS %f/NIPS/NIPS-2007-4510.pdf %*A Spectral Regularization Framework for Multi-Task Structure Learning %@Andreas Argyriou,Massimiliano Pontil,Yiming Ying,Charles A. Micchelli %t2007 %cNIPS %f/NIPS/NIPS-2007-4511.pdf %*Random Sampling of States in Dynamic Programming %@Chris Atkeson,Benjamin Stephens %t2007 %cNIPS %f/NIPS/NIPS-2007-4512.pdf %*DIFFRAC: a discriminative and flexible framework for clustering %@Francis R. Bach,Zaïd Harchaoui %t2007 %cNIPS %f/NIPS/NIPS-2007-4513.pdf %*Optimal ROC Curve for a Combination of Classifiers %@Marco Barreno,Alvaro Cardenas,J. D. Tygar %t2007 %cNIPS %f/NIPS/NIPS-2007-4514.pdf %*Adaptive Online Gradient Descent %@Elad Hazan,Alexander Rakhlin,Peter L. Bartlett %t2007 %cNIPS %f/NIPS/NIPS-2007-4515.pdf %*One-Pass Boosting %@Zafer Barutcuoglu,Phil Long,Rocco Servedio %t2007 %cNIPS %f/NIPS/NIPS-2007-4516.pdf %*Comparing Bayesian models for multisensory cue combination without mandatory integration %@Ulrik Beierholm,Ladan Shams,Wei J. Ma,Konrad Koerding %t2007 %cNIPS %f/NIPS/NIPS-2007-4517.pdf %*On Sparsity and Overcompleteness in Image Models %@Pietro Berkes,Richard Turner,Maneesh Sahani %t2007 %cNIPS %f/NIPS/NIPS-2007-4518.pdf %*Near-Maximum Entropy Models for Binary Neural Representations of Natural Images %@Matthias Bethge,Philipp Berens %t2007 %cNIPS %f/NIPS/NIPS-2007-4519.pdf %*Incremental Natural Actor-Critic Algorithms %@Shalabh Bhatnagar,Mohammad Ghavamzadeh,Mark Lee,Richard S. Sutton %t2007 %cNIPS %f/NIPS/NIPS-2007-4520.pdf %*Invariant Common Spatial Patterns: Alleviating Nonstationarities in Brain-Computer Interfacing %@Benjamin Blankertz,Motoaki Kawanabe,Ryota Tomioka,Friederike Hohlefeld,Klaus-Robert Müller,Vadim V. Nikulin %t2007 %cNIPS %f/NIPS/NIPS-2007-4521.pdf %*Supervised Topic Models %@Jon D. Mcauliffe,David M. Blei %t2007 %cNIPS %f/NIPS/NIPS-2007-4522.pdf %*Learning Bounds for Domain Adaptation %@John Blitzer,Koby Crammer,Alex Kulesza,Fernando Pereira,Jennifer Wortman %t2007 %cNIPS %f/NIPS/NIPS-2007-4523.pdf %*Feature Selection Methods for Improving Protein Structure Prediction with Rosetta %@Ben Blum,David Baker,Michael I. Jordan,Philip Bradley,Rhiju Das,David E. Kim %t2007 %cNIPS %f/NIPS/NIPS-2007-4524.pdf %*A neural network implementing optimal state estimation based on dynamic spike train decoding %@Omer Bobrowski,Ron Meir,Shy Shoham,Yonina Eldar %t2007 %cNIPS %f/NIPS/NIPS-2007-4525.pdf %*Multi-task Gaussian Process Prediction %@Edwin V. Bonilla,Kian M. Chai,Christopher Williams %t2007 %cNIPS %f/NIPS/NIPS-2007-4526.pdf %*The Tradeoffs of Large Scale Learning %@Olivier Bousquet,Léon Bottou %t2007 %cNIPS %f/NIPS/NIPS-2007-4527.pdf %*A Probabilistic Approach to Language Change %@Alexandre Bouchard-côté,Percy S. Liang,Dan Klein,Thomas L. Griffiths %t2007 %cNIPS %f/NIPS/NIPS-2007-4528.pdf %*Unsupervised Feature Selection for Accurate Recommendation of High-Dimensional Image Data %@Sabri Boutemedjet,Djemel Ziou,Nizar Bouguila %t2007 %cNIPS %f/NIPS/NIPS-2007-4529.pdf %*FilterBoost: Regression and Classification on Large Datasets %@Joseph K. Bradley,Robert E. Schapire %t2007 %cNIPS %f/NIPS/NIPS-2007-4530.pdf %*Simplified Rules and Theoretical Analysis for Information Bottleneck Optimization and PCA with Spiking Neurons %@Lars Buesing,Wolfgang Maass %t2007 %cNIPS %f/NIPS/NIPS-2007-4531.pdf %*The Distribution Family of Similarity Distances %@Gertjan Burghouts,Arnold Smeulders,Jan-mark Geusebroek %t2007 %cNIPS %f/NIPS/NIPS-2007-4532.pdf %*Discriminative Keyword Selection Using Support Vector Machines %@Fred Richardson,William M. Campbell %t2007 %cNIPS %f/NIPS/NIPS-2007-4533.pdf %*Evaluating Search Engines by Modeling the Relationship Between Relevance and Clicks %@Ben Carterette,Rosie Jones %t2007 %cNIPS %f/NIPS/NIPS-2007-4534.pdf %*Subspace-Based Face Recognition in Analog VLSI %@Gonzalo Carvajal,Waldo Valenzuela,Miguel Figueroa %t2007 %cNIPS %f/NIPS/NIPS-2007-4535.pdf %*A learning framework for nearest neighbor search %@Lawrence Cayton,Sanjoy Dasgupta %t2007 %cNIPS %f/NIPS/NIPS-2007-4536.pdf %*Predicting human gaze using low-level saliency combined with face detection %@Moran Cerf,Jonathan Harel,Wolfgang Einhaeuser,Christof Koch %t2007 %cNIPS %f/NIPS/NIPS-2007-4537.pdf %*Adaptive Embedded Subgraph Algorithms using Walk-Sum Analysis %@Venkat Chandrasekaran,Alan S. Willsky,Jason K. Johnson %t2007 %cNIPS %f/NIPS/NIPS-2007-4538.pdf %*Parallelizing Support Vector Machines on Distributed Computers %@Kaihua Zhu,Hao Wang,Hongjie Bai,Jian Li,Zhihuan Qiu,Hang Cui,Edward Y. Chang %t2007 %cNIPS %f/NIPS/NIPS-2007-4539.pdf %*Augmented Functional Time Series Representation and Forecasting with Gaussian Processes %@Nicolas Chapados,Yoshua Bengio %t2007 %cNIPS %f/NIPS/NIPS-2007-4540.pdf %*Efficient Principled Learning of Thin Junction Trees %@Anton Chechetka,Carlos Guestrin %t2007 %cNIPS %f/NIPS/NIPS-2007-4541.pdf %*Regularized Boost for Semi-Supervised Learning %@Ke Chen,Shihai Wang %t2007 %cNIPS %f/NIPS/NIPS-2007-4542.pdf %*Rapid Inference on a Novel AND/OR graph for Object Detection, Segmentation and Parsing %@Yuanhao Chen,Long Zhu,Chenxi Lin,Hongjiang Zhang,Alan L. Yuille %t2007 %cNIPS %f/NIPS/NIPS-2007-4543.pdf %*Cooled and Relaxed Survey Propagation for MRFs %@Hai L. Chieu,Wee S. Lee,Yee W. Teh %t2007 %cNIPS %f/NIPS/NIPS-2007-4544.pdf %*How SVMs can estimate quantiles and the median %@Andreas Christmann,Ingo Steinwart %t2007 %cNIPS %f/NIPS/NIPS-2007-4545.pdf %*Second Order Bilinear Discriminant Analysis for single trial EEG analysis %@Christoforos Christoforou,Paul Sajda,Lucas C. Parra %t2007 %cNIPS %f/NIPS/NIPS-2007-4546.pdf %*An online Hebbian learning rule that performs Independent Component Analysis %@Claudia Clopath,André Longtin,Wulfram Gerstner %t2007 %cNIPS %f/NIPS/NIPS-2007-4547.pdf %*Inferring Neural Firing Rates from Spike Trains Using Gaussian Processes %@John P. Cunningham,Byron M. Yu,Krishna V. Shenoy,Maneesh Sahani %t2007 %cNIPS %f/NIPS/NIPS-2007-4548.pdf %*TrueSkill Through Time: Revisiting the History of Chess %@Pierre Dangauthier,Ralf Herbrich,Tom Minka,Thore Graepel %t2007 %cNIPS %f/NIPS/NIPS-2007-4549.pdf %*The Price of Bandit Information for Online Optimization %@Varsha Dani,Sham M. Kakade,Thomas P. Hayes %t2007 %cNIPS %f/NIPS/NIPS-2007-4550.pdf %*A general agnostic active learning algorithm %@Sanjoy Dasgupta,Daniel J. Hsu,Claire Monteleoni %t2007 %cNIPS %f/NIPS/NIPS-2007-4551.pdf %*Measuring Neural Synchrony by Message Passing %@Justin Dauwels,François Vialatte,Tomasz Rutkowski,Andrzej S. Cichocki %t2007 %cNIPS %f/NIPS/NIPS-2007-4552.pdf %*The rat as particle filter %@Aaron C. Courville,Nathaniel D. Daw %t2007 %cNIPS %f/NIPS/NIPS-2007-4553.pdf %*Efficient multiple hyperparameter learning for log-linear models %@Chuan-sheng Foo,Chuong B. Do,Andrew Y. Ng %t2007 %cNIPS %f/NIPS/NIPS-2007-4554.pdf %*Automatic Generation of Social Tags for Music Recommendation %@Douglas Eck,Paul Lamere,Thierry Bertin-mahieux,Stephen Green %t2007 %cNIPS %f/NIPS/NIPS-2007-4555.pdf %*Bayesian binning beats approximate alternatives: estimating peri-stimulus time histograms %@Dominik Endres,Mike Oram,Johannes Schindelin,Peter Foldiak %t2007 %cNIPS %f/NIPS/NIPS-2007-4556.pdf %*A probabilistic model for generating realistic lip movements from speech %@Gwenn Englebienne,Tim Cootes,Magnus Rattray %t2007 %cNIPS %f/NIPS/NIPS-2007-4557.pdf %*Active Preference Learning with Discrete Choice Data %@Brochu Eric,Nando D. Freitas,Abhijeet Ghosh %t2007 %cNIPS %f/NIPS/NIPS-2007-4558.pdf %*Catching Up Faster in Bayesian Model Selection and Model Averaging %@Tim V. Erven,Steven D. Rooij,Peter Grünwald %t2007 %cNIPS %f/NIPS/NIPS-2007-4559.pdf %*Anytime Induction of Cost-sensitive Trees %@Saher Esmeir,Shaul Markovitch %t2007 %cNIPS %f/NIPS/NIPS-2007-4560.pdf %*Learning Visual Attributes %@Vittorio Ferrari,Andrew Zisserman %t2007 %cNIPS %f/NIPS/NIPS-2007-4561.pdf %*EEG-Based Brain-Computer Interaction: Improved Accuracy by Automatic Single-Trial Error Detection %@Pierre Ferrez,José Millán %t2007 %cNIPS %f/NIPS/NIPS-2007-4562.pdf %*A Bayesian Framework for Cross-Situational Word-Learning %@Noah Goodman,Joshua B. Tenenbaum,Michael J. Black %t2007 %cNIPS %f/NIPS/NIPS-2007-4563.pdf %*Sequential Hypothesis Testing under Stochastic Deadlines %@Peter Frazier,Angela J. Yu %t2007 %cNIPS %f/NIPS/NIPS-2007-4564.pdf %*Learning the structure of manifolds using random projections %@Yoav Freund,Sanjoy Dasgupta,Mayank Kabra,Nakul Verma %t2007 %cNIPS %f/NIPS/NIPS-2007-4565.pdf %*Discovering Weakly-Interacting Factors in a Complex Stochastic Process %@Charlie Frogner,Avi Pfeffer %t2007 %cNIPS %f/NIPS/NIPS-2007-4566.pdf %*Kernel Measures of Conditional Dependence %@Kenji Fukumizu,Arthur Gretton,Xiaohai Sun,Bernhard Schölkopf %t2007 %cNIPS %f/NIPS/NIPS-2007-4567.pdf %*The discriminant center-surround hypothesis for bottom-up saliency %@Dashan Gao,Vijay Mahadevan,Nuno Vasconcelos %t2007 %cNIPS %f/NIPS/NIPS-2007-4568.pdf %*Learning Horizontal Connections in a Sparse Coding Model of Natural Images %@Pierre Garrigues,Bruno A. Olshausen %t2007 %cNIPS %f/NIPS/NIPS-2007-4569.pdf %*Iterative Non-linear Dimensionality Reduction with Manifold Sculpting %@Michael Gashler,Dan Ventura,Tony Martinez %t2007 %cNIPS %f/NIPS/NIPS-2007-4570.pdf %*On higher-order perceptron algorithms %@Claudio Gentile,Fabio Vitale,Cristian Brotto %t2007 %cNIPS %f/NIPS/NIPS-2007-4571.pdf %*Bayesian Inference for Spiking Neuron Models with a Sparsity Prior %@Sebastian Gerwinn,Matthias Bethge,Jakob H. Macke,Matthias Seeger %t2007 %cNIPS %f/NIPS/NIPS-2007-4572.pdf %*Predicting Brain States from fMRI Data: Incremental Functional Principal Component Regression %@Sennay Ghebreab,Arnold Smeulders,Pieter Adriaans %t2007 %cNIPS %f/NIPS/NIPS-2007-4573.pdf %*A configurable analog VLSI neural network with spiking neurons and self-regulating plastic synapses %@Massimiliano Giulioni,Mario Pannunzi,Davide Badoni,Vittorio Dante,Paolo D. Giudice %t2007 %cNIPS %f/NIPS/NIPS-2007-4574.pdf %*Fixing Max-Product: Convergent Message Passing Algorithms for MAP LP-Relaxations %@Amir Globerson,Tommi S. Jaakkola %t2007 %cNIPS %f/NIPS/NIPS-2007-4575.pdf %*Competition Adds Complexity %@Judy Goldsmith,Martin Mundhenk %t2007 %cNIPS %f/NIPS/NIPS-2007-4576.pdf %*Expectation Maximization and Posterior Constraints %@Kuzman Ganchev,Ben Taskar,João Gama %t2007 %cNIPS %f/NIPS/NIPS-2007-4577.pdf %*Unconstrained On-line Handwriting Recognition with Recurrent Neural Networks %@Alex Graves,Marcus Liwicki,Horst Bunke,Juergen Schmidhuber,Santiago Fernández %t2007 %cNIPS %f/NIPS/NIPS-2007-4578.pdf %*A Kernel Statistical Test of Independence %@Arthur Gretton,Kenji Fukumizu,Choon H. Teo,Le Song,Bernhard Schölkopf,Alex J. Smola %t2007 %cNIPS %f/NIPS/NIPS-2007-4579.pdf %*Discriminative Batch Mode Active Learning %@Yuhong Guo,Dale Schuurmans %t2007 %cNIPS %f/NIPS/NIPS-2007-4580.pdf %*Convex Relaxations of Latent Variable Training %@Yuhong Guo,Dale Schuurmans %t2007 %cNIPS %f/NIPS/NIPS-2007-4581.pdf %*Testing for Homogeneity with Kernel Fisher Discriminant Analysis %@Moulines Eric,Francis R. Bach,Zaïd Harchaoui %t2007 %cNIPS %f/NIPS/NIPS-2007-4582.pdf %*Catching Change-points with Lasso %@Céline Levy-leduc,Zaïd Harchaoui %t2007 %cNIPS %f/NIPS/NIPS-2007-4583.pdf %*Computational Equivalence of Fixed Points and No Regret Algorithms, and Convergence to Equilibria %@Elad Hazan,Satyen Kale %t2007 %cNIPS %f/NIPS/NIPS-2007-4584.pdf %*Nearest-Neighbor-Based Active Learning for Rare Category Detection %@Jingrui He,Jaime G. Carbonell %t2007 %cNIPS %f/NIPS/NIPS-2007-4585.pdf %*Random Projections for Manifold Learning %@Chinmay Hegde,Michael Wakin,Richard Baraniuk %t2007 %cNIPS %f/NIPS/NIPS-2007-4586.pdf %*Regulator Discovery from Gene Expression Time Series of Malaria Parasites: a Hierachical Approach %@José M. Hernández-lobato,Tjeerd Dijkstra,Tom Heskes %t2007 %cNIPS %f/NIPS/NIPS-2007-4587.pdf %*Bayesian Policy Learning with Trans-Dimensional MCMC %@Matthew Hoffman,Arnaud Doucet,Nando D. Freitas,Ajay Jasra %t2007 %cNIPS %f/NIPS/NIPS-2007-4588.pdf %*Ultrafast Monte Carlo for Statistical Summations %@Charles L. Isbell,Michael P. Holmes,Alexander G. Gray %t2007 %cNIPS %f/NIPS/NIPS-2007-4589.pdf %*Learning Monotonic Transformations for Classification %@Andrew Howard,Tony Jebara %t2007 %cNIPS %f/NIPS/NIPS-2007-4590.pdf %*What makes some POMDP problems easy to approximate? %@Wee S. Lee,Nan Rong,David Hsu %t2007 %cNIPS %f/NIPS/NIPS-2007-4591.pdf %*Efficient Inference for Distributions on Permutations %@Jonathan Huang,Carlos Guestrin,Leonidas J. Guibas %t2007 %cNIPS %f/NIPS/NIPS-2007-4592.pdf %*Temporal Difference Updating without a Learning Rate %@Marcus Hutter,Shane Legg %t2007 %cNIPS %f/NIPS/NIPS-2007-4593.pdf %*Density Estimation under Independent Similarly Distributed Sampling Assumptions %@Tony Jebara,Yingbo Song,Kapil Thadani %t2007 %cNIPS %f/NIPS/NIPS-2007-4594.pdf %*Computing Robust Counter-Strategies %@Michael Johanson,Martin Zinkevich,Michael Bowling %t2007 %cNIPS %f/NIPS/NIPS-2007-4595.pdf %*Local Algorithms for Approximate Inference in Minor-Excluded Graphs %@Kyomin Jung,Devavrat Shah %t2007 %cNIPS %f/NIPS/NIPS-2007-4596.pdf %*Multi-Task Learning via Conic Programming %@Tsuyoshi Kato,Hisashi Kashima,Masashi Sugiyama,Kiyoshi Asai %t2007 %cNIPS %f/NIPS/NIPS-2007-4597.pdf %*Privacy-Preserving Belief Propagation and Sampling %@Michael Kearns,Jinsong Tan,Jennifer Wortman %t2007 %cNIPS %f/NIPS/NIPS-2007-4598.pdf %*Learning and using relational theories %@Charles Kemp,Noah Goodman,Joshua B. Tenenbaum %t2007 %cNIPS %f/NIPS/NIPS-2007-4599.pdf %*Hierarchical Apprenticeship Learning with Application to Quadruped Locomotion %@J. Z. Kolter,Pieter Abbeel,Andrew Y. Ng %t2007 %cNIPS %f/NIPS/NIPS-2007-4600.pdf %*Selecting Observations against Adversarial Objectives %@Andreas Krause,Brendan Mcmahan,Carlos Guestrin,Anupam Gupta %t2007 %cNIPS %f/NIPS/NIPS-2007-4601.pdf %*Structured Learning with Approximate Inference %@Alex Kulesza,Fernando Pereira %t2007 %cNIPS %f/NIPS/NIPS-2007-4602.pdf %*A Randomized Algorithm for Large Scale Support Vector Learning %@Krishnan Kumar,Chiru Bhattacharya,Ramesh Hariharan %t2007 %cNIPS %f/NIPS/NIPS-2007-4603.pdf %*Statistical Analysis of Semi-Supervised Regression %@Larry Wasserman,John D. Lafferty %t2007 %cNIPS %f/NIPS/NIPS-2007-4604.pdf %*Extending position/phase-shift tuning to motion energy neurons improves velocity discrimination %@Yiu M. Lam,Bertram E. Shi %t2007 %cNIPS %f/NIPS/NIPS-2007-4605.pdf %*The Epoch-Greedy Algorithm for Multi-armed Bandits with Side Information %@John Langford,Tong Zhang %t2007 %cNIPS %f/NIPS/NIPS-2007-4606.pdf %*Convex Clustering with Exemplar-Based Models %@Danial Lashkari,Polina Golland %t2007 %cNIPS %f/NIPS/NIPS-2007-4607.pdf %*Reinforcement Learning in Continuous Action Spaces through Sequential Monte Carlo Methods %@Alessandro Lazaric,Marcello Restelli,Andrea Bonarini %t2007 %cNIPS %f/NIPS/NIPS-2007-4608.pdf %*Learning the 2-D Topology of Images %@Nicolas L. Roux,Yoshua Bengio,Pascal Lamblin,Marc Joliveau,Balázs Kégl %t2007 %cNIPS %f/NIPS/NIPS-2007-4609.pdf %*Topmoumoute Online Natural Gradient Algorithm %@Nicolas L. Roux,Pierre-antoine Manzagol,Yoshua Bengio %t2007 %cNIPS %f/NIPS/NIPS-2007-4610.pdf %*Non-parametric Modeling of Partially Ranked Data %@Guy Lebanon,Yi Mao %t2007 %cNIPS %f/NIPS/NIPS-2007-4611.pdf %*Simulated Annealing: Rigorous finite-time guarantees for optimization on continuous domains %@Andrea Lecchini-visintini,John Lygeros,Jan Maciejowski %t2007 %cNIPS %f/NIPS/NIPS-2007-4612.pdf %*Sparse deep belief net model for visual area V2 %@Honglak Lee,Chaitanya Ekanadham,Andrew Y. Ng %t2007 %cNIPS %f/NIPS/NIPS-2007-4613.pdf %*Theoretical Analysis of Learning with Reward-Modulated Spike-Timing-Dependent Plasticity %@Dejan Pecevski,Wolfgang Maass,Robert A. Legenstein %t2007 %cNIPS %f/NIPS/NIPS-2007-4614.pdf %*Hippocampal Contributions to Control: The Third Way %@Máté Lengyel,Peter Dayan %t2007 %cNIPS %f/NIPS/NIPS-2007-4615.pdf %*McRank: Learning to Rank Using Multiple Classification and Gradient Boosting %@Ping Li,Qiang Wu,Christopher J. Burges %t2007 %cNIPS %f/NIPS/NIPS-2007-4616.pdf %*A Unified Near-Optimal Estimator For Dimension Reduction in l_\alpha (0<\alpha\leq 2) Using Stable Random Projections %@Ping Li,Trevor J. Hastie %t2007 %cNIPS %f/NIPS/NIPS-2007-4617.pdf %*Agreement-Based Learning %@Percy S. Liang,Dan Klein,Michael I. Jordan %t2007 %cNIPS %f/NIPS/NIPS-2007-4618.pdf %*Blind channel identification for speech dereverberation using l1-norm sparse learning %@Yuanqing Lin,Jingdong Chen,Youngmoo Kim,Daniel D. Lee %t2007 %cNIPS %f/NIPS/NIPS-2007-4619.pdf %*Mining Internet-Scale Software Repositories %@Erik Linstead,Paul Rigor,Sushil Bajracharya,Cristina Lopes,Pierre F. Baldi %t2007 %cNIPS %f/NIPS/NIPS-2007-4620.pdf %*Semi-Supervised Multitask Learning %@Qiuhua Liu,Xuejun Liao,Lawrence Carin %t2007 %cNIPS %f/NIPS/NIPS-2007-4621.pdf %*Boosting the Area under the ROC Curve %@Phil Long,Rocco Servedio %t2007 %cNIPS %f/NIPS/NIPS-2007-4622.pdf %*Support Vector Machine Classification with Indefinite Kernels %@Ronny Luss,Alexandre D'aspremont %t2007 %cNIPS %f/NIPS/NIPS-2007-4623.pdf %*Consistent Minimization of Clustering Objective Functions %@Ulrike V. Luxburg,Stefanie Jegelka,Michael Kaufmann,Sébastien Bubeck %t2007 %cNIPS %f/NIPS/NIPS-2007-4624.pdf %*Receptive Fields without Spike-Triggering %@Guenther Zeck,Matthias Bethge,Jakob H. Macke %t2007 %cNIPS %f/NIPS/NIPS-2007-4625.pdf %*Fast and Scalable Training of Semi-Supervised CRFs with Application to Activity Recognition %@Maryam Mahdaviani,Tanzeem Choudhury %t2007 %cNIPS %f/NIPS/NIPS-2007-4626.pdf %*Transfer Learning using Kolmogorov Complexity: Basic Theory and Empirical Evaluations %@M. M. Mahmud,Sylvian Ray %t2007 %cNIPS %f/NIPS/NIPS-2007-4627.pdf %*Scan Strategies for Meteorological Radars %@Victoria Manfredi,Jim Kurose %t2007 %cNIPS %f/NIPS/NIPS-2007-4628.pdf %*Locality and low-dimensions in the prediction of natural experience from fMRI %@Francois Meyer,Greg Stephens %t2007 %cNIPS %f/NIPS/NIPS-2007-4629.pdf %*Learning to classify complex patterns using a VLSI network of spiking neurons %@Srinjoy Mitra,Giacomo Indiveri,Stefano Fusi %t2007 %cNIPS %f/NIPS/NIPS-2007-4630.pdf %*The Infinite Markov Model %@Daichi Mochihashi,Eiichiro Sumita %t2007 %cNIPS %f/NIPS/NIPS-2007-4631.pdf %*Stability Bounds for Non-i.i.d. Processes %@Mehryar Mohri,Afshin Rostamizadeh %t2007 %cNIPS %f/NIPS/NIPS-2007-4632.pdf %*Experience-Guided Search: A Theory of Attentional Control %@David Baldwin,Michael C. Mozer %t2007 %cNIPS %f/NIPS/NIPS-2007-4633.pdf %*An Analysis of Convex Relaxations for MAP Estimation %@Pawan Mudigonda,Vladimir Kolmogorov,Philip Torr %t2007 %cNIPS %f/NIPS/NIPS-2007-4634.pdf %*Continuous Time Particle Filtering for fMRI %@Lawrence Murray,Amos J. Storkey %t2007 %cNIPS %f/NIPS/NIPS-2007-4635.pdf %*The Generalized FITC Approximation %@Andrew Naish-guzman,Sean Holden %t2007 %cNIPS %f/NIPS/NIPS-2007-4636.pdf %*Robust Regression with Twinned Gaussian Processes %@Andrew Naish-guzman,Sean Holden %t2007 %cNIPS %f/NIPS/NIPS-2007-4637.pdf %*Contraction Properties of VLSI Cooperative Competitive Neural Networks of Spiking Neurons %@Emre Neftci,Elisabetta Chicca,Giacomo Indiveri,Jean-jeacques Slotine,Rodney J. Douglas %t2007 %cNIPS %f/NIPS/NIPS-2007-4638.pdf %*Distributed Inference for Latent Dirichlet Allocation %@David Newman,Padhraic Smyth,Max Welling,Arthur U. Asuncion %t2007 %cNIPS %f/NIPS/NIPS-2007-4639.pdf %*Estimating divergence functionals and the likelihood ratio by penalized convex risk minimization %@Long Nguyen,Martin J. Wainwright,Michael I. Jordan %t2007 %cNIPS %f/NIPS/NIPS-2007-4640.pdf %*Heterogeneous Component Analysis %@Shigeyuki Oba,Motoaki Kawanabe,Klaus-Robert Müller,Shin Ishii %t2007 %cNIPS %f/NIPS/NIPS-2007-4641.pdf %*Variational inference for Markov jump processes %@Manfred Opper,Guido Sanguinetti %t2007 %cNIPS %f/NIPS/NIPS-2007-4642.pdf %*Modeling image patches with a directed hierarchy of Markov random fields %@Simon Osindero,Geoffrey E. Hinton %t2007 %cNIPS %f/NIPS/NIPS-2007-4643.pdf %*Kernels on Attributed Pointsets with Applications %@Mehul Parsana,Sourangshu Bhattacharya,Chiru Bhattacharya,K. Ramakrishnan %t2007 %cNIPS %f/NIPS/NIPS-2007-4644.pdf %*A Risk Minimization Principle for a Class of Parzen Estimators %@Kristiaan Pelckmans,Johan Suykens,Bart D. Moor %t2007 %cNIPS %f/NIPS/NIPS-2007-4645.pdf %*Congruence between model and human attention reveals unique signatures of critical visual events %@Robert Peters,Laurent Itti %t2007 %cNIPS %f/NIPS/NIPS-2007-4646.pdf %*Discriminative Log-Linear Grammars with Latent Variables %@Slav Petrov,Dan Klein %t2007 %cNIPS %f/NIPS/NIPS-2007-4647.pdf %*Neural characterization in partially observed populations of spiking neurons %@Jonathan W. Pillow,Peter E. Latham %t2007 %cNIPS %f/NIPS/NIPS-2007-4648.pdf %*Fast Variational Inference for Large-scale Internet Diagnosis %@Emre Kiciman,David Maltz,John C. Platt %t2007 %cNIPS %f/NIPS/NIPS-2007-4649.pdf %*Random Features for Large-Scale Kernel Machines %@Ali Rahimi,Benjamin Recht %t2007 %cNIPS %f/NIPS/NIPS-2007-4650.pdf %*Sparse Feature Learning for Deep Belief Networks %@Marc'aurelio Ranzato,Y-lan Boureau,Yann L. Cun %t2007 %cNIPS %f/NIPS/NIPS-2007-4651.pdf %*Retrieved context and the discovery of semantic structure %@Vinayak Rao,Marc Howard %t2007 %cNIPS %f/NIPS/NIPS-2007-4652.pdf %*SpAM: Sparse Additive Models %@Han Liu,Larry Wasserman,John D. Lafferty,Pradeep K. Ravikumar %t2007 %cNIPS %f/NIPS/NIPS-2007-4653.pdf %*On Ranking in Survival Analysis: Bounds on the Concordance Index %@Harald Steck,Balaji Krishnapuram,Cary Dehing-oberije,Philippe Lambin,Vikas C. Raykar %t2007 %cNIPS %f/NIPS/NIPS-2007-4654.pdf %*GRIFT: A graphical model for inferring visual classification features from human data %@Michael Ross,Andrew Cohen %t2007 %cNIPS %f/NIPS/NIPS-2007-4655.pdf %*Bayes-Adaptive POMDPs %@Stephane Ross,Brahim Chaib-draa,Joelle Pineau %t2007 %cNIPS %f/NIPS/NIPS-2007-4656.pdf %*Theoretical Analysis of Heuristic Search Methods for Online POMDPs %@Stephane Ross,Joelle Pineau,Brahim Chaib-draa %t2007 %cNIPS %f/NIPS/NIPS-2007-4657.pdf %*Object Recognition by Scene Alignment %@Bryan Russell,Antonio Torralba,Ce Liu,Rob Fergus,William T. Freeman %t2007 %cNIPS %f/NIPS/NIPS-2007-4658.pdf %*Using Deep Belief Nets to Learn Covariance Kernels for Gaussian Processes %@Geoffrey E. Hinton,Ruslan R. Salakhutdinov %t2007 %cNIPS %f/NIPS/NIPS-2007-4659.pdf %*Probabilistic Matrix Factorization %@Andriy Mnih,Ruslan R. Salakhutdinov %t2007 %cNIPS %f/NIPS/NIPS-2007-4660.pdf %*Markov Chain Monte Carlo with People %@Adam Sanborn,Thomas L. Griffiths %t2007 %cNIPS %f/NIPS/NIPS-2007-4661.pdf %*Linear programming analysis of loopy belief propagation for weighted matching %@Sujay Sanghavi,Dmitry Malioutov,Alan S. Willsky %t2007 %cNIPS %f/NIPS/NIPS-2007-4662.pdf %*Message Passing for Max-weight Independent Set %@Sujay Sanghavi,Devavrat Shah,Alan S. Willsky %t2007 %cNIPS %f/NIPS/NIPS-2007-4663.pdf %*Multiple-Instance Active Learning %@Burr Settles,Mark Craven,Soumya Ray %t2007 %cNIPS %f/NIPS/NIPS-2007-4664.pdf %*Cluster Stability for Finite Samples %@Ohad Shamir,Naftali Tishby %t2007 %cNIPS %f/NIPS/NIPS-2007-4665.pdf %*Sparse Overcomplete Latent Variable Decomposition of Counts Data %@Madhusudana Shashanka,Bhiksha Raj,Paris Smaragdis %t2007 %cNIPS %f/NIPS/NIPS-2007-4666.pdf %*Collective Inference on Markov Models for Modeling Bird Migration %@M.a. S. Elmohamed,Dexter Kozen,Daniel R. Sheldon %t2007 %cNIPS %f/NIPS/NIPS-2007-4667.pdf %*A Constraint Generation Approach to Learning Stable Linear Dynamical Systems %@Byron Boots,Geoffrey J. Gordon,Sajid M. Siddiqi %t2007 %cNIPS %f/NIPS/NIPS-2007-4668.pdf %*Combined discriminative and generative articulated pose and non-rigid shape estimation %@Leonid Sigal,Alexandru Balan,Michael J. Black %t2007 %cNIPS %f/NIPS/NIPS-2007-4669.pdf %*Hidden Common Cause Relations in Relational Learning %@Ricardo Silva,Wei Chu,Zoubin Ghahramani %t2007 %cNIPS %f/NIPS/NIPS-2007-4670.pdf %*Ensemble Clustering using Semidefinite Programming %@Vikas Singh,Lopamudra Mukherjee,Jiming Peng,Jinhui Xu %t2007 %cNIPS %f/NIPS/NIPS-2007-4671.pdf %*The Value of Labeled and Unlabeled Examples when the Model is Imperfect %@Kaushik Sinha,Mikhail Belkin %t2007 %cNIPS %f/NIPS/NIPS-2007-4672.pdf %*An Analysis of Inference with the Universum %@Olivier Chapelle,Alekh Agarwal,Fabian H. Sinz,Bernhard Schölkopf %t2007 %cNIPS %f/NIPS/NIPS-2007-4673.pdf %*Bundle Methods for Machine Learning %@Quoc V. Le,Alex J. Smola,S.v.n. Vishwanathan %t2007 %cNIPS %f/NIPS/NIPS-2007-4674.pdf %*Colored Maximum Variance Unfolding %@Le Song,Arthur Gretton,Karsten M. Borgwardt,Alex J. Smola %t2007 %cNIPS %f/NIPS/NIPS-2007-4675.pdf %*New Outer Bounds on the Marginal Polytope %@David Sontag,Tommi S. Jaakkola %t2007 %cNIPS %f/NIPS/NIPS-2007-4676.pdf %*An in-silico Neural Model of Dynamic Routing through Neuronal Coherence %@Devarajan Sridharan,Brian Percival,John Arthur,Kwabena A. Boahen %t2007 %cNIPS %f/NIPS/NIPS-2007-4677.pdf %*A Bayesian Model of Conditioned Perception %@Alan Stocker,Eero P. Simoncelli %t2007 %cNIPS %f/NIPS/NIPS-2007-4678.pdf %*Online Linear Regression and Its Application to Model-Based Reinforcement Learning %@Alexander L. Strehl,Michael L. Littman %t2007 %cNIPS %f/NIPS/NIPS-2007-4679.pdf %*Loop Series and Bethe Variational Bounds in Attractive Graphical Models %@Alan S. Willsky,Erik B. Sudderth,Martin J. Wainwright %t2007 %cNIPS %f/NIPS/NIPS-2007-4680.pdf %*Direct Importance Estimation with Model Selection and Its Application to Covariate Shift Adaptation %@Masashi Sugiyama,Shinichi Nakajima,Hisashi Kashima,Paul V. Buenau,Motoaki Kawanabe %t2007 %cNIPS %f/NIPS/NIPS-2007-4681.pdf %*Efficient Bayesian Inference for Dynamically Changing Graphs %@Ozgur Sumer,Umut Acar,Alexander T. Ihler,Ramgopal R. Mettu %t2007 %cNIPS %f/NIPS/NIPS-2007-4682.pdf %*A Game-Theoretic Approach to Apprenticeship Learning %@Umar Syed,Robert E. Schapire %t2007 %cNIPS %f/NIPS/NIPS-2007-4683.pdf %*Hierarchical Penalization %@Marie Szafranski,Yves Grandvalet,Pierre Morizet-mahoudeaux %t2007 %cNIPS %f/NIPS/NIPS-2007-4684.pdf %*Receding Horizon Differential Dynamic Programming %@Yuval Tassa,Tom Erez,William D. Smart %t2007 %cNIPS %f/NIPS/NIPS-2007-4685.pdf %*Bayesian Agglomerative Clustering with Coalescents %@Yee W. Teh,Hal Daume III,Daniel M. Roy %t2007 %cNIPS %f/NIPS/NIPS-2007-4686.pdf %*Collapsed Variational Inference for HDP %@Yee W. Teh,Kenichi Kurihara,Max Welling %t2007 %cNIPS %f/NIPS/NIPS-2007-4687.pdf %*Convex Learning with Invariances %@Choon H. Teo,Amir Globerson,Sam T. Roweis,Alex J. Smola %t2007 %cNIPS %f/NIPS/NIPS-2007-4688.pdf %*Managing Power Consumption and Performance of Computing Systems Using Reinforcement Learning %@Gerald Tesauro,Rajarshi Das,Hoi Chan,Jeffrey Kephart,David Levine,Freeman Rawson,Charles Lefurgy %t2007 %cNIPS %f/NIPS/NIPS-2007-4689.pdf %*Optimistic Linear Programming gives Logarithmic Regret for Irreducible MDPs %@Ambuj Tewari,Peter L. Bartlett %t2007 %cNIPS %f/NIPS/NIPS-2007-4690.pdf %*A Bayesian LDA-based model for semi-supervised part-of-speech tagging %@Kristina Toutanova,Mark Johnson %t2007 %cNIPS %f/NIPS/NIPS-2007-4691.pdf %*Configuration Estimates Improve Pedestrian Finding %@Duan Tran,David A. Forsyth %t2007 %cNIPS %f/NIPS/NIPS-2007-4692.pdf %*Estimating disparity with confidence from energy neurons %@Eric K. Tsang,Bertram E. Shi %t2007 %cNIPS %f/NIPS/NIPS-2007-4693.pdf %*Modeling Natural Sounds with Modulation Cascade Processes %@Richard Turner,Maneesh Sahani %t2007 %cNIPS %f/NIPS/NIPS-2007-4694.pdf %*Scene Segmentation with CRFs Learned from Partially Labeled Images %@Bill Triggs,Jakob J. Verbeek %t2007 %cNIPS %f/NIPS/NIPS-2007-4695.pdf %*Learning with Transformation Invariant Kernels %@Christian Walder,Olivier Chapelle %t2007 %cNIPS %f/NIPS/NIPS-2007-4696.pdf %*Stable Dual Dynamic Programming %@Tao Wang,Michael Bowling,Dale Schuurmans,Daniel J. Lizotte %t2007 %cNIPS %f/NIPS/NIPS-2007-4697.pdf %*Spatial Latent Dirichlet Allocation %@Xiaogang Wang,Eric Grimson %t2007 %cNIPS %f/NIPS/NIPS-2007-4698.pdf %*Boosting Algorithms for Maximizing the Soft Margin %@Gunnar Rätsch,Manfred K. Warmuth,Karen A. Glocer %t2007 %cNIPS %f/NIPS/NIPS-2007-4699.pdf %*COFI RANK - Maximum Margin Matrix Factorization for Collaborative Ranking %@Markus Weimer,Alexandros Karatzoglou,Quoc V. Le,Alex J. Smola %t2007 %cNIPS %f/NIPS/NIPS-2007-4700.pdf %*Infinite State Bayes-Nets for Structured Domains %@Max Welling,Ian Porteous,Evgeniy Bart %t2007 %cNIPS %f/NIPS/NIPS-2007-4701.pdf %*Modelling motion primitives and their timing in biologically executed movements %@Ben Williams,Marc Toussaint,Amos J. Storkey %t2007 %cNIPS %f/NIPS/NIPS-2007-4702.pdf %*Exponential Family Predictive Representations of State %@David Wingate,Satinder S. Baveja %t2007 %cNIPS %f/NIPS/NIPS-2007-4703.pdf %*A New View of Automatic Relevance Determination %@David P. Wipf,Srikantan S. Nagarajan %t2007 %cNIPS %f/NIPS/NIPS-2007-4704.pdf %*Classification via Minimum Incremental Coding Length (MICL) %@John Wright,Yangyu Tao,Zhouchen Lin,Yi Ma,Heung-yeung Shum %t2007 %cNIPS %f/NIPS/NIPS-2007-4705.pdf %*Efficient Convex Relaxation for Transductive Support Vector Machine %@Zenglin Xu,Rong Jin,Jianke Zhu,Irwin King,Michael Lyu %t2007 %cNIPS %f/NIPS/NIPS-2007-4706.pdf %*Discriminative K-means for Clustering %@Jieping Ye,Zheng Zhao,Mingrui Wu %t2007 %cNIPS %f/NIPS/NIPS-2007-4707.pdf %*Gaussian Process Models for Link Analysis and Transfer Learning %@Kai Yu,Wei Chu %t2007 %cNIPS %f/NIPS/NIPS-2007-4708.pdf %*Bayesian Co-Training %@Shipeng Yu,Balaji Krishnapuram,Harald Steck,R. B. Rao,Rómer Rosales %t2007 %cNIPS %f/NIPS/NIPS-2007-4709.pdf %*The Noisy-Logical Distribution and its Application to Causal Inference %@Hongjing Lu,Alan L. Yuille %t2007 %cNIPS %f/NIPS/NIPS-2007-4710.pdf %*Multiple-Instance Pruning For Learning Efficient Cascade Detectors %@Cha Zhang,Paul A. Viola %t2007 %cNIPS %f/NIPS/NIPS-2007-4711.pdf %*HM-BiTAM: Bilingual Topic Exploration, Word Alignment, and Translation %@Bing Zhao,Eric P. Xing %t2007 %cNIPS %f/NIPS/NIPS-2007-4712.pdf %*A General Boosting Method and its Application to Learning Ranking Functions for Web Search %@Zhaohui Zheng,Hongyuan Zha,Tong Zhang,Olivier Chapelle,Keke Chen,Gordon Sun %t2007 %cNIPS %f/NIPS/NIPS-2007-4713.pdf %*People Tracking with the Laplacian Eigenmaps Latent Variable Model %@Zhengdong Lu,Cristian Sminchisescu,Miguel Á. Carreira-Perpiñán %t2007 %cNIPS %f/NIPS/NIPS-2007-4714.pdf %*Compressed Regression %@Shuheng Zhou,Larry Wasserman,John D. Lafferty %t2007 %cNIPS %f/NIPS/NIPS-2007-4715.pdf %*Predictive Matrix-Variate t Models %@Shenghuo Zhu,Kai Yu,Yihong Gong %t2007 %cNIPS %f/NIPS/NIPS-2007-4716.pdf %*Regret Minimization in Games with Incomplete Information %@Martin Zinkevich,Michael Johanson,Michael Bowling,Carmelo Piccione %t2007 %cNIPS %f/NIPS/NIPS-2007-4717.pdf %*An Application of Reinforcement Learning to Aerobatic Helicopter Flight %@Pieter Abbeel,Adam Coates,Morgan Quigley,Andrew Y. Ng %t2006 %cNIPS %f/NIPS/NIPS-2006-4718.pdf %*Tighter PAC-Bayes Bounds %@Amiran Ambroladze,Emilio Parrado-hernández,John S. Shawe-taylor %t2006 %cNIPS %f/NIPS/NIPS-2006-4719.pdf %*Online Classification for Complex Problems Using Simultaneous Projections %@Yonatan Amit,Shai Shalev-shwartz,Yoram Singer %t2006 %cNIPS %f/NIPS/NIPS-2006-4720.pdf %*Learning on Graph with Laplacian Regularization %@Rie K. Ando,Tong Zhang %t2006 %cNIPS %f/NIPS/NIPS-2006-4721.pdf %*Sparse Kernel Orthonormalized PLS for feature extraction in large data sets %@Jerónimo Arenas-garcía,Kaare B. Petersen,Lars K. Hansen %t2006 %cNIPS %f/NIPS/NIPS-2006-4722.pdf %*Multi-Task Feature Learning %@Andreas Argyriou,Theodoros Evgeniou,Massimiliano Pontil %t2006 %cNIPS %f/NIPS/NIPS-2006-4723.pdf %*Logarithmic Online Regret Bounds for Undiscounted Reinforcement Learning %@Peter Auer,Ronald Ortner %t2006 %cNIPS %f/NIPS/NIPS-2006-4724.pdf %*Efficient Methods for Privacy Preserving Face Detection %@Shai Avidan,Moshe Butman %t2006 %cNIPS %f/NIPS/NIPS-2006-4725.pdf %*Subordinate class recognition using relational object models %@Aharon B. Hillel,Daphna Weinshall %t2006 %cNIPS %f/NIPS/NIPS-2006-4726.pdf %*Unified Inference for Variational Bayesian Linear Gaussian State-Space Models %@David Barber,Silvia Chiappa %t2006 %cNIPS %f/NIPS/NIPS-2006-4727.pdf %*A Novel Gaussian Sum Smoother for Approximate Inference in Switching Linear Dynamical Systems %@David Barber,Bertrand Mesot %t2006 %cNIPS %f/NIPS/NIPS-2006-4728.pdf %*Sample Complexity of Policy Search with Known Dynamics %@Peter L. Bartlett,Ambuj Tewari %t2006 %cNIPS %f/NIPS/NIPS-2006-4729.pdf %*AdaBoost is Consistent %@Peter L. Bartlett,Mikhail Traskin %t2006 %cNIPS %f/NIPS/NIPS-2006-4730.pdf %*A selective attention multi--chip system with dynamic synapses and spiking neurons %@Chiara Bartolozzi,Giacomo Indiveri %t2006 %cNIPS %f/NIPS/NIPS-2006-4731.pdf %*Temporal and Cross-Subject Probabilistic Models for fMRI Prediction Tasks %@Alexis Battle,Gal Chechik,Daphne Koller %t2006 %cNIPS %f/NIPS/NIPS-2006-4732.pdf %*Convergence of Laplacian Eigenmaps %@Mikhail Belkin,Partha Niyogi %t2006 %cNIPS %f/NIPS/NIPS-2006-4733.pdf %*Analysis of Representations for Domain Adaptation %@Shai Ben-David,John Blitzer,Koby Crammer,Fernando Pereira %t2006 %cNIPS %f/NIPS/NIPS-2006-4734.pdf %*An Approach to Bounded Rationality %@Eli Ben-sasson,Ehud Kalai,Adam Kalai %t2006 %cNIPS %f/NIPS/NIPS-2006-4735.pdf %*Greedy Layer-Wise Training of Deep Networks %@Yoshua Bengio,Pascal Lamblin,Dan Popovici,Hugo Larochelle %t2006 %cNIPS %f/NIPS/NIPS-2006-4736.pdf %*Dirichlet-Enhanced Spam Filtering based on Biased Samples %@Steffen Bickel,Tobias Scheffer %t2006 %cNIPS %f/NIPS/NIPS-2006-4737.pdf %*Detecting Humans via Their Pose %@Alessandro Bissacco,Ming-Hsuan Yang,Stefano Soatto %t2006 %cNIPS %f/NIPS/NIPS-2006-4738.pdf %*Similarity by Composition %@Oren Boiman,Michal Irani %t2006 %cNIPS %f/NIPS/NIPS-2006-4739.pdf %*Denoising and Dimension Reduction in Feature Space %@Mikio L. Braun,Klaus-Robert Müller,Joachim M. Buhmann %t2006 %cNIPS %f/NIPS/NIPS-2006-4740.pdf %*Learning to Rank with Nonsmooth Cost Functions %@Christopher J. Burges,Robert Ragno,Quoc V. Le %t2006 %cNIPS %f/NIPS/NIPS-2006-4741.pdf %*Conditional mean field %@Peter Carbonetto,Nando D. Freitas %t2006 %cNIPS %f/NIPS/NIPS-2006-4742.pdf %*Sparse Multinomial Logistic Regression via Bayesian L1 Regularisation %@Gavin C. Cawley,Nicola L. Talbot,Mark Girolami %t2006 %cNIPS %f/NIPS/NIPS-2006-4743.pdf %*Branch and Bound for Semi-Supervised Support Vector Machines %@Olivier Chapelle,Vikas Sindhwani,S. S. Keerthi %t2006 %cNIPS %f/NIPS/NIPS-2006-4744.pdf %*Automated Hierarchy Discovery for Planning in Partially Observable Environments %@Laurent Charlin,Pascal Poupart,Romy Shioda %t2006 %cNIPS %f/NIPS/NIPS-2006-4745.pdf %*Max-margin classification of incomplete data %@Gal Chechik,Geremy Heitz,Gal Elidan,Pieter Abbeel,Daphne Koller %t2006 %cNIPS %f/NIPS/NIPS-2006-4746.pdf %*Modeling General and Specific Aspects of Documents with a Probabilistic Topic Model %@Chaitanya Chemudugunta,Padhraic Smyth,Mark Steyvers %t2006 %cNIPS %f/NIPS/NIPS-2006-4747.pdf %*implicit Online Learning with Kernels %@Li Cheng,Dale Schuurmans,Shaojun Wang,Terry Caelli,S.v.n. Vishwanathan %t2006 %cNIPS %f/NIPS/NIPS-2006-4748.pdf %*Context dependent amplification of both rate and event-correlation in a VLSI network of spiking neurons %@Elisabetta Chicca,Giacomo Indiveri,Rodney J. Douglas %t2006 %cNIPS %f/NIPS/NIPS-2006-4749.pdf %*Bayesian Ensemble Learning %@Hugh A. Chipman,Edward I. George,Robert E. Mcculloch %t2006 %cNIPS %f/NIPS/NIPS-2006-4750.pdf %*Implicit Surfaces with Globally Regularised and Compactly Supported Basis Functions %@Christian Walder,Olivier Chapelle,Bernhard Schölkopf %t2006 %cNIPS %f/NIPS/NIPS-2006-4751.pdf %*Map-Reduce for Machine Learning on Multicore %@Cheng-tao Chu,Sang K. Kim,Yi-an Lin,Yuanyuan Yu,Gary Bradski,Kunle Olukotun,Andrew Y. Ng %t2006 %cNIPS %f/NIPS/NIPS-2006-4752.pdf %*Relational Learning with Gaussian Processes %@Wei Chu,Vikas Sindhwani,Zoubin Ghahramani,S. S. Keerthi %t2006 %cNIPS %f/NIPS/NIPS-2006-4753.pdf %*Recursive Attribute Factoring %@David Cohn,Deepak Verma,Karl Pfleger %t2006 %cNIPS %f/NIPS/NIPS-2006-4754.pdf %*On Transductive Regression %@Corinna Cortes,Mehryar Mohri %t2006 %cNIPS %f/NIPS/NIPS-2006-4755.pdf %*Balanced Graph Matching %@Timothee Cour,Praveen Srinivasan,Jianbo Shi %t2006 %cNIPS %f/NIPS/NIPS-2006-4756.pdf %*Learning from Multiple Sources %@Koby Crammer,Michael Kearns,Jennifer Wortman %t2006 %cNIPS %f/NIPS/NIPS-2006-4757.pdf %*Kernels on Structured Objects Through Nested Histograms %@Marco Cuturi,Kenji Fukumizu %t2006 %cNIPS %f/NIPS/NIPS-2006-4758.pdf %*Differential Entropic Clustering of Multivariate Gaussians %@Jason V. Davis,Inderjit S. Dhillon %t2006 %cNIPS %f/NIPS/NIPS-2006-4759.pdf %*Support Vector Machines on a Budget %@Ofer Dekel,Yoram Singer %t2006 %cNIPS %f/NIPS/NIPS-2006-4760.pdf %*A Theory of Retinal Population Coding %@Eizaburo Doi,Michael S. Lewicki %t2006 %cNIPS %f/NIPS/NIPS-2006-4761.pdf %*Learning to Traverse Image Manifolds %@Piotr Dollár,Vincent Rabaud,Serge J. Belongie %t2006 %cNIPS %f/NIPS/NIPS-2006-4762.pdf %*Using Combinatorial Optimization within Max-Product Belief Propagation %@Daniel Tarlow,Gal Elidan,Daphne Koller,John C. Duchi %t2006 %cNIPS %f/NIPS/NIPS-2006-4763.pdf %*Optimal Single-Class Classification Strategies %@Ran El-Yaniv,Mordechai Nisenson %t2006 %cNIPS %f/NIPS/NIPS-2006-4764.pdf %*A Small World Threshold for Economic Network Formation %@Eyal Even-dar,Michael Kearns %t2006 %cNIPS %f/NIPS/NIPS-2006-4765.pdf %*PG-means: learning the number of clusters in data %@Yu Feng,Greg Hamerly %t2006 %cNIPS %f/NIPS/NIPS-2006-4766.pdf %*Clustering Under Prior Knowledge with Application to Image Segmentation %@Dong S. Cheng,Vittorio Murino,Mário Figueiredo %t2006 %cNIPS %f/NIPS/NIPS-2006-4767.pdf %*Multi-dynamic Bayesian Networks %@Karim Filali,Jeff A. Bilmes %t2006 %cNIPS %f/NIPS/NIPS-2006-4768.pdf %*Image Retrieval and Classification Using Local Distance Functions %@Andrea Frome,Yoram Singer,Jitendra Malik %t2006 %cNIPS %f/NIPS/NIPS-2006-4769.pdf %*Multiple Instance Learning for Computer Aided Diagnosis %@Murat Dundar,Balaji Krishnapuram,R. B. Rao,Glenn M. Fung %t2006 %cNIPS %f/NIPS/NIPS-2006-4770.pdf %*Distributed Inference in Dynamical Systems %@Stanislav Funiak,Carlos Guestrin,Rahul Sukthankar,Mark A. Paskin %t2006 %cNIPS %f/NIPS/NIPS-2006-4771.pdf %*iLSTD: Eligibility Traces and Convergence Analysis %@Alborz Geramifard,Michael Bowling,Martin Zinkevich,Richard S. Sutton %t2006 %cNIPS %f/NIPS/NIPS-2006-4772.pdf %*A PAC-Bayes Risk Bound for General Loss Functions %@Pascal Germain,Alexandre Lacasse,François Laviolette,Mario Marchand %t2006 %cNIPS %f/NIPS/NIPS-2006-4773.pdf %*Bayesian Policy Gradient Algorithms %@Mohammad Ghavamzadeh,Yaakov Engel %t2006 %cNIPS %f/NIPS/NIPS-2006-4774.pdf %*Data Integration for Classification Problems Employing Gaussian Process Priors %@Mark Girolami,Mingjun Zhong %t2006 %cNIPS %f/NIPS/NIPS-2006-4775.pdf %*Approximate inference using planar graph decomposition %@Amir Globerson,Tommi S. Jaakkola %t2006 %cNIPS %f/NIPS/NIPS-2006-4776.pdf %*Near-Uniform Sampling of Combinatorial Spaces Using XOR Constraints %@Carla P. Gomes,Ashish Sabharwal,Bart Selman %t2006 %cNIPS %f/NIPS/NIPS-2006-4777.pdf %*Large Margin Multi-channel Analog-to-Digital Conversion with Applications to Neural Prosthesis %@Amit Gore,Shantanu Chakrabartty %t2006 %cNIPS %f/NIPS/NIPS-2006-4778.pdf %*Approximate Correspondences in High Dimensions %@Kristen Grauman,Trevor Darrell %t2006 %cNIPS %f/NIPS/NIPS-2006-4779.pdf %*A Kernel Method for the Two-Sample-Problem %@Arthur Gretton,Karsten M. Borgwardt,Malte Rasch,Bernhard Schölkopf,Alex J. Smola %t2006 %cNIPS %f/NIPS/NIPS-2006-4780.pdf %*Learning Nonparametric Models for Probabilistic Imitation %@David B. Grimes,Daniel R. Rashid,Rajesh P. Rao %t2006 %cNIPS %f/NIPS/NIPS-2006-4781.pdf %*Training Conditional Random Fields for Maximum Labelwise Accuracy %@Samuel S. Gross,Olga Russakovsky,Chuong B. Do,Serafim Batzoglou %t2006 %cNIPS %f/NIPS/NIPS-2006-4782.pdf %*Adaptive Spatial Filters with predefined Region of Interest for EEG based Brain-Computer-Interfaces %@Moritz Grosse-wentrup,Klaus Gramann,Martin Buss %t2006 %cNIPS %f/NIPS/NIPS-2006-4783.pdf %*Graph-Based Visual Saliency %@Jonathan Harel,Christof Koch,Pietro Perona %t2006 %cNIPS %f/NIPS/NIPS-2006-4784.pdf %*Stratification Learning: Detecting Mixed Density and Dimensionality in High Dimensional Point Clouds %@Gloria Haro,Gregory Randall,Guillermo Sapiro %t2006 %cNIPS %f/NIPS/NIPS-2006-4785.pdf %*Manifold Denoising %@Matthias Hein,Markus Maier %t2006 %cNIPS %f/NIPS/NIPS-2006-4786.pdf %*TrueSkill™: A Bayesian Skill Rating System %@Ralf Herbrich,Tom Minka,Thore Graepel %t2006 %cNIPS %f/NIPS/NIPS-2006-4787.pdf %*Prediction on a Graph with a Perceptron %@Mark Herbster,Massimiliano Pontil %t2006 %cNIPS %f/NIPS/NIPS-2006-4788.pdf %*Single Channel Speech Separation Using Factorial Dynamics %@John R. Hershey,Trausti Kristjansson,Steven Rennie,Peder A. Olsen %t2006 %cNIPS %f/NIPS/NIPS-2006-4789.pdf %*Correcting Sample Selection Bias by Unlabeled Data %@Jiayuan Huang,Arthur Gretton,Karsten M. Borgwardt,Bernhard Schölkopf,Alex J. Smola %t2006 %cNIPS %f/NIPS/NIPS-2006-4790.pdf %*Sparse Representation for Signal Classification %@Ke Huang,Selin Aviyente %t2006 %cNIPS %f/NIPS/NIPS-2006-4791.pdf %*In-Network PCA and Anomaly Detection %@Ling Huang,Long Nguyen,Minos Garofalakis,Michael I. Jordan,Anthony Joseph,Nina Taft %t2006 %cNIPS %f/NIPS/NIPS-2006-4792.pdf %*Learning Time-Intensity Profiles of Human Activity using Non-Parametric Bayesian Models %@Alexander T. Ihler,Padhraic Smyth %t2006 %cNIPS %f/NIPS/NIPS-2006-4793.pdf %*Kernel Maximum Entropy Data Transformation and an Enhanced Spectral Clustering Algorithm %@Robert Jenssen,Torbjørn Eltoft,Mark Girolami,Deniz Erdogmus %t2006 %cNIPS %f/NIPS/NIPS-2006-4794.pdf %*Adaptor Grammars: A Framework for Specifying Compositional Nonparametric Bayesian Models %@Mark Johnson,Thomas L. Griffiths,Sharon Goldwater %t2006 %cNIPS %f/NIPS/NIPS-2006-4795.pdf %*A Humanlike Predictor of Facial Attractiveness %@Amit Kagian,Gideon Dror,Tommer Leyvand,Daniel Cohen-or,Eytan Ruppin %t2006 %cNIPS %f/NIPS/NIPS-2006-4796.pdf %*Clustering appearance and shape by learning jigsaws %@Anitha Kannan,John Winn,Carsten Rother %t2006 %cNIPS %f/NIPS/NIPS-2006-4797.pdf %*A Kernel Subspace Method by Stochastic Realization for Learning Nonlinear Dynamical Systems %@Yoshinobu Kawahara,Takehisa Yairi,Kazuo Machida %t2006 %cNIPS %f/NIPS/NIPS-2006-4798.pdf %*An Efficient Method for Gradient-Based Adaptation of Hyperparameters in SVM Models %@S. S. Keerthi,Vikas Sindhwani,Olivier Chapelle %t2006 %cNIPS %f/NIPS/NIPS-2006-4799.pdf %*Combining causal and similarity-based reasoning %@Charles Kemp,Patrick Shafto,Allison Berke,Joshua B. Tenenbaum %t2006 %cNIPS %f/NIPS/NIPS-2006-4800.pdf %*A Nonparametric Approach to Bottom-Up Visual Saliency %@Wolf Kienzle,Felix A. Wichmann,Matthias O. Franz,Bernhard Schölkopf %t2006 %cNIPS %f/NIPS/NIPS-2006-4801.pdf %*Hierarchical Dirichlet Processes with Random Effects %@Seyoung Kim,Padhraic Smyth %t2006 %cNIPS %f/NIPS/NIPS-2006-4802.pdf %*An Information Theoretic Framework for Eukaryotic Gradient Sensing %@Joseph M. Kimmel,Richard M. Salter,Peter J. Thomas %t2006 %cNIPS %f/NIPS/NIPS-2006-4803.pdf %*Information Bottleneck Optimization and Independent Component Extraction with Spiking Neurons %@Stefan Klampfl,Wolfgang Maass,Robert A. Legenstein %t2006 %cNIPS %f/NIPS/NIPS-2006-4804.pdf %*Predicting spike times from subthreshold dynamics of a neuron %@Ryota Kobayashi,Shigeru Shinomoto %t2006 %cNIPS %f/NIPS/NIPS-2006-4805.pdf %*Gaussian and Wishart Hyperkernels %@Risi Kondor,Tony Jebara %t2006 %cNIPS %f/NIPS/NIPS-2006-4806.pdf %*Causal inference in sensorimotor integration %@Konrad P. Körding,Joshua B. Tenenbaum %t2006 %cNIPS %f/NIPS/NIPS-2006-4807.pdf %*Multiple timescales and uncertainty in motor adaptation %@Konrad P. Körding,Joshua B. Tenenbaum,Reza Shadmehr %t2006 %cNIPS %f/NIPS/NIPS-2006-4808.pdf %*Reducing Calibration Time For Brain-Computer Interfaces: A Clustering Approach %@Matthias Krauledat,Michael Schröder,Benjamin Blankertz,Klaus-Robert Müller %t2006 %cNIPS %f/NIPS/NIPS-2006-4809.pdf %*Accelerated Variational Dirichlet Process Mixtures %@Kenichi Kurihara,Max Welling,Nikos A. Vlassis %t2006 %cNIPS %f/NIPS/NIPS-2006-4810.pdf %*PAC-Bayes Bounds for the Risk of the Majority Vote and the Variance of the Gibbs Classifier %@Alexandre Lacasse,François Laviolette,Mario Marchand,Pascal Germain,Nicolas Usunier %t2006 %cNIPS %f/NIPS/NIPS-2006-4811.pdf %*Inducing Metric Violations in Human Similarity Judgements %@Julian Laub,Klaus-Robert Müller,Felix A. Wichmann,Jakob H. Macke %t2006 %cNIPS %f/NIPS/NIPS-2006-4812.pdf %*Modelling transcriptional regulation using Gaussian Processes %@Neil D. Lawrence,Guido Sanguinetti,Magnus Rattray %t2006 %cNIPS %f/NIPS/NIPS-2006-4813.pdf %*Learning to Model Spatial Dependency: Semi-Supervised Discriminative Random Fields %@Chi-hoon Lee,Shaojun Wang,Feng Jiao,Dale Schuurmans,Russell Greiner %t2006 %cNIPS %f/NIPS/NIPS-2006-4814.pdf %*Efficient sparse coding algorithms %@Honglak Lee,Alexis Battle,Rajat Raina,Andrew Y. Ng %t2006 %cNIPS %f/NIPS/NIPS-2006-4815.pdf %*A Bayesian Approach to Diffusion Models of Decision-Making and Response Time %@Michael D. Lee,Ian G. Fuss,Daniel J. Navarro %t2006 %cNIPS %f/NIPS/NIPS-2006-4816.pdf %*Efficient Structure Learning of Markov Networks using L_1-Regularization %@Su-in Lee,Varun Ganapathi,Daphne Koller %t2006 %cNIPS %f/NIPS/NIPS-2006-4817.pdf %*Aggregating Classification Accuracy across Time: Application to Single Trial EEG %@Steven Lemm,Christin Schäfer,Gabriel Curio %t2006 %cNIPS %f/NIPS/NIPS-2006-4818.pdf %*Uncertainty, phase and oscillatory hippocampal recall %@Máté Lengyel,Peter Dayan %t2006 %cNIPS %f/NIPS/NIPS-2006-4819.pdf %*Speakers optimize information density through syntactic reduction %@T. F. Jaeger,Roger P. Levy %t2006 %cNIPS %f/NIPS/NIPS-2006-4820.pdf %*Real-time adaptive information-theoretic optimization of neurophysiology experiments %@Jeremy Lewi,Robert Butera,Liam Paninski %t2006 %cNIPS %f/NIPS/NIPS-2006-4821.pdf %*Ordinal Regression by Extended Binary Classification %@Ling Li,Hsuan-tien Lin %t2006 %cNIPS %f/NIPS/NIPS-2006-4822.pdf %*Conditional Random Sampling: A Sketch-based Sampling Technique for Sparse Data %@Ping Li,Kenneth W. Church,Trevor J. Hastie %t2006 %cNIPS %f/NIPS/NIPS-2006-4823.pdf %*Generalized Regularized Least-Squares Learning with Predefined Features in a Hilbert Space %@Wenye Li,Kin-hong Lee,Kwong-sak Leung %t2006 %cNIPS %f/NIPS/NIPS-2006-4824.pdf %*Learnability and the doubling dimension %@Yi Li,Philip M. Long %t2006 %cNIPS %f/NIPS/NIPS-2006-4825.pdf %*Emergence of conjunctive visual features by quadratic independent component analysis %@J.t. Lindgren,Aapo Hyvärinen %t2006 %cNIPS %f/NIPS/NIPS-2006-4826.pdf %*Bayesian Detection of Infrequent Differences in Sets of Time Series with Shared Structure %@Jennifer Listgarten,Radford M. Neal,Sam T. Roweis,Rachel Puckrin,Sean Cutler %t2006 %cNIPS %f/NIPS/NIPS-2006-4827.pdf %*Analysis of Contour Motions %@Ce Liu,William T. Freeman,Edward H. Adelson %t2006 %cNIPS %f/NIPS/NIPS-2006-4828.pdf %*Attribute-efficient learning of decision lists and linear threshold functions under unconcentrated distributions %@Philip M. Long,Rocco Servedio %t2006 %cNIPS %f/NIPS/NIPS-2006-4829.pdf %*Dynamic Foreground/Background Extraction from Images and Videos using Random Patches %@Le Lu,Gregory D. Hager %t2006 %cNIPS %f/NIPS/NIPS-2006-4830.pdf %*Effects of Stress and Genotype on Meta-parameter Dynamics in Reinforcement Learning %@Gediminas Lukšys,Jérémie Knüsel,Denis Sheynikhovich,Carmen Sandi,Wulfram Gerstner %t2006 %cNIPS %f/NIPS/NIPS-2006-4831.pdf %*Statistical Modeling of Images with Fields of Gaussian Scale Mixtures %@Siwei Lyu,Eero P. Simoncelli %t2006 %cNIPS %f/NIPS/NIPS-2006-4832.pdf %*An EM Algorithm for Localizing Multiple Sound Sources in Reverberant Environments %@Michael I. Mandel,Daniel P. Ellis,Tony Jebara %t2006 %cNIPS %f/NIPS/NIPS-2006-4833.pdf %*Isotonic Conditional Random Fields and Local Sentiment Flow %@Yi Mao,Guy Lebanon %t2006 %cNIPS %f/NIPS/NIPS-2006-4834.pdf %*Part-based Probabilistic Point Matching using Equivalence Constraints %@Graham Mcneill,Sethu Vijayakumar %t2006 %cNIPS %f/NIPS/NIPS-2006-4835.pdf %*Modeling Dyadic Data with Binary Latent Factors %@Edward Meeds,Zoubin Ghahramani,Radford M. Neal,Sam T. Roweis %t2006 %cNIPS %f/NIPS/NIPS-2006-4836.pdf %*Fast Discriminative Visual Codebooks using Randomized Clustering Forests %@Frank Moosmann,Bill Triggs,Frederic Jurie %t2006 %cNIPS %f/NIPS/NIPS-2006-4837.pdf %*Context Effects in Category Learning: An Investigation of Four Probabilistic Models %@Michael C. Mozer,Michael Shettel,Michael P. Holmes %t2006 %cNIPS %f/NIPS/NIPS-2006-4838.pdf %*Multi-Robot Negotiation: Approximating the Set of Subgame Perfect Equilibria in General-Sum Stochastic Games %@Chris Murray,Geoffrey J. Gordon %t2006 %cNIPS %f/NIPS/NIPS-2006-4839.pdf %*Non-rigid point set registration: Coherent Point Drift %@Andriy Myronenko,Xubo Song,Miguel Á. Carreira-Perpiñán %t2006 %cNIPS %f/NIPS/NIPS-2006-4840.pdf %*Fundamental Limitations of Spectral Clustering %@Boaz Nadler,Meirav Galun %t2006 %cNIPS %f/NIPS/NIPS-2006-4841.pdf %*On the Relation Between Low Density Separation, Spectral Clustering and Graph Cuts %@Hariharan Narayanan,Mikhail Belkin,Partha Niyogi %t2006 %cNIPS %f/NIPS/NIPS-2006-4842.pdf %*A Nonparametric Bayesian Method for Inferring Features From Similarity Judgments %@Daniel J. Navarro,Thomas L. Griffiths %t2006 %cNIPS %f/NIPS/NIPS-2006-4843.pdf %*Temporal dynamics of information content carried by neurons in the primary visual cortex %@Danko Nikolić,Stefan Haeusler,Wolf Singer,Wolfgang Maass %t2006 %cNIPS %f/NIPS/NIPS-2006-4844.pdf %*Blind source separation for over-determined delayed mixtures %@Lars Omlor,Martin Giese %t2006 %cNIPS %f/NIPS/NIPS-2006-4845.pdf %*The Neurodynamics of Belief Propagation on Binary Markov Random Fields %@Thomas Ott,Ruedi Stoop %t2006 %cNIPS %f/NIPS/NIPS-2006-4846.pdf %*Handling Advertisements of Unknown Quality in Search Advertising %@Sandeep Pandey,Christopher Olston %t2006 %cNIPS %f/NIPS/NIPS-2006-4847.pdf %*Bayesian Model Scoring in Markov Random Fields %@Sridevi Parise,Max Welling %t2006 %cNIPS %f/NIPS/NIPS-2006-4848.pdf %*Game Theoretic Algorithms for Protein-DNA binding %@Luis Pérez-breva,Luis E. Ortiz,Chen-hsiang Yeang,Tommi S. Jaakkola %t2006 %cNIPS %f/NIPS/NIPS-2006-4849.pdf %*Bayesian Image Super-resolution, Continued %@Lyndsey C. Pickup,David P. Capel,Stephen J. Roberts,Andrew Zisserman %t2006 %cNIPS %f/NIPS/NIPS-2006-4850.pdf %*Parameter Expanded Variational Bayesian Methods %@Tommi S. Jaakkola,Yuan Qi %t2006 %cNIPS %f/NIPS/NIPS-2006-4851.pdf %*Inferring Network Structure from Co-Occurrences %@Michael G. Rabbat,Mário Figueiredo,Robert Nowak %t2006 %cNIPS %f/NIPS/NIPS-2006-4852.pdf %*Unsupervised Regression with Applications to Nonlinear System Identification %@Ali Rahimi,Ben Recht %t2006 %cNIPS %f/NIPS/NIPS-2006-4853.pdf %*Stability of K-Means Clustering %@Alexander Rakhlin,Andrea Caponnetto %t2006 %cNIPS %f/NIPS/NIPS-2006-4854.pdf %*Efficient Learning of Sparse Representations with an Energy-Based Model %@Marc'aurelio Ranzato,Christopher Poultney,Sumit Chopra,Yann L. Cun %t2006 %cNIPS %f/NIPS/NIPS-2006-4855.pdf %*Learning to be Bayesian without Supervision %@Martin Raphan,Eero P. Simoncelli %t2006 %cNIPS %f/NIPS/NIPS-2006-4856.pdf %*Boosting Structured Prediction for Imitation Learning %@J. A. Bagnell,Joel Chestnutt,David M. Bradley,Nathan D. Ratliff %t2006 %cNIPS %f/NIPS/NIPS-2006-4857.pdf %*Large Scale Hidden Semi-Markov SVMs %@Gunnar Rätsch,Sören Sonnenburg %t2006 %cNIPS %f/NIPS/NIPS-2006-4858.pdf %*Natural Actor-Critic for Road Traffic Optimisation %@Silvia Richter,Douglas Aberdeen,Jin Yu %t2006 %cNIPS %f/NIPS/NIPS-2006-4859.pdf %*Computation of Similarity Measures for Sequential Data using Generalized Suffix Trees %@Konrad Rieck,Pavel Laskov,Sören Sonnenburg %t2006 %cNIPS %f/NIPS/NIPS-2006-4860.pdf %*Learning annotated hierarchies from relational data %@Daniel M. Roy,Charles Kemp,Vikash K. Mansinghka,Joshua B. Tenenbaum %t2006 %cNIPS %f/NIPS/NIPS-2006-4861.pdf %*Shifting, One-Inclusion Mistake Bounds and Tight Multiclass Expected Risk Bounds %@Benjamin I. Rubinstein,Peter L. Bartlett,J. H. Rubinstein %t2006 %cNIPS %f/NIPS/NIPS-2006-4862.pdf %*Neurophysiological Evidence of Cooperative Mechanisms for Stereo Computation %@Jason M. Samonds,Brian R. Potetz,Tai S. Lee %t2006 %cNIPS %f/NIPS/NIPS-2006-4863.pdf %*Robotic Grasping of Novel Objects %@Ashutosh Saxena,Justin Driemeyer,Justin Kearns,Andrew Y. Ng %t2006 %cNIPS %f/NIPS/NIPS-2006-4864.pdf %*Theory and Dynamics of Perceptual Bistability %@Paul R. Schrater,Rashmi Sundareswara %t2006 %cNIPS %f/NIPS/NIPS-2006-4865.pdf %*Fast Iterative Kernel PCA %@Nicol N. Schraudolph,Simon Günter,S.v.n. Vishwanathan %t2006 %cNIPS %f/NIPS/NIPS-2006-4866.pdf %*Information Bottleneck for Non Co-Occurrence Data %@Yevgeny Seldin,Noam Slonim,Naftali Tishby %t2006 %cNIPS %f/NIPS/NIPS-2006-4867.pdf %*Large Margin Hidden Markov Models for Automatic Speech Recognition %@Fei Sha,Lawrence K. Saul %t2006 %cNIPS %f/NIPS/NIPS-2006-4868.pdf %*Nonlinear physically-based models for decoding motor-cortical population activity %@Gregory Shakhnarovich,Sung-phil Kim,Michael J. Black %t2006 %cNIPS %f/NIPS/NIPS-2006-4869.pdf %*Convex Repeated Games and Fenchel Duality %@Shai Shalev-shwartz,Yoram Singer %t2006 %cNIPS %f/NIPS/NIPS-2006-4870.pdf %*Recursive ICA %@Honghao Shan,Lingyun Zhang,Garrison W. Cottrell %t2006 %cNIPS %f/NIPS/NIPS-2006-4871.pdf %*Chained Boosting %@Christian R. Shelton,Wesley Huie,Kin F. Kan %t2006 %cNIPS %f/NIPS/NIPS-2006-4872.pdf %*A recipe for optimizing a time-histogram %@Hideaki Shimazaki,Shigeru Shinomoto %t2006 %cNIPS %f/NIPS/NIPS-2006-4873.pdf %*Mutagenetic tree Fisher kernel improves prediction of HIV drug resistance from viral genotype %@Tobias Sing,Niko Beerenwinkel %t2006 %cNIPS %f/NIPS/NIPS-2006-4874.pdf %*Hidden Markov Dirichlet Process: Modeling Genetic Recombination in Open Ancestral Space %@Kyung-ah Sohn,Eric P. Xing %t2006 %cNIPS %f/NIPS/NIPS-2006-4875.pdf %*Learning Dense 3D Correspondence %@Florian Steinke,Volker Blanz,Bernhard Schölkopf %t2006 %cNIPS %f/NIPS/NIPS-2006-4876.pdf %*An Oracle Inequality for Clipped Regularized Risk Minimizers %@Ingo Steinwart,Don Hush,Clint Scovel %t2006 %cNIPS %f/NIPS/NIPS-2006-4877.pdf %*Learning Structural Equation Models for fMRI %@Enrico Simonotto,Heather Whalley,Stephen Lawrie,Lawrence Murray,David Mcgonigle,Amos J. Storkey %t2006 %cNIPS %f/NIPS/NIPS-2006-4878.pdf %*Mixture Regression for Covariate Shift %@Masashi Sugiyama,Amos J. Storkey %t2006 %cNIPS %f/NIPS/NIPS-2006-4879.pdf %*Modeling Human Motion Using Binary Latent Variables %@Graham W. Taylor,Geoffrey E. Hinton,Sam T. Roweis %t2006 %cNIPS %f/NIPS/NIPS-2006-4880.pdf %*A Collapsed Variational Bayesian Inference Algorithm for Latent Dirichlet Allocation %@Yee W. Teh,David Newman,Max Welling %t2006 %cNIPS %f/NIPS/NIPS-2006-4881.pdf %*Logistic Regression for Single Trial EEG Classification %@Ryota Tomioka,Kazuyuki Aihara,Klaus-Robert Müller %t2006 %cNIPS %f/NIPS/NIPS-2006-4882.pdf %*Large Margin Component Analysis %@Lorenzo Torresani,Kuang-chih Lee %t2006 %cNIPS %f/NIPS/NIPS-2006-4883.pdf %*Learning Motion Style Synthesis from Perceptual Observations %@Lorenzo Torresani,Peggy Hackney,Christoph Bregler %t2006 %cNIPS %f/NIPS/NIPS-2006-4884.pdf %*Large-Scale Sparsified Manifold Regularization %@Ivor W. Tsang,James T. Kwok %t2006 %cNIPS %f/NIPS/NIPS-2006-4885.pdf %*Scalable Discriminative Learning for Natural Language Parsing and Translation %@Joseph Turian,Benjamin Wellington,I. D. Melamed %t2006 %cNIPS %f/NIPS/NIPS-2006-4886.pdf %*Generalized Maximum Margin Clustering and Unsupervised Kernel Learning %@Hamed Valizadegan,Rong Jin %t2006 %cNIPS %f/NIPS/NIPS-2006-4887.pdf %*A Complexity-Distortion Approach to Joint Pattern Alignment %@Andrea Vedaldi,Stefano Soatto %t2006 %cNIPS %f/NIPS/NIPS-2006-4888.pdf %*Comparative Gene Prediction using Conditional Random Fields %@Jade P. Vinson,David Decaprio,Matthew D. Pearson,Stacey Luoma,James E. Galagan %t2006 %cNIPS %f/NIPS/NIPS-2006-4889.pdf %*Fast Computation of Graph Kernels %@Karsten M. Borgwardt,Nicol N. Schraudolph,S.v.n. Vishwanathan %t2006 %cNIPS %f/NIPS/NIPS-2006-4890.pdf %*High-Dimensional Graphical Model Selection Using \ell_1-Regularized Logistic Regression %@Martin J. Wainwright,John D. Lafferty,Pradeep K. Ravikumar %t2006 %cNIPS %f/NIPS/NIPS-2006-4891.pdf %*Attentional Processing on a Spike-Based VLSI Neural Network %@Yingxue Wang,Rodney J. Douglas,Shih-Chii Liu %t2006 %cNIPS %f/NIPS/NIPS-2006-4892.pdf %*Randomized PCA Algorithms with Regret Bounds that are Logarithmic in the Dimension %@Manfred K. Warmuth,Dima Kuzmin %t2006 %cNIPS %f/NIPS/NIPS-2006-4893.pdf %*Graph Laplacian Regularization for Large-Scale Semidefinite Programming %@Kilian Q. Weinberger,Fei Sha,Qihui Zhu,Lawrence K. Saul %t2006 %cNIPS %f/NIPS/NIPS-2006-4894.pdf %*Analysis of Empirical Bayesian Methods for Neuroelectromagnetic Source Localization %@Rey Ramírez,Jason Palmer,Scott Makeig,Bhaskar D. Rao,David P. Wipf %t2006 %cNIPS %f/NIPS/NIPS-2006-4895.pdf %*Particle Filtering for Nonparametric Bayesian Matrix Factorization %@Frank Wood,Thomas L. Griffiths %t2006 %cNIPS %f/NIPS/NIPS-2006-4896.pdf %*A Scalable Machine Learning Approach to Go %@Lin Wu,Pierre F. Baldi %t2006 %cNIPS %f/NIPS/NIPS-2006-4897.pdf %*A Local Learning Approach for Clustering %@Mingrui Wu,Bernhard Schölkopf %t2006 %cNIPS %f/NIPS/NIPS-2006-4898.pdf %*The Robustness-Performance Tradeoff in Markov Decision Processes %@Huan Xu,Shie Mannor %t2006 %cNIPS %f/NIPS/NIPS-2006-4899.pdf %*Stochastic Relational Models for Discriminative Link Prediction %@Kai Yu,Wei Chu,Shipeng Yu,Volker Tresp,Zhao Xu %t2006 %cNIPS %f/NIPS/NIPS-2006-4900.pdf %*Nonnegative Sparse PCA %@Ron Zass,Amnon Shashua %t2006 %cNIPS %f/NIPS/NIPS-2006-4901.pdf %*Doubly Stochastic Normalization for Spectral Clustering %@Ron Zass,Amnon Shashua %t2006 %cNIPS %f/NIPS/NIPS-2006-4902.pdf %*Simplifying Mixture Models through Function Approximation %@Kai Zhang,James T. Kwok %t2006 %cNIPS %f/NIPS/NIPS-2006-4903.pdf %*Hyperparameter Learning for Graph Based Semi-supervised Learning Algorithms %@Xinhua Zhang,Wee S. Lee %t2006 %cNIPS %f/NIPS/NIPS-2006-4904.pdf %*MLLE: Modified Locally Linear Embedding Using Multiple Weights %@Zhenyue Zhang,Jing Wang %t2006 %cNIPS %f/NIPS/NIPS-2006-4905.pdf %*Learning with Hypergraphs: Clustering, Classification, and Embedding %@Denny Zhou,Jiayuan Huang,Bernhard Schölkopf %t2006 %cNIPS %f/NIPS/NIPS-2006-4906.pdf %*Multi-Instance Multi-Label Learning with Application to Scene Classification %@Zhi-hua Zhou,Min-ling Zhang %t2006 %cNIPS %f/NIPS/NIPS-2006-4907.pdf %*Unsupervised Learning of a Probabilistic Grammar for Object Detection and Parsing %@Yuanhao Chen,Long Zhu,Alan L. Yuille %t2006 %cNIPS %f/NIPS/NIPS-2006-4908.pdf %*A Probabilistic Algorithm Integrating Source Localization and Noise Suppression of MEG and EEG data %@Johanna M. Zumer,Hagai T. Attias,Kensuke Sekihara,Srikantan S. Nagarajan %t2006 %cNIPS %f/NIPS/NIPS-2006-4909.pdf %*Learning vehicular dynamics, with application to modeling helicopters %@Pieter Abbeel,Varun Ganapathi,Andrew Y. Ng %t2005 %cNIPS %f/NIPS/NIPS-2005-4910.pdf %*Kernelized Infomax Clustering %@David Barber,Felix V. Agakov %t2005 %cNIPS %f/NIPS/NIPS-2005-4911.pdf %*Large-scale biophysical parameter estimation in single neurons via constrained linear regression %@Misha Ahrens,Liam Paninski,Quentin J. Huys %t2005 %cNIPS %f/NIPS/NIPS-2005-4912.pdf %*Maximum Margin Semi-Supervised Learning for Structured Variables %@Y. Altun,D. McAllester,M. Belkin %t2005 %cNIPS %f/NIPS/NIPS-2005-4913.pdf %*Large scale networks fingerprinting and visualization using the k-core decomposition %@J. I. Alvarez-hamelin,Luca Dall'asta,Alain Barrat,Alessandro Vespignani %t2005 %cNIPS %f/NIPS/NIPS-2005-4914.pdf %*Fast Information Value for Graphical Models %@Brigham S. Anderson,Andrew W. Moore %t2005 %cNIPS %f/NIPS/NIPS-2005-4915.pdf %*Combining Graph Laplacians for Semi--Supervised Learning %@Andreas Argyriou,Mark Herbster,Massimiliano Pontil %t2005 %cNIPS %f/NIPS/NIPS-2005-4916.pdf %*Learning in Silicon: Timing is Everything %@John V. Arthur,Kwabena Boahen %t2005 %cNIPS %f/NIPS/NIPS-2005-4917.pdf %*On Local Rewards and Scaling Distributed Reinforcement Learning %@Drew Bagnell,Andrew Y. Ng %t2005 %cNIPS %f/NIPS/NIPS-2005-4918.pdf %*Bayesian models of human action understanding %@Chris Baker,Rebecca Saxe,Joshua B. Tenenbaum %t2005 %cNIPS %f/NIPS/NIPS-2005-4919.pdf %*The Curse of Highly Variable Functions for Local Kernel Machines %@Yoshua Bengio,Olivier Delalleau,Nicolas L. Roux %t2005 %cNIPS %f/NIPS/NIPS-2005-4920.pdf %*Non-Local Manifold Parzen Windows %@Yoshua Bengio,Hugo Larochelle,Pascal Vincent %t2005 %cNIPS %f/NIPS/NIPS-2005-4921.pdf %*Convex Neural Networks %@Yoshua Bengio,Nicolas L. Roux,Pascal Vincent,Olivier Delalleau,Patrice Marcotte %t2005 %cNIPS %f/NIPS/NIPS-2005-4922.pdf %*Non-Gaussian Component Analysis: a Semi-parametric Framework for Linear Dimension Reduction %@Gilles Blanchard,Masashi Sugiyama,Motoaki Kawanabe,Vladimir Spokoiny,Klaus-Robert Müller %t2005 %cNIPS %f/NIPS/NIPS-2005-4923.pdf %*From Weighted Classification to Policy Search %@Doron Blatt,Alfred O. Hero %t2005 %cNIPS %f/NIPS/NIPS-2005-4924.pdf %*Correlated Topic Models %@John D. Lafferty,David M. Blei %t2005 %cNIPS %f/NIPS/NIPS-2005-4925.pdf %*Saliency Based on Information Maximization %@Neil Bruce,John Tsotsos %t2005 %cNIPS %f/NIPS/NIPS-2005-4926.pdf %*Active Learning For Identifying Function Threshold Boundaries %@Brent Bryan,Robert C. Nichol,Christopher R. Genovese,Jeff Schneider,Christopher J. Miller,Larry Wasserman %t2005 %cNIPS %f/NIPS/NIPS-2005-4927.pdf %*Subsequence Kernels for Relation Extraction %@Raymond J. Mooney,Razvan C. Bunescu %t2005 %cNIPS %f/NIPS/NIPS-2005-4928.pdf %*Faster Rates in Regression via Active Learning %@Rebecca Willett,Robert Nowak,Rui M. Castro %t2005 %cNIPS %f/NIPS/NIPS-2005-4929.pdf %*Gradient Flow Independent Component Analysis in Micropower VLSI %@Abdullah Celik,Milutin Stanacevic,Gert Cauwenberghs %t2005 %cNIPS %f/NIPS/NIPS-2005-4930.pdf %*Improved risk tail bounds for on-line algorithms %@Nicolò Cesa-bianchi,Claudio Gentile %t2005 %cNIPS %f/NIPS/NIPS-2005-4931.pdf %*Layered Dynamic Textures %@Antoni B. Chan,Nuno Vasconcelos %t2005 %cNIPS %f/NIPS/NIPS-2005-4932.pdf %*Size Regularized Cut for Data Clustering %@Yixin Chen,Ya Zhang,Xiang Ji %t2005 %cNIPS %f/NIPS/NIPS-2005-4933.pdf %*Learning from Data of Variable Quality %@Koby Crammer,Michael Kearns,Jennifer Wortman %t2005 %cNIPS %f/NIPS/NIPS-2005-4934.pdf %*Efficient estimation of hidden state dynamics from spike trains %@Marton G. Danoczy,Richard H. R. Hahnloser %t2005 %cNIPS %f/NIPS/NIPS-2005-4935.pdf %*Norepinephrine and Neural Interrupts %@Peter Dayan,Angela J. Yu %t2005 %cNIPS %f/NIPS/NIPS-2005-4936.pdf %*Fast Krylov Methods for N-Body Learning %@Nando D. Freitas,Yang Wang,Maryam Mahdaviani,Dustin Lang %t2005 %cNIPS %f/NIPS/NIPS-2005-4937.pdf %*The Forgetron: A Kernel-Based Perceptron on a Fixed Budget %@Ofer Dekel,Shai Shalev-shwartz,Yoram Singer %t2005 %cNIPS %f/NIPS/NIPS-2005-4938.pdf %*Data-Driven Online to Batch Conversions %@Ofer Dekel,Yoram Singer %t2005 %cNIPS %f/NIPS/NIPS-2005-4939.pdf %*Beyond Gaussian Processes: On the Distributions of Infinite Networks %@Ricky Der,Daniel D. Lee %t2005 %cNIPS %f/NIPS/NIPS-2005-4940.pdf %*Generalized Nonnegative Matrix Approximations with Bregman Divergences %@Suvrit Sra,Inderjit S. Dhillon %t2005 %cNIPS %f/NIPS/NIPS-2005-4941.pdf %*An Application of Markov Random Fields to Range Sensing %@James Diebel,Sebastian Thrun %t2005 %cNIPS %f/NIPS/NIPS-2005-4942.pdf %*Transfer learning for text classification %@Chuong B. Do,Andrew Y. Ng %t2005 %cNIPS %f/NIPS/NIPS-2005-4943.pdf %*A Theoretical Analysis of Robust Coding over Noisy Overcomplete Channels %@Eizaburo Doi,Doru C. Balcan,Michael S. Lewicki %t2005 %cNIPS %f/NIPS/NIPS-2005-4944.pdf %*Optimizing spatio-temporal filters for improving Brain-Computer Interfacing %@Guido Dornhege,Benjamin Blankertz,Matthias Krauledat,Florian Losch,Gabriel Curio,Klaus-Robert Müller %t2005 %cNIPS %f/NIPS/NIPS-2005-4945.pdf %*Correcting sample selection bias in maximum entropy density estimation %@Miroslav Dudík,Steven J. Phillips,Robert E. Schapire %t2005 %cNIPS %f/NIPS/NIPS-2005-4946.pdf %*Searching for Character Models %@Jaety Edwards,David Forsyth %t2005 %cNIPS %f/NIPS/NIPS-2005-4947.pdf %*Hierarchical Linear/Constant Time SLAM Using Particle Filters for Dense Maps %@Austin I. Eliazar,Ronald Parr %t2005 %cNIPS %f/NIPS/NIPS-2005-4948.pdf %*Learning to Control an Octopus Arm with Gaussian Process Temporal Difference Methods %@Yaakov Engel,Peter Szabo,Dmitry Volkinshtein %t2005 %cNIPS %f/NIPS/NIPS-2005-4949.pdf %*Two view learning: SVM-2K, Theory and Practice %@Jason Farquhar,David Hardoon,Hongying Meng,John S. Shawe-taylor,Sándor Szedmák %t2005 %cNIPS %f/NIPS/NIPS-2005-4950.pdf %*Robust design of biological experiments %@Patrick Flaherty,Adam Arkin,Michael I. Jordan %t2005 %cNIPS %f/NIPS/NIPS-2005-4951.pdf %*Pattern Recognition from One Example by Chopping %@Francois Fleuret,Gilles Blanchard %t2005 %cNIPS %f/NIPS/NIPS-2005-4952.pdf %*Mixture Modeling by Affinity Propagation %@Brendan J. Frey,Delbert Dueck %t2005 %cNIPS %f/NIPS/NIPS-2005-4953.pdf %*Statistical Convergence of Kernel CCA %@Kenji Fukumizu,Arthur Gretton,Francis R. Bach %t2005 %cNIPS %f/NIPS/NIPS-2005-4954.pdf %*Learning Rankings via Convex Hull Separation %@Glenn Fung,Rómer Rosales,Balaji Krishnapuram %t2005 %cNIPS %f/NIPS/NIPS-2005-4955.pdf %*A Connectionist Model for Constructive Modal Reasoning %@Artur Garcez,Luis C. Lamb,Dov M. Gabbay %t2005 %cNIPS %f/NIPS/NIPS-2005-4956.pdf %*Large-Scale Multiclass Transduction %@Thomas Gärtner,Quoc V. Le,Simon Burton,Alex J. Smola,Vishy Vishwanathan %t2005 %cNIPS %f/NIPS/NIPS-2005-4957.pdf %*Products of ``Edge-perts %@Max Welling,Peter V. Gehler %t2005 %cNIPS %f/NIPS/NIPS-2005-4958.pdf %*Fast biped walking with a reflexive controller and real-time policy searching %@Tao Geng,Bernd Porr,Florentin Wörgötter %t2005 %cNIPS %f/NIPS/NIPS-2005-4959.pdf %*Bayesian Sets %@Zoubin Ghahramani,Katherine A. Heller %t2005 %cNIPS %f/NIPS/NIPS-2005-4960.pdf %*Query by Committee Made Real %@Ran Gilad-bachrach,Amir Navot,Naftali Tishby %t2005 %cNIPS %f/NIPS/NIPS-2005-4961.pdf %*Metric Learning by Collapsing Classes %@Amir Globerson,Sam T. Roweis %t2005 %cNIPS %f/NIPS/NIPS-2005-4962.pdf %*Interpolating between types and tokens by estimating power-law generators %@Sharon Goldwater,Mark Johnson,Thomas L. Griffiths %t2005 %cNIPS %f/NIPS/NIPS-2005-4963.pdf %*A Probabilistic Interpretation of SVMs with an Application to Unbalanced Classification %@Yves Grandvalet,Johnny Mariethoz,Samy Bengio %t2005 %cNIPS %f/NIPS/NIPS-2005-4964.pdf %*Infinite latent feature models and the Indian buffet process %@Zoubin Ghahramani,Thomas L. Griffiths %t2005 %cNIPS %f/NIPS/NIPS-2005-4965.pdf %*Computing the Solution Path for the Regularized Support Vector Regression %@Lacey Gunter,Ji Zhu %t2005 %cNIPS %f/NIPS/NIPS-2005-4966.pdf %*Hot Coupling: A Particle Approach to Inference and Normalization on Pairwise Undirected Graphs %@Firas Hamze,Nando de Freitas %t2005 %cNIPS %f/NIPS/NIPS-2005-4967.pdf %*Tensor Subspace Analysis %@Xiaofei He,Deng Cai,Partha Niyogi %t2005 %cNIPS %f/NIPS/NIPS-2005-4968.pdf %*Laplacian Score for Feature Selection %@Xiaofei He,Deng Cai,Partha Niyogi %t2005 %cNIPS %f/NIPS/NIPS-2005-4969.pdf %*Inferring Motor Programs from Images of Handwritten Digits %@Vinod Nair,Geoffrey E. Hinton %t2005 %cNIPS %f/NIPS/NIPS-2005-4970.pdf %*Response Analysis of Neuronal Population with Synaptic Depression %@Wentao Huang,Licheng Jiao,Shan Tan,Maoguo Gong %t2005 %cNIPS %f/NIPS/NIPS-2005-4971.pdf %*Non-iterative Estimation with Perturbed Gaussian Markov Processes %@Yunsong Huang,B. Keith Jenkins %t2005 %cNIPS %f/NIPS/NIPS-2005-4972.pdf %*Bayesian Surprise Attracts Human Attention %@Laurent Itti,Pierre F. Baldi %t2005 %cNIPS %f/NIPS/NIPS-2005-4973.pdf %*Efficient Estimation of OOMs %@Herbert Jaeger,Mingjie Zhao,Andreas Kolling %t2005 %cNIPS %f/NIPS/NIPS-2005-4974.pdf %*Representing Part-Whole Relationships in Recurrent Neural Networks %@Viren Jain,Valentin Zhigulin,H. S. Seung %t2005 %cNIPS %f/NIPS/NIPS-2005-4975.pdf %*A Probabilistic Approach for Optimizing Spectral Clustering %@Rong Jin,Feng Kang,Chris H. Ding %t2005 %cNIPS %f/NIPS/NIPS-2005-4976.pdf %*Walk-Sum Interpretation and Analysis of Gaussian Belief Propagation %@Dmitry Malioutov,Alan S. Willsky,Jason K. Johnson %t2005 %cNIPS %f/NIPS/NIPS-2005-4977.pdf %*Using ``epitomes'' to model genetic diversity: Rational design of HIV vaccine cocktails %@Nebojsa Jojic,Vladimir Jojic,Christopher Meek,David Heckerman,Brendan J. Frey %t2005 %cNIPS %f/NIPS/NIPS-2005-4978.pdf %*Integrate-and-Fire models with adaptation are good enough %@Renaud Jolivet,Alexander Rauch,Hans-rudolf Lüscher,Wulfram Gerstner %t2005 %cNIPS %f/NIPS/NIPS-2005-4979.pdf %*Generalization Error Bounds for Aggregation by Mirror Descent with Averaging %@Anatoli Juditsky,Alexander Nazin,Alexandre Tsybakov,Nicolas Vayatis %t2005 %cNIPS %f/NIPS/NIPS-2005-4980.pdf %*From Batch to Transductive Online Learning %@Sham Kakade,Adam Tauman Kalai %t2005 %cNIPS %f/NIPS/NIPS-2005-4981.pdf %*Worst-Case Bounds for Gaussian Process Models %@Sham M. Kakade,Matthias W. Seeger,Dean P. Foster %t2005 %cNIPS %f/NIPS/NIPS-2005-4982.pdf %*Hyperparameter and Kernel Learning for Graph Based Semi-Supervised Classification %@Ashish Kapoor,Hyungil Ahn,Yuan Qi,Rosalind W. Picard %t2005 %cNIPS %f/NIPS/NIPS-2005-4983.pdf %*Is Early Vision Optimized for Extracting Higher-order Dependencies? %@Yan Karklin,Michael S. Lewicki %t2005 %cNIPS %f/NIPS/NIPS-2005-4984.pdf %*A matching pursuit approach to sparse Gaussian process regression %@Sathiya Keerthi,Wei Chu %t2005 %cNIPS %f/NIPS/NIPS-2005-4985.pdf %*Benchmarking Non-Parametric Statistical Tests %@Mikaela Keller,Samy Bengio,Siew Y. Wong %t2005 %cNIPS %f/NIPS/NIPS-2005-4986.pdf %*Robust Fisher Discriminant Analysis %@Seung-jean Kim,Alessandro Magnani,Stephen Boyd %t2005 %cNIPS %f/NIPS/NIPS-2005-4987.pdf %*Measuring Shared Information and Coordinated Activity in Neuronal Networks %@Kristina Klinkner,Cosma Shalizi,Marcelo Camperi %t2005 %cNIPS %f/NIPS/NIPS-2005-4988.pdf %*Inference with Minimal Communication: a Decision-Theoretic Variational Approach %@O. P. Kreidl,Alan S. Willsky %t2005 %cNIPS %f/NIPS/NIPS-2005-4989.pdf %*Generalization in Clustering with Unobserved Features %@Eyal Krupka,Naftali Tishby %t2005 %cNIPS %f/NIPS/NIPS-2005-4990.pdf %*Variable KD-Tree Algorithms for Spatial Pattern Search and Discovery %@Jeremy Kubica,Joseph Masiero,Robert Jedicke,Andrew Connolly,Andrew W. Moore %t2005 %cNIPS %f/NIPS/NIPS-2005-4991.pdf %*Assessing Approximations for Gaussian Process Classification %@Malte Kuss,Carl E. Rasmussen %t2005 %cNIPS %f/NIPS/NIPS-2005-4992.pdf %*Rodeo: Sparse Nonparametric Regression in High Dimensions %@Larry Wasserman,John D. Lafferty %t2005 %cNIPS %f/NIPS/NIPS-2005-4993.pdf %*Fusion of Similarity Data in Clustering %@Tilman Lange,Joachim M. Buhmann %t2005 %cNIPS %f/NIPS/NIPS-2005-4994.pdf %*A PAC-Bayes approach to the Set Covering Machine %@François Laviolette,Mario Marchand,Mohak Shah %t2005 %cNIPS %f/NIPS/NIPS-2005-4995.pdf %*Off-Road Obstacle Avoidance through End-to-End Learning %@Urs Muller,Jan Ben,Eric Cosatto,Beat Flepp,Yann L. Cun %t2005 %cNIPS %f/NIPS/NIPS-2005-4996.pdf %*Dual-Tree Fast Gauss Transforms %@Dongryeol Lee,Andrew W. Moore,Alexander G. Gray %t2005 %cNIPS %f/NIPS/NIPS-2005-4997.pdf %*CMOL CrossNets: Possible Neuromorphic Nanoelectronic Circuits %@Jung Hoon Lee,Xiaolong Ma,Konstantin K. Likharev %t2005 %cNIPS %f/NIPS/NIPS-2005-4998.pdf %*A Criterion for the Convergence of Learning with Spike Timing Dependent Plasticity %@Robert A. Legenstein,Wolfgang Maass %t2005 %cNIPS %f/NIPS/NIPS-2005-4999.pdf %*Dynamical Synapses Give Rise to a Power-Law Distribution of Neuronal Avalanches %@Anna Levina,Michael Herrmann %t2005 %cNIPS %f/NIPS/NIPS-2005-5000.pdf %*From Lasso regression to Feature vector machine %@Fan Li,Yiming Yang,Eric P. Xing %t2005 %cNIPS %f/NIPS/NIPS-2005-5001.pdf %*Location-based activity recognition %@Lin Liao,Dieter Fox,Henry Kautz %t2005 %cNIPS %f/NIPS/NIPS-2005-5002.pdf %*Radial Basis Function Network for Multi-task Learning %@Xuejun Liao,Lawrence Carin %t2005 %cNIPS %f/NIPS/NIPS-2005-5003.pdf %*Asymptotics of Gaussian Regularized Least Squares %@Ross Lippert,Ryan Rifkin %t2005 %cNIPS %f/NIPS/NIPS-2005-5004.pdf %*Efficient Unsupervised Learning for Localization and Detection in Object Categories %@Nicolas Loeff,Himanshu Arora,Alexander Sorokin,David Forsyth %t2005 %cNIPS %f/NIPS/NIPS-2005-5005.pdf %*Convergence and Consistency of Regularized Boosting Algorithms with Stationary B-Mixing Observations %@Aurelie C. Lozano,Sanjeev R. Kulkarni,Robert E. Schapire %t2005 %cNIPS %f/NIPS/NIPS-2005-5006.pdf %*Ideal Observers for Detecting Motion: Correspondence Noise %@Hongjing Lu,Alan L. Yuille %t2005 %cNIPS %f/NIPS/NIPS-2005-5007.pdf %*Principles of real-time computing with feedback applied to cortical microcircuit models %@Wolfgang Maass,Prashant Joshi,Eduardo D. Sontag %t2005 %cNIPS %f/NIPS/NIPS-2005-5008.pdf %*Value Function Approximation with Diffusion Wavelets and Laplacian Eigenfunctions %@Sridhar Mahadevan,Mauro Maggioni %t2005 %cNIPS %f/NIPS/NIPS-2005-5009.pdf %*Noise and the two-thirds power Law %@Uri Maoz,Elon Portugaly,Tamar Flash,Yair Weiss %t2005 %cNIPS %f/NIPS/NIPS-2005-5010.pdf %*Modeling Memory Transfer and Saving in Cerebellar Motor Learning %@Naoki Masuda,Shun-ichi Amari %t2005 %cNIPS %f/NIPS/NIPS-2005-5011.pdf %*An exploration-exploitation model based on norepinepherine and dopamine activity %@Samuel M. McClure,Mark S. Gilzenrat,Jonathan D. Cohen %t2005 %cNIPS %f/NIPS/NIPS-2005-5012.pdf %*Online Discovery and Learning of Predictive State Representations %@Peter Mccracken,Michael Bowling %t2005 %cNIPS %f/NIPS/NIPS-2005-5013.pdf %*An Alternative Infinite Mixture Of Gaussian Process Experts %@Edward Meeds,Simon Osindero %t2005 %cNIPS %f/NIPS/NIPS-2005-5014.pdf %*Unbiased Estimator of Shape Parameter for Spiking Irregularities under Changing Environments %@Keiji Miura,Masato Okada,Shun-ichi Amari %t2005 %cNIPS %f/NIPS/NIPS-2005-5015.pdf %*Consensus Propagation %@Benjamin V. Roy,Ciamac C. Moallemi %t2005 %cNIPS %f/NIPS/NIPS-2005-5016.pdf %*Context as Filtering %@Daichi Mochihashi,Yuji Matsumoto %t2005 %cNIPS %f/NIPS/NIPS-2005-5017.pdf %*Spectral Bounds for Sparse PCA: Exact and Greedy Algorithms %@Baback Moghaddam,Yair Weiss,Shai Avidan %t2005 %cNIPS %f/NIPS/NIPS-2005-5018.pdf %*Top-Down Control of Visual Attention: A Rational Account %@Michael Shettel,Shaun Vecera,Michael C. Mozer %t2005 %cNIPS %f/NIPS/NIPS-2005-5019.pdf %*Rate Distortion Codes in Sensor Networks: A System-level Analysis %@Tatsuto Murayama,Peter Davis %t2005 %cNIPS %f/NIPS/NIPS-2005-5020.pdf %*Gaussian Processes for Multiuser Detection in CDMA receivers %@Juan J. Murillo-fuentes,Sebastian Caro,Fernando Pérez-Cruz %t2005 %cNIPS %f/NIPS/NIPS-2005-5021.pdf %*Nested sampling for Potts models %@Iain Murray,David MacKay,Zoubin Ghahramani,John Skilling %t2005 %cNIPS %f/NIPS/NIPS-2005-5022.pdf %*Diffusion Maps, Spectral Clustering and Eigenfunctions of Fokker-Planck Operators %@Boaz Nadler,Stephane Lafon,Ioannis Kevrekidis,Ronald R. Coifman %t2005 %cNIPS %f/NIPS/NIPS-2005-5023.pdf %*Stimulus Evoked Independent Factor Analysis of MEG Data with Large Background Activity %@Kenneth Hild,Kensuke Sekihara,Hagai T. Attias,Srikantan S. Nagarajan %t2005 %cNIPS %f/NIPS/NIPS-2005-5024.pdf %*An Analog Visual Pre-Processing Processor Employing Cyclic Line Access in Only-Nearest-Neighbor-Interconnects Architecture %@Yusuke Nakashita,Yoshio Mita,Tadashi Shibata %t2005 %cNIPS %f/NIPS/NIPS-2005-5025.pdf %*Q-Clustering %@Mukund Narasimhan,Nebojsa Jojic,Jeff A. Bilmes %t2005 %cNIPS %f/NIPS/NIPS-2005-5026.pdf %*Optimal cue selection strategy %@Vidhya Navalpakkam,Laurent Itti %t2005 %cNIPS %f/NIPS/NIPS-2005-5027.pdf %*Nearest Neighbor Based Feature Selection for Regression and its Application to Neural Activity %@Amir Navot,Lavi Shpigelman,Naftali Tishby,Eilon Vaadia %t2005 %cNIPS %f/NIPS/NIPS-2005-5028.pdf %*A Bayesian Spatial Scan Statistic %@Daniel B. Neill,Andrew W. Moore,Gregory F. Cooper %t2005 %cNIPS %f/NIPS/NIPS-2005-5029.pdf %*Divergences, surrogate loss functions and experimental design %@Long Nguyen,Martin J. Wainwright,Michael I. Jordan %t2005 %cNIPS %f/NIPS/NIPS-2005-5030.pdf %*How fast to work: Response vigor, motivation and tonic dopamine %@Yael Niv,Nathaniel D. Daw,Peter Dayan %t2005 %cNIPS %f/NIPS/NIPS-2005-5031.pdf %*Analyzing Coupled Brain Sources: Distinguishing True from Spurious Interaction %@Guido Nolte,Andreas Ziehe,Frank Meinecke,Klaus-Robert Müller %t2005 %cNIPS %f/NIPS/NIPS-2005-5032.pdf %*Bayesian model learning in human visual perception %@Gergő Orbán,Jozsef Fiser,Richard N. Aslin,Máté Lengyel %t2005 %cNIPS %f/NIPS/NIPS-2005-5033.pdf %*Spiking Inputs to a Winner-take-all Network %@Matthias Oster,Shih-Chii Liu %t2005 %cNIPS %f/NIPS/NIPS-2005-5034.pdf %*Variational EM Algorithms for Non-Gaussian Latent Variable Models %@Jason Palmer,Kenneth Kreutz-Delgado,Bhaskar D. Rao,David P. Wipf %t2005 %cNIPS %f/NIPS/NIPS-2005-5035.pdf %*Neuronal Fiber Delineation in Area of Edema from Diffusion Weighted MRI %@Ofer Pasternak,Nathan Intrator,Nir Sochen,Yaniv Assaf %t2005 %cNIPS %f/NIPS/NIPS-2005-5036.pdf %*Beyond Pair-Based STDP: a Phenomenological Rule for Spike Triplet and Frequency Effects %@Jean-pascal Pfister,Wulfram Gerstner %t2005 %cNIPS %f/NIPS/NIPS-2005-5037.pdf %*Scaling Laws in Natural Scenes and the Inference of 3D Shape %@Tai-sing Lee,Brian R. Potetz %t2005 %cNIPS %f/NIPS/NIPS-2005-5038.pdf %*Off-policy Learning with Options and Recognizers %@Doina Precup,Cosmin Paduraru,Anna Koop,Richard S. Sutton,Satinder P. Singh %t2005 %cNIPS %f/NIPS/NIPS-2005-5039.pdf %*Estimation of Intrinsic Dimensionality Using High-Rate Vector Quantization %@Maxim Raginsky,Svetlana Lazebnik %t2005 %cNIPS %f/NIPS/NIPS-2005-5040.pdf %*Preconditioner Approximations for Probabilistic Graphical Models %@John D. Lafferty,Pradeep K. Ravikumar %t2005 %cNIPS %f/NIPS/NIPS-2005-5041.pdf %*Cue Integration for Figure/Ground Labeling %@Xiaofeng Ren,Jitendra Malik,Charless C. Fowlkes %t2005 %cNIPS %f/NIPS/NIPS-2005-5042.pdf %*Generalization to Unseen Cases %@Teemu Roos,Peter Grünwald,Petri Myllymäki,Henry Tirri %t2005 %cNIPS %f/NIPS/NIPS-2005-5043.pdf %*Dynamic Social Network Analysis using Latent Space Models %@Purnamrita Sarkar,Andrew W. Moore %t2005 %cNIPS %f/NIPS/NIPS-2005-5044.pdf %*Learning Depth from Single Monocular Images %@Ashutosh Saxena,Sung H. Chung,Andrew Y. Ng %t2005 %cNIPS %f/NIPS/NIPS-2005-5045.pdf %*Identifying Distributed Object Representations in Human Extrastriate Visual Cortex %@Rory Sayres,David Ress,Kalanit Grill-spector %t2005 %cNIPS %f/NIPS/NIPS-2005-5046.pdf %*On the Accuracy of Bounded Rationality: How Far from Optimal Is Fast and Frugal? %@Michael Schmitt,Laura Martignon %t2005 %cNIPS %f/NIPS/NIPS-2005-5047.pdf %*Fast Online Policy Gradient Learning with SMD Gain Vector Adaptation %@Jin Yu,Douglas Aberdeen,Nicol N. Schraudolph %t2005 %cNIPS %f/NIPS/NIPS-2005-5048.pdf %*The Information-Form Data Association Filter %@Brad Schumitsch,Sebastian Thrun,Gary Bradski,Kunle Olukotun %t2005 %cNIPS %f/NIPS/NIPS-2005-5049.pdf %*A Bayesian Framework for Tilt Perception and Confidence %@Odelia Schwartz,Peter Dayan,Terrence J. Sejnowski %t2005 %cNIPS %f/NIPS/NIPS-2005-5050.pdf %*Learning Minimum Volume Sets %@Clayton Scott,Robert Nowak %t2005 %cNIPS %f/NIPS/NIPS-2005-5051.pdf %*AER Building Blocks for Multi-Layer Multi-Chip Neuromorphic Vision Systems %@R. Serrano-Gotarredona,M. Oster,P. Lichtsteiner,A. Linares-Barranco,R. Paz-Vicente,F. Gomez-Rodriguez,H. Kolle Riis,T. Delbruck,S. C. Liu,S. Zahnd,A. M. Whatley,R. Douglas,P. Hafliger,G. Jimenez-Moreno,A. Civit,T. Serrano-Gotarredona,A. Acosta-Jimenez,B. Linares-Barranco %t2005 %cNIPS %f/NIPS/NIPS-2005-5052.pdf %*Fast Gaussian Process Regression using KD-Trees %@Yirong Shen,Matthias Seeger,Andrew Y. Ng %t2005 %cNIPS %f/NIPS/NIPS-2005-5053.pdf %*Learning Shared Latent Structure for Image Synthesis and Robotic Imitation %@Aaron Shon,Keith Grochow,Aaron Hertzmann,Rajesh P. Rao %t2005 %cNIPS %f/NIPS/NIPS-2005-5054.pdf %*Selecting Landmark Points for Sparse Manifold Learning %@Jorge Silva,Jorge Marques,João Lemos %t2005 %cNIPS %f/NIPS/NIPS-2005-5055.pdf %*Conditional Visual Tracking in Kernel Space %@Cristian Sminchisescu,Atul Kanujia,Zhiguo Li,Dimitris Metaxas %t2005 %cNIPS %f/NIPS/NIPS-2005-5056.pdf %*Sparse Gaussian Processes using Pseudo-inputs %@Edward Snelson,Zoubin Ghahramani %t2005 %cNIPS %f/NIPS/NIPS-2005-5057.pdf %*Phase Synchrony Rate for the Recognition of Motor Imagery in Brain-Computer Interface %@Le Song,Evian Gordon,Elly Gysels %t2005 %cNIPS %f/NIPS/NIPS-2005-5058.pdf %*A General and Efficient Multiple Kernel Learning Algorithm %@Sören Sonnenburg,Gunnar Rätsch,Christin Schäfer %t2005 %cNIPS %f/NIPS/NIPS-2005-5059.pdf %*Prediction and Change Detection %@Mark Steyvers,Scott Brown %t2005 %cNIPS %f/NIPS/NIPS-2005-5060.pdf %*Sensory Adaptation within a Bayesian Framework for Perception %@Alan Stocker,Eero P. Simoncelli %t2005 %cNIPS %f/NIPS/NIPS-2005-5061.pdf %*Describing Visual Scenes using Transformed Dirichlet Processes %@Antonio Torralba,Alan S. Willsky,Erik B. Sudderth,William T. Freeman %t2005 %cNIPS %f/NIPS/NIPS-2005-5062.pdf %*Temporal Abstraction in Temporal-difference Networks %@Eddie Rafols,Anna Koop,Richard S. Sutton %t2005 %cNIPS %f/NIPS/NIPS-2005-5063.pdf %*Sequence and Tree Kernels with Statistical Feature Mining %@Jun Suzuki,Hideki Isozaki %t2005 %cNIPS %f/NIPS/NIPS-2005-5064.pdf %*Silicon growth cones map silicon retina %@Brian Taba,Kwabena Boahen %t2005 %cNIPS %f/NIPS/NIPS-2005-5065.pdf %*Temporally changing synaptic plasticity %@Minija Tamosiunaite,Bernd Porr,Florentin Wörgötter %t2005 %cNIPS %f/NIPS/NIPS-2005-5066.pdf %*Structured Prediction via the Extragradient Method %@Ben Taskar,Simon Lacoste-Julien,Michael I. Jordan %t2005 %cNIPS %f/NIPS/NIPS-2005-5067.pdf %*Predicting EMG Data from M1 Neurons with Variational Bayesian Least Squares %@Jo-anne Ting,Aaron D'souza,Kenji Yamamoto,Toshinori Yoshioka,Donna Hoffman,Shinji Kakei,Lauren Sergio,John Kalaska,Mitsuo Kawato %t2005 %cNIPS %f/NIPS/NIPS-2005-5068.pdf %*Generalization error bounds for classifiers trained with interdependent data %@Nicolas Usunier,Massih-reza Amini,Patrick Gallinari %t2005 %cNIPS %f/NIPS/NIPS-2005-5069.pdf %*An aVLSI Cricket Ear Model %@Andre V. Schaik,Richard Reeve,Craig Jin,Tara Hamilton %t2005 %cNIPS %f/NIPS/NIPS-2005-5070.pdf %*Goal-Based Imitation as Probabilistic Inference over Graphical Models %@Deepak Verma,Rajesh P. Rao %t2005 %cNIPS %f/NIPS/NIPS-2005-5071.pdf %*Kernels for gene regulatory regions %@Jean-philippe Vert,Robert Thurman,William S. Noble %t2005 %cNIPS %f/NIPS/NIPS-2005-5072.pdf %*Consistency of one-class SVM and related algorithms %@Régis Vert,Jean-philippe Vert %t2005 %cNIPS %f/NIPS/NIPS-2005-5073.pdf %*Multiple Instance Boosting for Object Detection %@Cha Zhang,John C. Platt,Paul A. Viola %t2005 %cNIPS %f/NIPS/NIPS-2005-5074.pdf %*Recovery of Jointly Sparse Signals from Few Random Projections %@Michael B. Wakin,Marco F. Duarte,Shriram Sarvotham,Dror Baron,Richard G. Baraniuk %t2005 %cNIPS %f/NIPS/NIPS-2005-5075.pdf %*Gaussian Process Dynamical Models %@Jack Wang,Aaron Hertzmann,David M. Blei %t2005 %cNIPS %f/NIPS/NIPS-2005-5076.pdf %*Group and Topic Discovery from Relations and Their Attributes %@Xuerui Wang,Natasha Mohanty,Andrew McCallum %t2005 %cNIPS %f/NIPS/NIPS-2005-5077.pdf %*Variational Bayesian Stochastic Complexity of Mixture Models %@Kazuho Watanabe,Sumio Watanabe %t2005 %cNIPS %f/NIPS/NIPS-2005-5078.pdf %*Distance Metric Learning for Large Margin Nearest Neighbor Classification %@Kilian Q. Weinberger,John Blitzer,Lawrence K. Saul %t2005 %cNIPS %f/NIPS/NIPS-2005-5079.pdf %*Analyzing Auditory Neurons by Learning Distance Functions %@Inna Weiner,Tomer Hertz,Israel Nelken,Daphna Weinshall %t2005 %cNIPS %f/NIPS/NIPS-2005-5080.pdf %*Oblivious Equilibrium: A Mean Field Approximation for Large-Scale Dynamic Games %@Gabriel Y. Weintraub,Lanier Benkard,Benjamin Van Roy %t2005 %cNIPS %f/NIPS/NIPS-2005-5081.pdf %*Active Bidirectional Coupling in a Cochlear Chip %@Bo Wen,Kwabena A. Boahen %t2005 %cNIPS %f/NIPS/NIPS-2005-5082.pdf %*Neural mechanisms of contrast dependent receptive field size in V1 %@Jim Wielaard,Paul Sajda %t2005 %cNIPS %f/NIPS/NIPS-2005-5083.pdf %*Factorial Switching Kalman Filters for Condition Monitoring in Neonatal Intensive Care %@Christopher Williams,John Quinn,Neil Mcintosh %t2005 %cNIPS %f/NIPS/NIPS-2005-5084.pdf %*Comparing the Effects of Different Weight Distributions on Finding Sparse Representations %@Bhaskar D. Rao,David P. Wipf %t2005 %cNIPS %f/NIPS/NIPS-2005-5085.pdf %*Message passing for task redistribution on sparse graphs %@K. Y. Michael Wong,David Saad,Zhuo Gao %t2005 %cNIPS %f/NIPS/NIPS-2005-5086.pdf %*Modeling Neural Population Spiking Activity with Gibbs Distributions %@Frank Wood,Stefan Roth,Michael J. Black %t2005 %cNIPS %f/NIPS/NIPS-2005-5087.pdf %*Extracting Dynamical Structure Embedded in Neural Activity %@Byron M. Yu,Afsheen Afshar,Gopal Santhanam,Stephen I. Ryu,Krishna V. Shenoy,Maneesh Sahani %t2005 %cNIPS %f/NIPS/NIPS-2005-5088.pdf %*Soft Clustering on Graphs %@Kai Yu,Shipeng Yu,Volker Tresp %t2005 %cNIPS %f/NIPS/NIPS-2005-5089.pdf %*The Role of Top-down and Bottom-up Processes in Guiding Eye Movements during Visual Search %@Gregory Zelinsky,Wei Zhang,Bing Yu,Xin Chen,Dimitris Samaras %t2005 %cNIPS %f/NIPS/NIPS-2005-5090.pdf %*Learning Influence among Interacting Markov Chains %@Dong Zhang,Daniel Gatica-perez,Samy Bengio,Deb Roy %t2005 %cNIPS %f/NIPS/NIPS-2005-5091.pdf %*Learning Multiple Related Tasks using Latent Independent Component Analysis %@Jian Zhang,Zoubin Ghahramani,Yiming Yang %t2005 %cNIPS %f/NIPS/NIPS-2005-5092.pdf %*Modeling Neuronal Interactivity using Dynamic Bayesian Networks %@Lei Zhang,Dimitris Samaras,Nelly Alia-klein,Nora Volkow,Rita Goldstein %t2005 %cNIPS %f/NIPS/NIPS-2005-5093.pdf %*Analysis of Spectral Kernel Design based Semi-supervised Learning %@Tong Zhang,Rie Kubota Ando %t2005 %cNIPS %f/NIPS/NIPS-2005-5094.pdf %*A Computational Model of Eye Movements during Object Class Detection %@Wei Zhang,Hyejin Yang,Dimitris Samaras,Gregory J. Zelinsky %t2005 %cNIPS %f/NIPS/NIPS-2005-5095.pdf %*Separation of Music Signals by Harmonic Structure Modeling %@Yun-gang Zhang,Chang-shui Zhang %t2005 %cNIPS %f/NIPS/NIPS-2005-5096.pdf %*A Domain Decomposition Method for Fast Manifold Learning %@Zhenyue Zhang,Hongyuan Zha %t2005 %cNIPS %f/NIPS/NIPS-2005-5097.pdf %*A Hierarchical Compositional System for Rapid Object Detection %@Long Zhu,Alan L. Yuille %t2005 %cNIPS %f/NIPS/NIPS-2005-5098.pdf %*Cyclic Equilibria in Markov Games %@Martin Zinkevich,Amy Greenwald,Michael L. Littman %t2005 %cNIPS %f/NIPS/NIPS-2005-5099.pdf %*On the Convergence of Eigenspaces in Kernel Principal Component Analysis %@Laurent Zwald,Gilles Blanchard %t2005 %cNIPS %f/NIPS/NIPS-2005-5100.pdf %*Learning first-order Markov models for control %@Pieter Abbeel,Andrew Y. Ng %t2004 %cNIPS %f/NIPS/NIPS-2004-5101.pdf %*A Large Deviation Bound for the Area Under the ROC Curve %@Shivani Agarwal,Thore Graepel,Ralf Herbrich,Dan Roth %t2004 %cNIPS %f/NIPS/NIPS-2004-5102.pdf %*Learning Preferences for Multiclass Problems %@Fabio Aiolli,Alessandro Sperduti %t2004 %cNIPS %f/NIPS/NIPS-2004-5103.pdf %*Harmonising Chorales by Probabilistic Inference %@Moray Allan,Christopher Williams %t2004 %cNIPS %f/NIPS/NIPS-2004-5104.pdf %*The Correlated Correspondence Algorithm for Unsupervised Registration of Nonrigid Surfaces %@Dragomir Anguelov,Praveen Srinivasan,Hoi-cheung Pang,Daphne Koller,Sebastian Thrun,James Davis %t2004 %cNIPS %f/NIPS/NIPS-2004-5105.pdf %*A Direct Formulation for Sparse PCA Using Semidefinite Programming %@Alexandre D'aspremont,Laurent E. Ghaoui,Michael I. Jordan,Gert R. Lanckriet %t2004 %cNIPS %f/NIPS/NIPS-2004-5106.pdf %*Comparing Beliefs, Surveys, and Random Walks %@Erik Aurell,Uri Gordon,Scott Kirkpatrick %t2004 %cNIPS %f/NIPS/NIPS-2004-5107.pdf %*The power of feature clustering: An application to object detection %@Shai Avidan,Moshe Butman %t2004 %cNIPS %f/NIPS/NIPS-2004-5108.pdf %*Blind One-microphone Speech Separation: A Spectral Learning Approach %@Francis R. Bach,Michael I. Jordan %t2004 %cNIPS %f/NIPS/NIPS-2004-5109.pdf %*Computing regularization paths for learning multiple kernels %@Francis R. Bach,Romain Thibaux,Michael I. Jordan %t2004 %cNIPS %f/NIPS/NIPS-2004-5110.pdf %*Breaking SVM Complexity with Cross-Training %@Léon Bottou,Jason Weston,Gökhan H. Bakir %t2004 %cNIPS %f/NIPS/NIPS-2004-5111.pdf %*Co-Training and Expansion: Towards Bridging Theory and Practice %@Maria-florina Balcan,Avrim Blum,Ke Yang %t2004 %cNIPS %f/NIPS/NIPS-2004-5112.pdf %*Large-Scale Prediction of Disulphide Bond Connectivity %@Jianlin Cheng,Alessandro Vullo,Pierre F. Baldi %t2004 %cNIPS %f/NIPS/NIPS-2004-5113.pdf %*Spike Sorting: Bayesian Clustering of Non-Stationary Data %@Aharon Bar-hillel,Adam Spiro,Eran Stark %t2004 %cNIPS %f/NIPS/NIPS-2004-5114.pdf %*Exponentiated Gradient Algorithms for Large-margin Structured Classification %@Peter L. Bartlett,Michael Collins,Ben Taskar,David A. McAllester %t2004 %cNIPS %f/NIPS/NIPS-2004-5115.pdf %*Maximising Sensitivity in a Spiking Network %@Anthony J. Bell,Lucas C. Parra %t2004 %cNIPS %f/NIPS/NIPS-2004-5116.pdf %*Non-Local Manifold Tangent Learning %@Yoshua Bengio,Martin Monperrus %t2004 %cNIPS %f/NIPS/NIPS-2004-5117.pdf %*Who's In the Picture %@Tamara L. Berg,Alexander C. Berg,Jaety Edwards,David A. Forsyth %t2004 %cNIPS %f/NIPS/NIPS-2004-5118.pdf %*At the Edge of Chaos: Real-time Computations and Self-Organized Criticality in Recurrent Neural Networks %@Nils Bertschinger,Thomas Natschläger,Robert A. Legenstein %t2004 %cNIPS %f/NIPS/NIPS-2004-5119.pdf %*A Second Order Cone programming Formulation for Classifying Missing Data %@Chiranjib Bhattacharyya,Pannagadatta K. Shivaswamy,Alex J. Smola %t2004 %cNIPS %f/NIPS/NIPS-2004-5120.pdf %*Support Vector Classification with Input Data Uncertainty %@Jinbo Bi,Tong Zhang %t2004 %cNIPS %f/NIPS/NIPS-2004-5121.pdf %*Responding to Modalities with Different Latencies %@Fredrik Bissmarck,Hiroyuki Nakahara,Kenji Doya,Okihide Hikosaka %t2004 %cNIPS %f/NIPS/NIPS-2004-5122.pdf %*Nonlinear Blind Source Separation by Integrating Independent Component Analysis and Slow Feature Analysis %@Tobias Blaschke,Laurenz Wiskott %t2004 %cNIPS %f/NIPS/NIPS-2004-5123.pdf %*Hierarchical Distributed Representations for Statistical Language Modeling %@John Blitzer,Fernando Pereira,Kilian Q. Weinberger,Lawrence K. Saul %t2004 %cNIPS %f/NIPS/NIPS-2004-5124.pdf %*Markov Networks for Detecting Overalpping Elements in Sequence Data %@Mark Craven,Joseph Bockhorst %t2004 %cNIPS %f/NIPS/NIPS-2004-5125.pdf %*Reducing Spike Train Variability: A Computational Theory Of Spike-Timing Dependent Plasticity %@Sander M. Bohte,Michael C. Mozer %t2004 %cNIPS %f/NIPS/NIPS-2004-5126.pdf %*Dependent Gaussian Processes %@Phillip Boyle,Marcus Frean %t2004 %cNIPS %f/NIPS/NIPS-2004-5127.pdf %*Proximity Graphs for Clustering and Manifold Learning %@Richard S. Zemel,Miguel Á. Carreira-Perpiñán %t2004 %cNIPS %f/NIPS/NIPS-2004-5128.pdf %*Incremental Algorithms for Hierarchical Classification %@Nicolò Cesa-bianchi,Claudio Gentile,Andrea Tironi,Luca Zaniboni %t2004 %cNIPS %f/NIPS/NIPS-2004-5129.pdf %*Worst-Case Analysis of Selective Sampling for Linear-Threshold Algorithms %@Nicolò Cesa-bianchi,Claudio Gentile,Luca Zaniboni %t2004 %cNIPS %f/NIPS/NIPS-2004-5130.pdf %*Sub-Microwatt Analog VLSI Support Vector Machine for Pattern Classification and Sequence Estimation %@Shantanu Chakrabartty,Gert Cauwenberghs %t2004 %cNIPS %f/NIPS/NIPS-2004-5131.pdf %*A Machine Learning Approach to Conjoint Analysis %@Olivier Chapelle,Zaïd Harchaoui %t2004 %cNIPS %f/NIPS/NIPS-2004-5132.pdf %*Using Machine Learning to Break Visual Human Interaction Proofs (HIPs) %@Kumar Chellapilla,Patrice Y. Simard %t2004 %cNIPS %f/NIPS/NIPS-2004-5133.pdf %*Hierarchical Eigensolver for Transition Matrices in Spectral Methods %@Chakra Chennubhotla,Allan D. Jepson %t2004 %cNIPS %f/NIPS/NIPS-2004-5134.pdf %*Modeling Conversational Dynamics as a Mixed-Memory Markov Process %@Tanzeem Choudhury,Sumit Basu %t2004 %cNIPS %f/NIPS/NIPS-2004-5135.pdf %*Theories of Access Consciousness %@Michael D. Colagrosso,Michael C. Mozer %t2004 %cNIPS %f/NIPS/NIPS-2004-5136.pdf %*Distributed Information Regularization on Graphs %@Adrian Corduneanu,Tommi S. Jaakkola %t2004 %cNIPS %f/NIPS/NIPS-2004-5137.pdf %*Confidence Intervals for the Area Under the ROC Curve %@Corinna Cortes,Mehryar Mohri %t2004 %cNIPS %f/NIPS/NIPS-2004-5138.pdf %*Similarity and Discrimination in Classical Conditioning: A Latent Variable Account %@Aaron C. Courville,Nathaniel D. Daw,David S. Touretzky %t2004 %cNIPS %f/NIPS/NIPS-2004-5139.pdf %*Trait Selection for Assessing Beef Meat Quality Using Non-linear SVM %@Juan Coz,Gustavo F. Bayón,Jorge Díez,Oscar Luaces,Antonio Bahamonde,Carlos Sañudo %t2004 %cNIPS %f/NIPS/NIPS-2004-5140.pdf %*Semigroup Kernels on Finite Sets %@Marco Cuturi,Jean-philippe Vert %t2004 %cNIPS %f/NIPS/NIPS-2004-5141.pdf %*The Power of Selective Memory: Self-Bounded Learning of Prediction Suffix Trees %@Ofer Dekel,Shai Shalev-shwartz,Yoram Singer %t2004 %cNIPS %f/NIPS/NIPS-2004-5142.pdf %*Triangle Fixing Algorithms for the Metric Nearness Problem %@Suvrit Sra,Joel Tropp,Inderjit S. Dhillon %t2004 %cNIPS %f/NIPS/NIPS-2004-5143.pdf %*Pictorial Structures for Molecular Modeling: Interpreting Density Maps %@Frank Dimaio,George Phillips,Jude W. Shavlik %t2004 %cNIPS %f/NIPS/NIPS-2004-5144.pdf %*Sparse Coding of Natural Images Using an Overcomplete Set of Limited Capacity Units %@Eizaburo Doi,Michael S. Lewicki %t2004 %cNIPS %f/NIPS/NIPS-2004-5145.pdf %*Making Latin Manuscripts Searchable using gHMM's %@Jaety Edwards,Yee W. Teh,Roger Bock,Michael Maire,Grace Vesom,David A. Forsyth %t2004 %cNIPS %f/NIPS/NIPS-2004-5146.pdf %*Seeing through water %@Alexei Efros,Volkan Isler,Jianbo Shi,Mirkó Visontai %t2004 %cNIPS %f/NIPS/NIPS-2004-5147.pdf %*Experts in a Markov Decision Process %@Eyal Even-dar,Sham M. Kakade,Yishay Mansour %t2004 %cNIPS %f/NIPS/NIPS-2004-5148.pdf %*Exploration-Exploitation Tradeoffs for Experts Algorithms in Reactive Environments %@Daniela D. Farias,Nimrod Megiddo %t2004 %cNIPS %f/NIPS/NIPS-2004-5149.pdf %*A Cost-Shaping LP for Bellman Error Minimization with Performance Guarantees %@Daniela D. Farias,Benjamin V. Roy %t2004 %cNIPS %f/NIPS/NIPS-2004-5150.pdf %*Learning Hyper-Features for Visual Identification %@Andras D. Ferencz,Erik G. Learned-miller,Jitendra Malik %t2004 %cNIPS %f/NIPS/NIPS-2004-5151.pdf %*Sampling Methods for Unsupervised Learning %@Rob Fergus,Andrew Zisserman,Pietro Perona %t2004 %cNIPS %f/NIPS/NIPS-2004-5152.pdf %*On-Chip Compensation of Device-Mismatch Effects in Analog VLSI Neural Networks %@Miguel Figueroa,Seth Bridges,Chris Diorio %t2004 %cNIPS %f/NIPS/NIPS-2004-5153.pdf %*A Hidden Markov Model for de Novo Peptide Sequencing %@Bernd Fischer,Volker Roth,Jonas Grossmann,Sacha Baginsky,Wilhelm Gruissem,Franz Roos,Peter Widmayer,Joachim M. Buhmann %t2004 %cNIPS %f/NIPS/NIPS-2004-5154.pdf %*Implicit Wiener Series for Higher-Order Image Analysis %@Matthias O. Franz,Bernhard Schölkopf %t2004 %cNIPS %f/NIPS/NIPS-2004-5155.pdf %*Joint Probabilistic Curve Clustering and Alignment %@Scott J. Gaffney,Padhraic Smyth %t2004 %cNIPS %f/NIPS/NIPS-2004-5156.pdf %*Discriminant Saliency for Visual Recognition from Cluttered Scenes %@Dashan Gao,Nuno Vasconcelos %t2004 %cNIPS %f/NIPS/NIPS-2004-5157.pdf %*Instance-Based Relevance Feedback for Image Retrieval %@Giorgio Gia\-cin\-to,Fabio Roli %t2004 %cNIPS %f/NIPS/NIPS-2004-5158.pdf %*Euclidean Embedding of Co-Occurrence Data %@Amir Globerson,Gal Chechik,Fernando Pereira,Naftali Tishby %t2004 %cNIPS %f/NIPS/NIPS-2004-5159.pdf %*Hierarchical Clustering of a Mixture Model %@Jacob Goldberger,Sam T. Roweis %t2004 %cNIPS %f/NIPS/NIPS-2004-5160.pdf %*Neighbourhood Components Analysis %@Jacob Goldberger,Geoffrey E. Hinton,Sam T. Roweis,Ruslan R. Salakhutdinov %t2004 %cNIPS %f/NIPS/NIPS-2004-5161.pdf %*Parallel Support Vector Machines: The Cascade SVM %@Hans P. Graf,Eric Cosatto,Léon Bottou,Igor Dourdanovic,Vladimir Vapnik %t2004 %cNIPS %f/NIPS/NIPS-2004-5162.pdf %*Semi-supervised Learning by Entropy Minimization %@Yves Grandvalet,Yoshua Bengio %t2004 %cNIPS %f/NIPS/NIPS-2004-5163.pdf %*Integrating Topics and Syntax %@Thomas L. Griffiths,Mark Steyvers,David M. Blei,Joshua B. Tenenbaum %t2004 %cNIPS %f/NIPS/NIPS-2004-5164.pdf %*Result Analysis of the NIPS 2003 Feature Selection Challenge %@Isabelle Guyon,Steve Gunn,Asa Ben-Hur,Gideon Dror %t2004 %cNIPS %f/NIPS/NIPS-2004-5165.pdf %*Theory of localized synfire chain: characteristic propagation speed of stable spike pattern %@Kosuke Hamaguchi,Masato Okada,Kazuyuki Aihara %t2004 %cNIPS %f/NIPS/NIPS-2004-5166.pdf %*The Entire Regularization Path for the Support Vector Machine %@Saharon Rosset,Robert Tibshirani,Ji Zhu,Trevor J. Hastie %t2004 %cNIPS %f/NIPS/NIPS-2004-5167.pdf %*An Auditory Paradigm for Brain-Computer Interfaces %@N. J. Hill,Thomas N. Lal,Karin Bierig,Niels Birbaumer,Bernhard Schölkopf %t2004 %cNIPS %f/NIPS/NIPS-2004-5168.pdf %*The Cerebellum Chip: an Analog VLSI Implementation of a Cerebellar Model of Classical Conditioning %@Constanze Hofstoetter,Manuel Gil,Kynan Eng,Giacomo Indiveri,Matti Mintz,Jörg Kramer,Paul F. Verschure %t2004 %cNIPS %f/NIPS/NIPS-2004-5169.pdf %*Schema Learning: Experience-Based Construction of Predictive Action Models %@Michael P. Holmes,Charles Jr. %t2004 %cNIPS %f/NIPS/NIPS-2004-5170.pdf %*Unsupervised Variational Bayesian Learning of Nonlinear Models %@Antti Honkela,Harri Valpola %t2004 %cNIPS %f/NIPS/NIPS-2004-5171.pdf %*A Generalized Bradley-Terry Model: From Group Competition to Individual Skill %@Tzu-kuo Huang,Chih-jen Lin,Ruby C. Weng %t2004 %cNIPS %f/NIPS/NIPS-2004-5172.pdf %*Message Errors in Belief Propagation %@Alexander T. Ihler,John W. Fisher,Alan S. Willsky %t2004 %cNIPS %f/NIPS/NIPS-2004-5173.pdf %*Parametric Embedding for Class Visualization %@Tomoharu Iwata,Kazumi Saito,Naonori Ueda,Sean Stromsten,Thomas L. Griffiths,Joshua B. Tenenbaum %t2004 %cNIPS %f/NIPS/NIPS-2004-5174.pdf %*The Laplacian PDF Distance: A Cost Function for Clustering in a Kernel Feature Space %@Robert Jenssen,Deniz Erdogmus,Jose Principe,Torbjørn Eltoft %t2004 %cNIPS %f/NIPS/NIPS-2004-5175.x-bibtex %*Economic Properties of Social Networks %@Sham M. Kakade,Michael Kearns,Luis E. Ortiz,Robin Pemantle,Siddharth Suri %t2004 %cNIPS %f/NIPS/NIPS-2004-5176.pdf %*Online Bounds for Bayesian Algorithms %@Sham M. Kakade,Andrew Y. Ng %t2004 %cNIPS %f/NIPS/NIPS-2004-5177.pdf %*Maximal Margin Labeling for Multi-Topic Text Categorization %@Hideto Kazawa,Tomonori Izumitani,Hirotoshi Taira,Eisaku Maeda %t2004 %cNIPS %f/NIPS/NIPS-2004-5178.pdf %*Boosting on Manifolds: Adaptive Regularization of Base Classifiers %@Ligen Wang,Balázs Kégl %t2004 %cNIPS %f/NIPS/NIPS-2004-5179.pdf %*Face Detection --- Efficient and Rank Deficient %@Wolf Kienzle,Matthias O. Franz,Bernhard Schölkopf,Gökhan H. Bakir %t2004 %cNIPS %f/NIPS/NIPS-2004-5180.pdf %*Neural Network Computation by In Vitro Transcriptional Circuits %@Jongmin Kim,John Hopfield,Erik Winfree %t2004 %cNIPS %f/NIPS/NIPS-2004-5181.pdf %*Synchronization of neural networks by mutual learning and its application to cryptography %@Einat Klein,Rachel Mislovaty,Ido Kanter,Andreas Ruttor,Wolfgang Kinzel %t2004 %cNIPS %f/NIPS/NIPS-2004-5182.pdf %*Optimal Aggregation of Classifiers and Boosting Maps in Functional Magnetic Resonance Imaging %@Vladimir Koltchinskii,Manel Martínez-ramón,Stefan Posse %t2004 %cNIPS %f/NIPS/NIPS-2004-5183.pdf %*Newscast EM %@Wojtek Kowalczyk,Nikos A. Vlassis %t2004 %cNIPS %f/NIPS/NIPS-2004-5184.pdf %*On Semi-Supervised Classification %@Balaji Krishnapuram,David Williams,Ya Xue,Lawrence Carin,Mário Figueiredo,Alexander J. Hartemink %t2004 %cNIPS %f/NIPS/NIPS-2004-5185.pdf %*An Application of Boosting to Graph Classification %@Taku Kudo,Eisaku Maeda,Yuji Matsumoto %t2004 %cNIPS %f/NIPS/NIPS-2004-5186.pdf %*Methods Towards Invasive Human Brain Computer Interfaces %@Thomas N. Lal,Thilo Hinterberger,Guido Widman,Michael Schröder,N. J. Hill,Wolfgang Rosenstiel,Christian E. Elger,Niels Birbaumer,Bernhard Schölkopf %t2004 %cNIPS %f/NIPS/NIPS-2004-5187.pdf %*Beat Tracking the Graphical Model Way %@Dustin Lang,Nando D. Freitas %t2004 %cNIPS %f/NIPS/NIPS-2004-5188.pdf %*Semi-supervised Learning via Gaussian Processes %@Neil D. Lawrence,Michael I. Jordan %t2004 %cNIPS %f/NIPS/NIPS-2004-5189.pdf %*Joint MRI Bias Removal Using Entropy Minimization Across Images %@Erik G. Learned-miller,Parvez Ahammad %t2004 %cNIPS %f/NIPS/NIPS-2004-5190.pdf %*Rate- and Phase-coded Autoassociative Memory %@Máté Lengyel,Peter Dayan %t2004 %cNIPS %f/NIPS/NIPS-2004-5191.pdf %*Maximum Likelihood Estimation of Intrinsic Dimension %@Elizaveta Levina,Peter J. Bickel %t2004 %cNIPS %f/NIPS/NIPS-2004-5192.pdf %*Planning for Markov Decision Processes with Sparse Stochasticity %@Maxim Likhachev,Sebastian Thrun,Geoffrey J. Gordon %t2004 %cNIPS %f/NIPS/NIPS-2004-5193.pdf %*Incremental Learning for Visual Tracking %@Jongwoo Lim,David A. Ross,Ruei-sung Lin,Ming-Hsuan Yang %t2004 %cNIPS %f/NIPS/NIPS-2004-5194.pdf %*Adaptive Discriminative Generative Model and Its Applications %@Ruei-sung Lin,David A. Ross,Jongwoo Lim,Ming-Hsuan Yang %t2004 %cNIPS %f/NIPS/NIPS-2004-5195.pdf %*Bayesian Regularization and Nonnegative Deconvolution for Time Delay Estimation %@Yuanqing Lin,Daniel D. Lee %t2004 %cNIPS %f/NIPS/NIPS-2004-5196.pdf %*Multiple Alignment of Continuous Time Series %@Jennifer Listgarten,Radford M. Neal,Sam T. Roweis,Andrew Emili %t2004 %cNIPS %f/NIPS/NIPS-2004-5197.pdf %*An Investigation of Practical Approximate Nearest Neighbor Algorithms %@Ting Liu,Andrew W. Moore,Ke Yang,Alexander G. Gray %t2004 %cNIPS %f/NIPS/NIPS-2004-5198.pdf %*Mistake Bounds for Maximum Entropy Discrimination %@Philip M. Long,Xinyu Wu %t2004 %cNIPS %f/NIPS/NIPS-2004-5199.pdf %*A Three Tiered Approach for Articulated Object Action Modeling and Recognition %@Le Lu,Gregory D. Hager,Laurent Younes %t2004 %cNIPS %f/NIPS/NIPS-2004-5200.pdf %*Semi-supervised Learning with Penalized Probabilistic Clustering %@Zhengdong Lu,Todd K. Leen %t2004 %cNIPS %f/NIPS/NIPS-2004-5201.pdf %*Limits of Spectral Clustering %@Ulrike V. Luxburg,Olivier Bousquet,Mikhail Belkin %t2004 %cNIPS %f/NIPS/NIPS-2004-5202.pdf %*Methods for Estimating the Computational Power and Generalization Capability of Neural Microcircuits %@Wolfgang Maass,Robert A. Legenstein,Nils Bertschinger %t2004 %cNIPS %f/NIPS/NIPS-2004-5203.pdf %*Co-Validation: Using Model Disagreement on Unlabeled Data to Validate Classification Algorithms %@Omid Madani,David M. Pennock,Gary W. Flake %t2004 %cNIPS %f/NIPS/NIPS-2004-5204.pdf %*PAC-Bayes Learning of Conjunctions and Classification of Gene-Expression Data %@Mario Marchand,Mohak Shah %t2004 %cNIPS %f/NIPS/NIPS-2004-5205.pdf %*Joint Tracking of Pose, Expression, and Texture using Conditionally Gaussian Filters %@Tim K. Marks,J. C. Roddey,Javier R. Movellan,John R. Hershey %t2004 %cNIPS %f/NIPS/NIPS-2004-5206.pdf %*Linear Multilayer Independent Component Analysis for Large Natural Scenes %@Yoshitatsu Matsuda,Kazunori Yamaguchi %t2004 %cNIPS %f/NIPS/NIPS-2004-5207.pdf %*Conditional Models of Identity Uncertainty with Application to Noun Coreference %@Andrew McCallum,Ben Wellner %t2004 %cNIPS %f/NIPS/NIPS-2004-5208.pdf %*Multiple Relational Embedding %@Roland Memisevic,Geoffrey E. Hinton %t2004 %cNIPS %f/NIPS/NIPS-2004-5209.pdf %*Kernels for Multi--task Learning %@Charles A. Micchelli,Massimiliano Pontil %t2004 %cNIPS %f/NIPS/NIPS-2004-5210.pdf %*A Topographic Support Vector Machine: Classification Using Local Label Configurations %@Johannes Mohr,Klaus Obermayer %t2004 %cNIPS %f/NIPS/NIPS-2004-5211.pdf %*Optimal Information Decoding from Neuronal Populations with Specific Stimulus Selectivity %@Marcelo A. Montemurro,Stefano Panzeri %t2004 %cNIPS %f/NIPS/NIPS-2004-5212.pdf %*Validity Estimates for Loopy Belief Propagation on Binary Real-world Networks %@Joris M. Mooij,Hilbert J. Kappen %t2004 %cNIPS %f/NIPS/NIPS-2004-5213.pdf %*Common-Frame Model for Object Recognition %@Pierre Moreels,Pietro Perona %t2004 %cNIPS %f/NIPS/NIPS-2004-5214.pdf %*Optimal sub-graphical models %@Mukund Narasimhan,Jeff A. Bilmes %t2004 %cNIPS %f/NIPS/NIPS-2004-5215.pdf %*Detecting Significant Multidimensional Spatial Clusters %@Daniel B. Neill,Andrew W. Moore,Francisco Pereira,Tom M. Mitchell %t2004 %cNIPS %f/NIPS/NIPS-2004-5216.pdf %*Stable adaptive control with online learning %@H. J. Kim,Andrew Y. Ng %t2004 %cNIPS %f/NIPS/NIPS-2004-5217.pdf %*A Harmonic Excitation State-Space Approach to Blind Separation of Speech %@Rasmus K. Olsson,Lars K. Hansen %t2004 %cNIPS %f/NIPS/NIPS-2004-5218.pdf %*Expectation Consistent Free Energies for Approximate Inference %@Manfred Opper,Ole Winther %t2004 %cNIPS %f/NIPS/NIPS-2004-5219.pdf %*Discrete profile alignment via constrained information bottleneck %@Sean O'rourke,Gal Chechik,Robin Friedman,Eleazar Eskin %t2004 %cNIPS %f/NIPS/NIPS-2004-5220.pdf %*Synergistic Face Detection and Pose Estimation with Energy-Based Models %@Margarita Osadchy,Matthew L. Miller,Yann L. Cun %t2004 %cNIPS %f/NIPS/NIPS-2004-5221.pdf %*Modeling Nonlinear Dependencies in Natural Images using Mixture of Laplacian Distribution %@Hyun J. Park,Te W. Lee %t2004 %cNIPS %f/NIPS/NIPS-2004-5222.pdf %*Approximately Efficient Online Mechanism Design %@David C. Parkes,Dimah Yanovsky,Satinder P. Singh %t2004 %cNIPS %f/NIPS/NIPS-2004-5223.pdf %*Efficient Out-of-Sample Extension of Dominant-Set Clusters %@Massimiliano Pavan,Marcello Pelillo %t2004 %cNIPS %f/NIPS/NIPS-2004-5224.pdf %*A Feature Selection Algorithm Based on the Global Minimization of a Generalization Error Bound %@Dori Peleg,Ron Meir %t2004 %cNIPS %f/NIPS/NIPS-2004-5225.pdf %*Active Learning for Anomaly and Rare-Category Detection %@Dan Pelleg,Andrew W. Moore %t2004 %cNIPS %f/NIPS/NIPS-2004-5226.pdf %*VDCBPI: an Approximate Scalable Algorithm for Large POMDPs %@Pascal Poupart,Craig Boutilier %t2004 %cNIPS %f/NIPS/NIPS-2004-5227.pdf %*New Criteria and a New Algorithm for Learning in Multi-Agent Systems %@Rob Powers,Yoav Shoham %t2004 %cNIPS %f/NIPS/NIPS-2004-5228.pdf %*Conditional Random Fields for Object Recognition %@Ariadna Quattoni,Michael Collins,Trevor Darrell %t2004 %cNIPS %f/NIPS/NIPS-2004-5229.pdf %*Chemosensory Processing in a Spiking Model of the Olfactory Bulb: Chemotopic Convergence and Center Surround Inhibition %@Baranidharan Raman,Ricardo Gutierrez-osuna %t2004 %cNIPS %f/NIPS/NIPS-2004-5230.pdf %*An Information Maximization Model of Eye Movements %@Laura W. Renninger,James M. Coughlan,Preeti Verghese,Jitendra Malik %t2004 %cNIPS %f/NIPS/NIPS-2004-5231.pdf %*Brain Inspired Reinforcement Learning %@Françcois Rivest,Yoshua Bengio,John Kalaska %t2004 %cNIPS %f/NIPS/NIPS-2004-5232.pdf %*Coarticulation in Markov Decision Processes %@Khashayar Rohanimanesh,Robert Platt,Sridhar Mahadevan,Roderic Grupen %t2004 %cNIPS %f/NIPS/NIPS-2004-5233.pdf %*Learning, Regularization and Ill-Posed Inverse Problems %@Lorenzo Rosasco,Andrea Caponnetto,Ernesto D. Vito,Francesca Odone,Umberto D. Giovannini %t2004 %cNIPS %f/NIPS/NIPS-2004-5234.pdf %*A Method for Inferring Label Sampling Mechanisms in Semi-Supervised Learning %@Saharon Rosset,Ji Zhu,Hui Zou,Trevor J. Hastie %t2004 %cNIPS %f/NIPS/NIPS-2004-5235.pdf %*Semi-parametric Exponential Family PCA %@Sajama Sajama,Alon Orlitsky %t2004 %cNIPS %f/NIPS/NIPS-2004-5236.pdf %*Semi-Markov Conditional Random Fields for Information Extraction %@Sunita Sarawagi,William W. Cohen %t2004 %cNIPS %f/NIPS/NIPS-2004-5237.pdf %*Kernel Methods for Implicit Surface Modeling %@Joachim Giesen,Simon Spalinger,Bernhard Schölkopf %t2004 %cNIPS %f/NIPS/NIPS-2004-5238.pdf %*Edge of Chaos Computation in Mixed-Mode VLSI - A Hard Liquid %@Felix Schürmann,Karlheinz Meier,Johannes Schemmel %t2004 %cNIPS %f/NIPS/NIPS-2004-5239.pdf %*Learning Gaussian Process Kernels via Hierarchical Bayes %@Anton Schwaighofer,Volker Tresp,Kai Yu %t2004 %cNIPS %f/NIPS/NIPS-2004-5240.pdf %*Assignment of Multiplicative Mixtures in Natural Images %@Odelia Schwartz,Terrence J. Sejnowski,Peter Dayan %t2004 %cNIPS %f/NIPS/NIPS-2004-5241.pdf %*On the Adaptive Properties of Decision Trees %@Clayton Scott,Robert Nowak %t2004 %cNIPS %f/NIPS/NIPS-2004-5242.pdf %*Real-Time Pitch Determination of One or More Voices by Nonnegative Matrix Factorization %@Fei Sha,Lawrence K. Saul %t2004 %cNIPS %f/NIPS/NIPS-2004-5243.pdf %*Probabilistic Inference of Alternative Splicing Events in Microarray Data %@Ofer Shai,Brendan J. Frey,Quaid D. Morris,Qun Pan,Christine Misquitta,Benjamin J. Blencowe %t2004 %cNIPS %f/NIPS/NIPS-2004-5244.pdf %*Resolving Perceptual Aliasing In The Presence Of Noisy Sensors %@Guy Shani,Ronen I. Brafman %t2004 %cNIPS %f/NIPS/NIPS-2004-5245.pdf %*Algebraic Set Kernels with Application to Inference Over Local Image Representations %@Amnon Shashua,Tamir Hazan %t2004 %cNIPS %f/NIPS/NIPS-2004-5246.pdf %*Dynamic Bayesian Networks for Brain-Computer Interfaces %@Pradeep Shenoy,Rajesh P. Rao %t2004 %cNIPS %f/NIPS/NIPS-2004-5247.pdf %*A Temporal Kernel-Based Model for Tracking Hand Movements from Neural Activities %@Lavi Shpigelman,Koby Crammer,Rony Paz,Eilon Vaadia,Yoram Singer %t2004 %cNIPS %f/NIPS/NIPS-2004-5248.pdf %*Intrinsically Motivated Reinforcement Learning %@Nuttapong Chentanez,Andrew G. Barto,Satinder P. Singh %t2004 %cNIPS %f/NIPS/NIPS-2004-5249.pdf %*Learning Efficient Auditory Codes Using Spikes Predicts Cochlear Filters %@Evan C. Smith,Michael S. Lewicki %t2004 %cNIPS %f/NIPS/NIPS-2004-5250.pdf %*Learning Syntactic Patterns for Automatic Hypernym Discovery %@Rion Snow,Daniel Jurafsky,Andrew Y. Ng %t2004 %cNIPS %f/NIPS/NIPS-2004-5251.pdf %*Surface Reconstruction using Learned Shape Models %@Jan E. Solem,Fredrik Kahl %t2004 %cNIPS %f/NIPS/NIPS-2004-5252.pdf %*Using the Equivalent Kernel to Understand Gaussian Process Regression %@Peter Sollich,Christopher Williams %t2004 %cNIPS %f/NIPS/NIPS-2004-5253.pdf %*Generalization Error Bounds for Collaborative Prediction with Low-Rank Matrices %@Nathan Srebro,Noga Alon,Tommi S. Jaakkola %t2004 %cNIPS %f/NIPS/NIPS-2004-5254.pdf %*Maximum-Margin Matrix Factorization %@Nathan Srebro,Jason Rennie,Tommi S. Jaakkola %t2004 %cNIPS %f/NIPS/NIPS-2004-5255.pdf %*Density Level Detection is Classification %@Ingo Steinwart,Don Hush,Clint Scovel %t2004 %cNIPS %f/NIPS/NIPS-2004-5256.pdf %*Fast Rates to Bayes for Kernel Machines %@Ingo Steinwart,Clint Scovel %t2004 %cNIPS %f/NIPS/NIPS-2004-5257.pdf %*Modelling Uncertainty in the Game of Go %@David H. Stern,Thore Graepel,David MacKay %t2004 %cNIPS %f/NIPS/NIPS-2004-5258.pdf %*Constraining a Bayesian Model of Human Visual Speed Perception %@Alan Stocker,Eero P. Simoncelli %t2004 %cNIPS %f/NIPS/NIPS-2004-5259.pdf %*Distributed Occlusion Reasoning for Tracking with Nonparametric Belief Propagation %@Erik B. Sudderth,Michael I. Mandel,William T. Freeman,Alan S. Willsky %t2004 %cNIPS %f/NIPS/NIPS-2004-5260.pdf %*Temporal-Difference Networks %@Richard S. Sutton,Brian Tanner %t2004 %cNIPS %f/NIPS/NIPS-2004-5261.pdf %*Sharing Clusters among Related Groups: Hierarchical Dirichlet Processes %@Yee W. Teh,Michael I. Jordan,Matthew J. Beal,David M. Blei %t2004 %cNIPS %f/NIPS/NIPS-2004-5262.pdf %*Heuristics for Ordering Cue Search in Decision Making %@Peter M. Todd,Anja Dieckmann %t2004 %cNIPS %f/NIPS/NIPS-2004-5263.pdf %*Contextual Models for Object Detection Using Boosted Random Fields %@Antonio Torralba,Kevin P. Murphy,William T. Freeman %t2004 %cNIPS %f/NIPS/NIPS-2004-5264.pdf %*Spike-timing Dependent Plasticity and Mutual Information Maximization for a Spiking Neuron Model %@Taro Toyoizumi,Jean-pascal Pfister,Kazuyuki Aihara,Wulfram Gerstner %t2004 %cNIPS %f/NIPS/NIPS-2004-5265.pdf %*Matrix Exponential Gradient Updates for On-line Learning and Bregman Projection %@Koji Tsuda,Gunnar Rätsch,Manfred K. Warmuth %t2004 %cNIPS %f/NIPS/NIPS-2004-5266.pdf %*Supervised Graph Inference %@Jean-philippe Vert,Yoshihiro Yamanishi %t2004 %cNIPS %f/NIPS/NIPS-2004-5267.pdf %*Binet-Cauchy Kernels %@Alex J. Smola,S.v.n. Vishwanathan %t2004 %cNIPS %f/NIPS/NIPS-2004-5268.pdf %*Instance-Specific Bayesian Model Averaging for Classification %@Shyam Visweswaran,Gregory F. Cooper %t2004 %cNIPS %f/NIPS/NIPS-2004-5269.pdf %*Saliency-Driven Image Acuity Modulation on a Reconfigurable Array of Spiking Silicon Neurons %@R. J. Vogelstein,Udayan Mallik,Eugenio Culurciello,Gert Cauwenberghs,Ralph Etienne-Cummings %t2004 %cNIPS %f/NIPS/NIPS-2004-5270.pdf %*Identifying Protein-Protein Interaction Sites on a Genome-Wide Scale %@Haidong Wang,Eran Segal,Asa Ben-Hur,Daphne Koller,Douglas L. Brutlag %t2004 %cNIPS %f/NIPS/NIPS-2004-5271.pdf %*Adaptive Manifold Learning %@Jing Wang,Zhenyue Zhang,Hongyuan Zha %t2004 %cNIPS %f/NIPS/NIPS-2004-5272.pdf %*Exponential Family Harmoniums with an Application to Information Retrieval %@Max Welling,Michal Rosen-zvi,Geoffrey E. Hinton %t2004 %cNIPS %f/NIPS/NIPS-2004-5273.pdf %*Machine Learning Applied to Perception: Decision Images for Gender Classification %@Felix A. Wichmann,Arnulf B. Graf,Heinrich H. Bülthoff,Eero P. Simoncelli,Bernhard Schölkopf %t2004 %cNIPS %f/NIPS/NIPS-2004-5274.pdf %*The Variational Ising Classifier (VIC) Algorithm for Coherently Contaminated Data %@Oliver Williams,Andrew Blake,Roberto Cipolla %t2004 %cNIPS %f/NIPS/NIPS-2004-5275.pdf %*Generative Affine Localisation and Tracking %@John Winn,Andrew Blake %t2004 %cNIPS %f/NIPS/NIPS-2004-5276.pdf %*ℓ₀-norm Minimization for Basis Selection %@David P. Wipf,Bhaskar D. Rao %t2004 %cNIPS %f/NIPS/NIPS-2004-5277.pdf %*Multi-agent Cooperation in Diverse Population Games %@K. Wong,S. W. Lim,Z. Gao %t2004 %cNIPS %f/NIPS/NIPS-2004-5278.pdf %*Efficient Kernel Discriminant Analysis via QR Decomposition %@Tao Xiong,Jieping Ye,Qi Li,Ravi Janardan,Vladimir Cherkassky %t2004 %cNIPS %f/NIPS/NIPS-2004-5279.pdf %*Maximum Margin Clustering %@Linli Xu,James Neufeld,Bryce Larson,Dale Schuurmans %t2004 %cNIPS %f/NIPS/NIPS-2004-5280.pdf %*Using Random Forests in the Structured Language Model %@Peng Xu,Frederick Jelinek %t2004 %cNIPS %f/NIPS/NIPS-2004-5281.pdf %*Solitaire: Man Versus Machine %@Xiang Yan,Persi Diaconis,Paat Rusmevichientong,Benjamin V. Roy %t2004 %cNIPS %f/NIPS/NIPS-2004-5282.pdf %*Efficient Kernel Machines Using the Improved Fast Gauss Transform %@Changjiang Yang,Ramani Duraiswami,Larry S. Davis %t2004 %cNIPS %f/NIPS/NIPS-2004-5283.pdf %*Two-Dimensional Linear Discriminant Analysis %@Jieping Ye,Ravi Janardan,Qi Li %t2004 %cNIPS %f/NIPS/NIPS-2004-5284.pdf %*Inference, Attention, and Decision in a Bayesian Neural Architecture %@Angela J. Yu,Peter Dayan %t2004 %cNIPS %f/NIPS/NIPS-2004-5285.pdf %*Self-Tuning Spectral Clustering %@Lihi Zelnik-manor,Pietro Perona %t2004 %cNIPS %f/NIPS/NIPS-2004-5286.pdf %*Probabilistic Computation in Spiking Populations %@Richard S. Zemel,Rama Natarajan,Peter Dayan,Quentin J. Huys %t2004 %cNIPS %f/NIPS/NIPS-2004-5287.pdf %*A Probabilistic Model for Online Document Clustering with Application to Novelty Detection %@Jian Zhang,Zoubin Ghahramani,Yiming Yang %t2004 %cNIPS %f/NIPS/NIPS-2004-5288.pdf %*Semi-supervised Learning on Directed Graphs %@Denny Zhou,Thomas Hofmann,Bernhard Schölkopf %t2004 %cNIPS %f/NIPS/NIPS-2004-5289.pdf %*Nonparametric Transforms of Graph Kernels for Semi-Supervised Learning %@Xiaojin Zhu,Jaz Kandola,Zoubin Ghahramani,John D. Lafferty %t2004 %cNIPS %f/NIPS/NIPS-2004-5290.pdf %*Kernel Projection Machine: a New Tool for Pattern Recognition %@Laurent Zwald,Gilles Blanchard,Pascal Massart,Régis Vert %t2004 %cNIPS %f/NIPS/NIPS-2004-5291.pdf %*Efficient Multiscale Sampling from Products of Gaussian Mixtures %@Alexander T. Ihler,Erik B. Sudderth,William T. Freeman,Alan S. Willsky %t2003 %cNIPS %f/NIPS/NIPS-2003-5292.pdf %*Simplicial Mixtures of Markov Chains: Distributed Modelling of Dynamic User Profiles %@Mark Girolami,Ata Kabán %t2003 %cNIPS %f/NIPS/NIPS-2003-5293.pdf %*Hierarchical Topic Models and the Nested Chinese Restaurant Process %@Thomas L. Griffiths,Michael I. Jordan,Joshua B. Tenenbaum,David M. Blei %t2003 %cNIPS %f/NIPS/NIPS-2003-5294.pdf %*Max-Margin Markov Networks %@Ben Taskar,Carlos Guestrin,Daphne Koller %t2003 %cNIPS %f/NIPS/NIPS-2003-5295.pdf %*Invariant Pattern Recognition by Semi-Definite Programming Machines %@Thore Graepel,Ralf Herbrich %t2003 %cNIPS %f/NIPS/NIPS-2003-5296.pdf %*Learning a Distance Metric from Relative Comparisons %@Matthew Schultz,Thorsten Joachims %t2003 %cNIPS %f/NIPS/NIPS-2003-5297.pdf %*1-norm Support Vector Machines %@Ji Zhu,Saharon Rosset,Robert Tibshirani,Trevor J. Hastie %t2003 %cNIPS %f/NIPS/NIPS-2003-5298.pdf %*Image Reconstruction by Linear Programming %@Koji Tsuda,Gunnar Rätsch %t2003 %cNIPS %f/NIPS/NIPS-2003-5299.pdf %*Multiple Instance Learning via Disjunctive Programming Boosting %@Stuart Andrews,Thomas Hofmann %t2003 %cNIPS %f/NIPS/NIPS-2003-5300.pdf %*Convex Methods for Transduction %@Tijl D. Bie,Nello Cristianini %t2003 %cNIPS %f/NIPS/NIPS-2003-5301.pdf %*Kernel Dimensionality Reduction for Supervised Learning %@Kenji Fukumizu,Francis R. Bach,Michael I. Jordan %t2003 %cNIPS %f/NIPS/NIPS-2003-5302.pdf %*Clustering with the Connectivity Kernel %@Bernd Fischer,Volker Roth,Joachim M. Buhmann %t2003 %cNIPS %f/NIPS/NIPS-2003-5303.pdf %*Efficient and Robust Feature Extraction by Maximum Margin Criterion %@Haifeng Li,Tao Jiang,Keshu Zhang %t2003 %cNIPS %f/NIPS/NIPS-2003-5304.pdf %*Sparse Greedy Minimax Probability Machine Classification %@Thomas R. Strohmann,Andrei Belitski,Gregory Z. Grudic,Dennis DeCoste %t2003 %cNIPS %f/NIPS/NIPS-2003-5305.pdf %*Sequential Bayesian Kernel Regression %@Jaco Vermaak,Simon J. Godsill,Arnaud Doucet %t2003 %cNIPS %f/NIPS/NIPS-2003-5306.pdf %*Dynamical Modeling with Kernels for Nonlinear Time Series Prediction %@Liva Ralaivola,Florence D'alché-buc %t2003 %cNIPS %f/NIPS/NIPS-2003-5307.pdf %*Extreme Components Analysis %@Max Welling,Christopher Williams,Felix V. Agakov %t2003 %cNIPS %f/NIPS/NIPS-2003-5308.pdf %*Linear Dependent Dimensionality Reduction %@Nathan Srebro,Tommi S. Jaakkola %t2003 %cNIPS %f/NIPS/NIPS-2003-5309.pdf %*Locality Preserving Projections %@Xiaofei He,Partha Niyogi %t2003 %cNIPS %f/NIPS/NIPS-2003-5310.pdf %*Optimal Manifold Representation of Data: An Information Theoretic Approach %@Denis V. Chigirev,William Bialek %t2003 %cNIPS %f/NIPS/NIPS-2003-5311.pdf %*Ranking on Data Manifolds %@Denny Zhou,Jason Weston,Arthur Gretton,Olivier Bousquet,Bernhard Schölkopf %t2003 %cNIPS %f/NIPS/NIPS-2003-5312.pdf %*Out-of-Sample Extensions for LLE, Isomap, MDS, Eigenmaps, and Spectral Clustering %@Yoshua Bengio,Jean-françcois Paiement,Pascal Vincent,Olivier Delalleau,Nicolas L. Roux,Marie Ouimet %t2003 %cNIPS %f/NIPS/NIPS-2003-5313.pdf %*Pairwise Clustering and Graphical Models %@Noam Shental,Assaf Zomet,Tomer Hertz,Yair Weiss %t2003 %cNIPS %f/NIPS/NIPS-2003-5314.pdf %*Tree-structured Approximations by Expectation Propagation %@Yuan Qi,Tom Minka %t2003 %cNIPS %f/NIPS/NIPS-2003-5315.pdf %*Information Maximization in Noisy Channels : A Variational Approach %@David Barber,Felix V. Agakov %t2003 %cNIPS %f/NIPS/NIPS-2003-5316.pdf %*Iterative Scaled Trust-Region Learning in Krylov Subspaces via Pearlmutter's Implicit Sparse Hessian %@Eiji Mizutani,James Demmel %t2003 %cNIPS %f/NIPS/NIPS-2003-5317.pdf %*Large Scale Online Learning %@Léon Bottou,Yann L. Cun %t2003 %cNIPS %f/NIPS/NIPS-2003-5318.pdf %*Online Classification on a Budget %@Koby Crammer,Jaz Kandola,Yoram Singer %t2003 %cNIPS %f/NIPS/NIPS-2003-5319.pdf %*Online Learning via Global Feedback for Phrase Recognition %@Xavier Carreras,Lluís Màrquez %t2003 %cNIPS %f/NIPS/NIPS-2003-5320.pdf %*Sparse Representation and Its Applications in Blind Source Separation %@Yuanqing Li,Shun-ichi Amari,Sergei Shishkin,Jianting Cao,Fanji Gu,Andrzej S. Cichocki %t2003 %cNIPS %f/NIPS/NIPS-2003-5321.pdf %*Perspectives on Sparse Bayesian Learning %@Jason Palmer,Bhaskar D. Rao,David P. Wipf %t2003 %cNIPS %f/NIPS/NIPS-2003-5322.pdf %*Semi-Supervised Learning with Trees %@Charles Kemp,Thomas L. Griffiths,Sean Stromsten,Joshua B. Tenenbaum %t2003 %cNIPS %f/NIPS/NIPS-2003-5323.pdf %*New Algorithms for Efficient High Dimensional Non-parametric Classification %@Ting liu,Andrew W. Moore,Alexander Gray %t2003 %cNIPS %f/NIPS/NIPS-2003-5324.pdf %*Nonstationary Covariance Functions for Gaussian Process Regression %@Christopher J. Paciorek,Mark J. Schervish %t2003 %cNIPS %f/NIPS/NIPS-2003-5325.pdf %*Learning the k in k-means %@Greg Hamerly,Charles Elkan %t2003 %cNIPS %f/NIPS/NIPS-2003-5326.pdf %*Finding the M Most Probable Configurations using Loopy Belief Propagation %@Chen Yanover,Yair Weiss %t2003 %cNIPS %f/NIPS/NIPS-2003-5327.pdf %*Non-linear CCA and PCA by Alignment of Local Models %@Jakob J. Verbeek,Sam T. Roweis,Nikos A. Vlassis %t2003 %cNIPS %f/NIPS/NIPS-2003-5328.pdf %*Learning Spectral Clustering %@Francis R. Bach,Michael I. Jordan %t2003 %cNIPS %f/NIPS/NIPS-2003-5329.pdf %*AUC Optimization vs. Error Rate Minimization %@Corinna Cortes,Mehryar Mohri %t2003 %cNIPS %f/NIPS/NIPS-2003-5330.pdf %*Learning with Local and Global Consistency %@Denny Zhou,Olivier Bousquet,Thomas N. Lal,Jason Weston,Bernhard Schölkopf %t2003 %cNIPS %f/NIPS/NIPS-2003-5331.pdf %*Warped Gaussian Processes %@Edward Snelson,Zoubin Ghahramani,Carl E. Rasmussen %t2003 %cNIPS %f/NIPS/NIPS-2003-5332.pdf %*Can We Learn to Beat the Best Stock %@Allan Borodin,Ran El-Yaniv,Vincent Gogan %t2003 %cNIPS %f/NIPS/NIPS-2003-5333.pdf %*Approximate Expectation Maximization %@Tom Heskes,Onno Zoeter,Wim Wiegerinck %t2003 %cNIPS %f/NIPS/NIPS-2003-5334.pdf %*Linear Response for Approximate Inference %@Max Welling,Yee W. Teh %t2003 %cNIPS %f/NIPS/NIPS-2003-5335.pdf %*Semidefinite Relaxations for Approximate Inference on Graphs with Cycles %@Michael I. Jordan,Martin J. Wainwright %t2003 %cNIPS %f/NIPS/NIPS-2003-5336.pdf %*Approximability of Probability Distributions %@Alina Beygelzimer,Irina Rish %t2003 %cNIPS %f/NIPS/NIPS-2003-5337.pdf %*Denoising and Untangling Graphs Using Degree Priors %@Quaid D. Morris,Brendan J. Frey %t2003 %cNIPS %f/NIPS/NIPS-2003-5338.pdf %*On the Concentration of Expectation and Approximate Inference in Layered Networks %@Long Nguyen,Michael I. Jordan %t2003 %cNIPS %f/NIPS/NIPS-2003-5339.pdf %*Inferring State Sequences for Non-linear Systems with Embedded Hidden Markov Models %@Radford M. Neal,Matthew J. Beal,Sam T. Roweis %t2003 %cNIPS %f/NIPS/NIPS-2003-5340.pdf %*Fast Algorithms for Large-State-Space HMMs with Applications to Web Usage Analysis %@Pedro F. Felzenszwalb,Daniel P. Huttenlocher,Jon M. Kleinberg %t2003 %cNIPS %f/NIPS/NIPS-2003-5341.pdf %*Wormholes Improve Contrastive Divergence %@Max Welling,Andriy Mnih,Geoffrey E. Hinton %t2003 %cNIPS %f/NIPS/NIPS-2003-5342.pdf %*Laplace Propagation %@Eleazar Eskin,Alex J. Smola,S.v.n. Vishwanathan %t2003 %cNIPS %f/NIPS/NIPS-2003-5343.pdf %*Learning to Find Pre-Images %@Jason Weston,Bernhard Schölkopf,Gökhan H. Bakir %t2003 %cNIPS %f/NIPS/NIPS-2003-5344.pdf %*Semi-Definite Programming by Perceptron Learning %@Thore Graepel,Ralf Herbrich,Andriy Kharechko,John S. Shawe-taylor %t2003 %cNIPS %f/NIPS/NIPS-2003-5345.pdf %*Computing Gaussian Mixture Models with EM Using Equivalence Constraints %@Noam Shental,Aharon Bar-hillel,Tomer Hertz,Daphna Weinshall %t2003 %cNIPS %f/NIPS/NIPS-2003-5346.pdf %*Feature Selection in Clustering Problems %@Volker Roth,Tilman Lange %t2003 %cNIPS %f/NIPS/NIPS-2003-5347.pdf %*An Iterative Improvement Procedure for Hierarchical Clustering %@David Kauchak,Sanjoy Dasgupta %t2003 %cNIPS %f/NIPS/NIPS-2003-5348.pdf %*Identifying Structure across Pre-partitioned Data %@Zvika Marx,Ido Dagan,Eli Shamir %t2003 %cNIPS %f/NIPS/NIPS-2003-5349.pdf %*Log-Linear Models for Label Ranking %@Ofer Dekel,Yoram Singer,Christopher D. Manning %t2003 %cNIPS %f/NIPS/NIPS-2003-5350.pdf %*No Unbiased Estimator of the Variance of K-Fold Cross-Validation %@Yoshua Bengio,Yves Grandvalet %t2003 %cNIPS %f/NIPS/NIPS-2003-5351.pdf %*Bias-Corrected Bootstrap and Model Uncertainty %@Harald Steck,Tommi S. Jaakkola %t2003 %cNIPS %f/NIPS/NIPS-2003-5352.pdf %*Probability Estimates for Multi-Class Classification by Pairwise Coupling %@Ting-fan Wu,Chih-jen Lin,Ruby C. Weng %t2003 %cNIPS %f/NIPS/NIPS-2003-5353.pdf %*Necessary Intransitive Likelihood-Ratio Classifiers %@Gang Ji,Jeff A. Bilmes %t2003 %cNIPS %f/NIPS/NIPS-2003-5354.pdf %*Classification with Hybrid Generative/Discriminative Models %@Rajat Raina,Yirong Shen,Andrew McCallum,Andrew Y. Ng %t2003 %cNIPS %f/NIPS/NIPS-2003-5355.pdf %*A Model for Learning the Semantics of Pictures %@Victor Lavrenko,R. Manmatha,Jiwoon Jeon %t2003 %cNIPS %f/NIPS/NIPS-2003-5356.pdf %*Algorithms for Interdependent Security Games %@Michael Kearns,Luis E. Ortiz %t2003 %cNIPS %f/NIPS/NIPS-2003-5357.pdf %*GPPS: A Gaussian Process Positioning System for Cellular Networks %@Anton Schwaighofer,Marian Grigoras,Volker Tresp,Clemens Hoffmann %t2003 %cNIPS %f/NIPS/NIPS-2003-5358.pdf %*An Autonomous Robotic System for Mapping Abandoned Mines %@David Ferguson,Aaron Morris,Dirk Hähnel,Christopher Baker,Zachary Omohundro,Carlos Reverte,Scott Thayer,Charles Whittaker,William Whittaker,Wolfram Burgard,Sebastian Thrun %t2003 %cNIPS %f/NIPS/NIPS-2003-5359.pdf %*Semi-supervised Protein Classification Using Cluster Kernels %@Jason Weston,Denny Zhou,André Elisseeff,William S. Noble,Christina S. Leslie %t2003 %cNIPS %f/NIPS/NIPS-2003-5360.pdf %*Statistical Debugging of Sampled Programs %@Alice X. Zheng,Michael I. Jordan,Ben Liblit,Alex Aiken %t2003 %cNIPS %f/NIPS/NIPS-2003-5361.pdf %*Markov Models for Automated ECG Interval Analysis %@Nicholas P. Hughes,Lionel Tarassenko,Stephen J. Roberts %t2003 %cNIPS %f/NIPS/NIPS-2003-5362.pdf %*Parameterized Novelty Detectors for Environmental Sensor Monitoring %@Cynthia Archer,Todd K. Leen,António M. Baptista %t2003 %cNIPS %f/NIPS/NIPS-2003-5363.pdf %*Application of SVMs for Colour Classification and Collision Detection with AIBO Robots %@Michael J. Quinlan,Stephan K. Chalup,Richard H. Middleton %t2003 %cNIPS %f/NIPS/NIPS-2003-5364.pdf %*Kernels for Structured Natural Language Data %@Jun Suzuki,Yutaka Sasaki,Eisaku Maeda %t2003 %cNIPS %f/NIPS/NIPS-2003-5365.pdf %*A Fast Multi-Resolution Method for Detection of Significant Spatial Disease Clusters %@Daniel B. Neill,Andrew W. Moore %t2003 %cNIPS %f/NIPS/NIPS-2003-5366.pdf %*Link Prediction in Relational Data %@Ben Taskar,Ming-fai Wong,Pieter Abbeel,Daphne Koller %t2003 %cNIPS %f/NIPS/NIPS-2003-5367.pdf %*Unsupervised Color Decomposition Of Histologically Stained Tissue Samples %@Andrew Rabinovich,Sameer Agarwal,Casey Laris,Jeffrey H. Price,Serge J. Belongie %t2003 %cNIPS %f/NIPS/NIPS-2003-5368.pdf %*ICA-based Clustering of Genes from Microarray Expression Data %@Su-in Lee,Serafim Batzoglou %t2003 %cNIPS %f/NIPS/NIPS-2003-5369.pdf %*Gene Expression Clustering with Functional Mixture Models %@Darya Chudova,Christopher Hart,Eric Mjolsness,Padhraic Smyth %t2003 %cNIPS %f/NIPS/NIPS-2003-5370.pdf %*Reconstructing MEG Sources with Unknown Correlations %@Maneesh Sahani,Srikantan S. Nagarajan %t2003 %cNIPS %f/NIPS/NIPS-2003-5371.pdf %*Different Cortico-Basal Ganglia Loops Specialize in Reward Prediction at Different Time Scales %@Saori C. Tanaka,Kenji Doya,Go Okada,Kazutaka Ueda,Yasumasa Okamoto,Shigeto Yamawaki %t2003 %cNIPS %f/NIPS/NIPS-2003-5372.pdf %*Training fMRI Classifiers to Detect Cognitive States across Multiple Human Subjects %@Xuerui Wang,Rebecca Hutchinson,Tom M. Mitchell %t2003 %cNIPS %f/NIPS/NIPS-2003-5373.pdf %*Nonlinear Filtering of Electron Micrographs by Means of Support Vector Regression %@Roland Vollgraf,Michael Scholz,Ian A. Meinertzhagen,Klaus Obermayer %t2003 %cNIPS %f/NIPS/NIPS-2003-5374.pdf %*Impact of an Energy Normalization Transform on the Performance of the LF-ASD Brain Computer Interface %@Yu Zhou,Steven G. Mason,Gary E. Birch %t2003 %cNIPS %f/NIPS/NIPS-2003-5375.pdf %*Increase Information Transfer Rates in BCI by CSP Extension to Multi-class %@Guido Dornhege,Benjamin Blankertz,Gabriel Curio,Klaus-Robert Müller %t2003 %cNIPS %f/NIPS/NIPS-2003-5376.pdf %*Subject-Independent Magnetoencephalographic Source Localization by a Multilayer Perceptron %@Sung C. Jun,Barak A. Pearlmutter %t2003 %cNIPS %f/NIPS/NIPS-2003-5377.pdf %*Gaussian Processes in Reinforcement Learning %@Malte Kuss,Carl E. Rasmussen %t2003 %cNIPS %f/NIPS/NIPS-2003-5378.pdf %*Applying Metric-Trees to Belief-Point POMDPs %@Joelle Pineau,Geoffrey J. Gordon,Sebastian Thrun %t2003 %cNIPS %f/NIPS/NIPS-2003-5379.pdf %*ARA*: Anytime A* with Provable Bounds on Sub-Optimality %@Maxim Likhachev,Geoffrey J. Gordon,Sebastian Thrun %t2003 %cNIPS %f/NIPS/NIPS-2003-5380.pdf %*Approximate Planning in POMDPs with Macro-Actions %@Georgios Theocharous,Leslie P. Kaelbling %t2003 %cNIPS %f/NIPS/NIPS-2003-5381.pdf %*Envelope-based Planning in Relational MDPs %@Natalia H. Gardiol,Leslie P. Kaelbling %t2003 %cNIPS %f/NIPS/NIPS-2003-5382.pdf %*An MDP-Based Approach to Online Mechanism Design %@David C. Parkes,Satinder P. Singh %t2003 %cNIPS %f/NIPS/NIPS-2003-5383.pdf %*Autonomous Helicopter Flight via Reinforcement Learning %@H. J. Kim,Michael I. Jordan,Shankar Sastry,Andrew Y. Ng %t2003 %cNIPS %f/NIPS/NIPS-2003-5384.pdf %*All learning is Local: Multi-agent Learning in Global Reward Games %@Yu-han Chang,Tracey Ho,Leslie P. Kaelbling %t2003 %cNIPS %f/NIPS/NIPS-2003-5385.pdf %*How to Combine Expert (and Novice) Advice when Actions Impact the Environment? %@Daniela Pucci de Farias,Nimrod Megiddo %t2003 %cNIPS %f/NIPS/NIPS-2003-5386.pdf %*Bounded Finite State Controllers %@Pascal Poupart,Craig Boutilier %t2003 %cNIPS %f/NIPS/NIPS-2003-5387.pdf %*Policy Search by Dynamic Programming %@J. A. Bagnell,Sham M. Kakade,Jeff G. Schneider,Andrew Y. Ng %t2003 %cNIPS %f/NIPS/NIPS-2003-5388.pdf %*Robustness in Markov Decision Problems with Uncertain Transition Matrices %@Arnab Nilim,Laurent El Ghaoui %t2003 %cNIPS %f/NIPS/NIPS-2003-5389.pdf %*Approximate Policy Iteration with a Policy Language Bias %@Alan Fern,Sungwook Yoon,Robert Givan %t2003 %cNIPS %f/NIPS/NIPS-2003-5390.pdf %*A Nonlinear Predictive State Representation %@Matthew R. Rudary,Satinder P. Singh %t2003 %cNIPS %f/NIPS/NIPS-2003-5391.pdf %*Learning Near-Pareto-Optimal Conventions in Polynomial Time %@Xiaofeng Wang,Tuomas Sandholm %t2003 %cNIPS %f/NIPS/NIPS-2003-5392.pdf %*Auction Mechanism Design for Multi-Robot Coordination %@Curt Bererton,Geoffrey J. Gordon,Sebastian Thrun %t2003 %cNIPS %f/NIPS/NIPS-2003-5393.pdf %*Distributed Optimization in Adaptive Networks %@Ciamac C. Moallemi,Benjamin V. Roy %t2003 %cNIPS %f/NIPS/NIPS-2003-5394.pdf %*Linear Program Approximations for Factored Continuous-State Markov Decision Processes %@Milos Hauskrecht,Branislav Kveton %t2003 %cNIPS %f/NIPS/NIPS-2003-5395.pdf %*Insights from Machine Learning Applied to Human Visual Classification %@Felix A. Wichmann,Arnulf B. Graf %t2003 %cNIPS %f/NIPS/NIPS-2003-5396.pdf %*Reasoning about Time and Knowledge in Neural Symbolic Learning Systems %@Artur Garcez,Luis C. Lamb %t2003 %cNIPS %f/NIPS/NIPS-2003-5397.pdf %*An MCMC-Based Method of Comparing Connectionist Models in Cognitive Science %@Woojae Kim,Daniel J. Navarro,Mark A. Pitt,In J. Myung %t2003 %cNIPS %f/NIPS/NIPS-2003-5398.pdf %*Perception of the Structure of the Physical World Using Unknown Multimodal Sensors and Effectors %@D. Philipona,J.k. O'regan,J.-p. Nadal,Olivier Coenen %t2003 %cNIPS %f/NIPS/NIPS-2003-5399.pdf %*From Algorithmic to Subjective Randomness %@Thomas L. Griffiths,Joshua B. Tenenbaum %t2003 %cNIPS %f/NIPS/NIPS-2003-5400.pdf %*Unsupervised Context Sensitive Language Acquisition from a Large Corpus %@Zach Solan,David Horn,Eytan Ruppin,Shimon Edelman %t2003 %cNIPS %f/NIPS/NIPS-2003-5401.pdf %*A Holistic Approach to Compositional Semantics: a connectionist model and robot experiments %@Yuuya Sugita,Jun Tani %t2003 %cNIPS %f/NIPS/NIPS-2003-5402.pdf %*Model Uncertainty in Classical Conditioning %@Aaron C. Courville,Geoffrey J. Gordon,David S. Touretzky,Nathaniel D. Daw %t2003 %cNIPS %f/NIPS/NIPS-2003-5403.pdf %*A Recurrent Model of Orientation Maps with Simple and Complex Cells %@Paul Merolla,Kwabena A. Boahen %t2003 %cNIPS %f/NIPS/NIPS-2003-5404.pdf %*A Summating, Exponentially-Decaying CMOS Synapse for Spiking Neural Systems %@Rock Z. Shi,Timothy K. Horiuchi %t2003 %cNIPS %f/NIPS/NIPS-2003-5405.pdf %*Minimising Contrastive Divergence in Noisy, Mixed-mode VLSI Neurons %@Hsin Chen,Patrice Fleury,Alan F. Murray %t2003 %cNIPS %f/NIPS/NIPS-2003-5406.pdf %*Training a Quantum Neural Network %@Bob Ricks,Dan Ventura %t2003 %cNIPS %f/NIPS/NIPS-2003-5407.pdf %*Synchrony Detection by Analogue VLSI Neurons with Bimodal STDP Synapses %@Adria Bofill-i-petit,Alan F. Murray %t2003 %cNIPS %f/NIPS/NIPS-2003-5408.pdf %*A Mixed-Signal VLSI for Real-Time Generation of Edge-Based Image Vectors %@Masakazu Yagi,Hideo Yamasaki,Tadashi Shibata %t2003 %cNIPS %f/NIPS/NIPS-2003-5409.pdf %*Entrainment of Silicon Central Pattern Generators for Legged Locomotory Control %@Francesco Tenore,Ralph Etienne-Cummings,M. A. Lewis %t2003 %cNIPS %f/NIPS/NIPS-2003-5410.pdf %*A Neuromorphic Multi-chip Model of a Disparity Selective Complex Cell %@Bertram E. Shi,Eric K. Tsang %t2003 %cNIPS %f/NIPS/NIPS-2003-5411.pdf %*Error Bounds for Transductive Learning via Compression and Clustering %@Philip Derbeko,Ran El-Yaniv,Ron Meir %t2003 %cNIPS %f/NIPS/NIPS-2003-5412.pdf %*Online Learning of Non-stationary Sequences %@Claire Monteleoni,Tommi S. Jaakkola %t2003 %cNIPS %f/NIPS/NIPS-2003-5413.pdf %*On the Dynamics of Boosting %@Cynthia Rudin,Ingrid Daubechies,Robert E. Schapire %t2003 %cNIPS %f/NIPS/NIPS-2003-5414.pdf %*Boosting versus Covering %@Kohei Hatano,Manfred K. Warmuth %t2003 %cNIPS %f/NIPS/NIPS-2003-5415.pdf %*Near-Minimax Optimal Classification with Dyadic Classification Trees %@Clayton Scott,Robert Nowak %t2003 %cNIPS %f/NIPS/NIPS-2003-5416.pdf %*PAC-Bayesian Generic Chaining %@Jean-yves Audibert,Olivier Bousquet %t2003 %cNIPS %f/NIPS/NIPS-2003-5417.pdf %*Self-calibrating Probability Forecasting %@Vladimir Vovk,Glenn Shafer,Ilia Nouretdinov %t2003 %cNIPS %f/NIPS/NIPS-2003-5418.pdf %*When Does Non-Negative Matrix Factorization Give a Correct Decomposition into Parts? %@David Donoho,Victoria Stodden %t2003 %cNIPS %f/NIPS/NIPS-2003-5419.pdf %*Variational Linear Response %@Manfred Opper,Ole Winther %t2003 %cNIPS %f/NIPS/NIPS-2003-5420.pdf %*Geometric Clustering Using the Information Bottleneck Method %@Susanne Still,William Bialek,Léon Bottou %t2003 %cNIPS %f/NIPS/NIPS-2003-5421.pdf %*Large Margin Classifiers: Convex Loss, Low Noise, and Convergence Rates %@Peter L. Bartlett,Michael I. Jordan,Jon D. Mcauliffe %t2003 %cNIPS %f/NIPS/NIPS-2003-5422.pdf %*Limiting Form of the Sample Covariance Eigenspectrum in PCA and Kernel PCA %@David Hoyle,Magnus Rattray %t2003 %cNIPS %f/NIPS/NIPS-2003-5423.pdf %*Approximate Analytical Bootstrap Averages for Support Vector Classifiers %@Dörthe Malzahn,Manfred Opper %t2003 %cNIPS %f/NIPS/NIPS-2003-5424.pdf %*Learning Curves for Stochastic Gradient Descent in Linear Feedforward Networks %@Justin Werfel,Xiaohui Xie,H. S. Seung %t2003 %cNIPS %f/NIPS/NIPS-2003-5425.pdf %*Ambiguous Model Learning Made Unambiguous with 1/f Priors %@Gurinder S. Atwal,William Bialek %t2003 %cNIPS %f/NIPS/NIPS-2003-5426.pdf %*Information Bottleneck for Gaussian Variables %@Gal Chechik,Amir Globerson,Naftali Tishby,Yair Weiss %t2003 %cNIPS %f/NIPS/NIPS-2003-5427.pdf %*Measure Based Regularization %@Olivier Bousquet,Olivier Chapelle,Matthias Hein %t2003 %cNIPS %f/NIPS/NIPS-2003-5428.pdf %*Online Passive-Aggressive Algorithms %@Shai Shalev-shwartz,Koby Crammer,Ofer Dekel,Yoram Singer %t2003 %cNIPS %f/NIPS/NIPS-2003-5429.pdf %*Margin Maximizing Loss Functions %@Saharon Rosset,Ji Zhu,Trevor J. Hastie %t2003 %cNIPS %f/NIPS/NIPS-2003-5430.pdf %*The Doubly Balanced Network of Spiking Neurons: A Memory Model with High Capacity %@Yuval Aviel,David Horn,Moshe Abeles %t2003 %cNIPS %f/NIPS/NIPS-2003-5431.pdf %*Information Dynamics and Emergent Computation in Recurrent Circuits of Spiking Neurons %@Thomas Natschläger,Wolfgang Maass %t2003 %cNIPS %f/NIPS/NIPS-2003-5432.pdf %*The Diffusion-Limited Biochemical Signal-Relay Channel %@Peter J. Thomas,Donald J. Spencer,Sierra K. Hampton,Peter Park,Joseph P. Zurkus %t2003 %cNIPS %f/NIPS/NIPS-2003-5433.pdf %*Dopamine Modulation in a Basal Ganglio-Cortical Network of Working Memory %@Aaron J. Gruber,Peter Dayan,Boris S. Gutkin,Sara A. Solla %t2003 %cNIPS %f/NIPS/NIPS-2003-5434.pdf %*Circuit Optimization Predicts Dynamic Networks for Chemosensory Orientation in Nematode C. elegans %@Nathan A. Dunn,John S. Conery,Shawn R. Lockery %t2003 %cNIPS %f/NIPS/NIPS-2003-5435.pdf %*Mechanism of Neural Interference by Transcranial Magnetic Stimulation: Network or Single Neuron? %@Yoichi Miyawaki,Masato Okada %t2003 %cNIPS %f/NIPS/NIPS-2003-5436.pdf %*Plasticity Kernels and Temporal Statistics %@Peter Dayan,Michael Häusser,Michael London %t2003 %cNIPS %f/NIPS/NIPS-2003-5437.pdf %*Maximum Likelihood Estimation of a Stochastic Integrate-and-Fire Neural Model %@Liam Paninski,Eero P. Simoncelli,Jonathan W. Pillow %t2003 %cNIPS %f/NIPS/NIPS-2003-5438.pdf %*Probabilistic Inference in Human Sensorimotor Processing %@Konrad P. Körding,Daniel M. Wolpert %t2003 %cNIPS %f/NIPS/NIPS-2003-5439.pdf %*Estimating Internal Variables and Paramters of a Learning Agent by a Particle Filter %@Kazuyuki Samejima,Kenji Doya,Yasumasa Ueda,Minoru Kimura %t2003 %cNIPS %f/NIPS/NIPS-2003-5440.pdf %*Analytical Solution of Spike-timing Dependent Plasticity Based on Synaptic Biophysics %@Bernd Porr,Ausra Saudargiene,Florentin Wörgötter %t2003 %cNIPS %f/NIPS/NIPS-2003-5441.pdf %*A Probabilistic Model of Auditory Space Representation in the Barn Owl %@Brian J. Fischer,Charles H. Anderson %t2003 %cNIPS %f/NIPS/NIPS-2003-5442.pdf %*Decoding V1 Neuronal Activity using Particle Filtering with Volterra Kernels %@Ryan C. Kelly,Tai Sing Lee %t2003 %cNIPS %f/NIPS/NIPS-2003-5443.pdf %*Prediction on Spike Data Using Kernel Algorithms %@Jan Eichhorn,Andreas Tolias,Alexander Zien,Malte Kuss,Jason Weston,Nikos Logothetis,Bernhard Schölkopf,Carl E. Rasmussen %t2003 %cNIPS %f/NIPS/NIPS-2003-5444.pdf %*Phonetic Speaker Recognition with Support Vector Machines %@William M. Campbell,Joseph P. Campbell,Douglas A. Reynolds,Douglas A. Jones,Timothy R. Leek %t2003 %cNIPS %f/NIPS/NIPS-2003-5445.pdf %*A Kullback-Leibler Divergence Based Kernel for SVM Classification in Multimedia Applications %@Pedro J. Moreno,Purdy P. Ho,Nuno Vasconcelos %t2003 %cNIPS %f/NIPS/NIPS-2003-5446.pdf %*Probabilistic Inference of Speech Signals from Phaseless Spectrograms %@Kannan Achan,Sam T. Roweis,Brendan J. Frey %t2003 %cNIPS %f/NIPS/NIPS-2003-5447.pdf %*Eigenvoice Speaker Adaptation via Composite Kernel Principal Component Analysis %@James T. Kwok,Brian Mak,Simon Ho %t2003 %cNIPS %f/NIPS/NIPS-2003-5448.pdf %*Predicting Speech Intelligibility from a Population of Neurons %@Jeff Bondy,Ian Bruce,Suzanna Becker,Simon Haykin %t2003 %cNIPS %f/NIPS/NIPS-2003-5449.pdf %*One Microphone Blind Dereverberation Based on Quasi-periodicity of Speech Signals %@Tomohiro Nakatani,Masato Miyoshi,Keisuke Kinoshita %t2003 %cNIPS %f/NIPS/NIPS-2003-5450.pdf %*A Classification-based Cocktail-party Processor %@Nicoleta Roman,Deliang Wang,Guy J. Brown %t2003 %cNIPS %f/NIPS/NIPS-2003-5451.pdf %*Local Phase Coherence and the Perception of Blur %@Zhou Wang,Eero P. Simoncelli %t2003 %cNIPS %f/NIPS/NIPS-2003-5452.pdf %*Nonlinear Processing in LGN Neurons %@Vincent Bonin,Valerio Mante,Matteo Carandini %t2003 %cNIPS %f/NIPS/NIPS-2003-5453.pdf %*A Functional Architecture for Motion Pattern Processing in MSTd %@Scott A. Beardsley,Lucia M. Vaina %t2003 %cNIPS %f/NIPS/NIPS-2003-5454.pdf %*Human and Ideal Observers for Detecting Image Curves %@Fang Fang,Daniel Kersten,Paul R. Schrater,Alan L. Yuille %t2003 %cNIPS %f/NIPS/NIPS-2003-5455.pdf %*Eye Movements for Reward Maximization %@Nathan Sprague,Dana Ballard %t2003 %cNIPS %f/NIPS/NIPS-2003-5456.pdf %*Eye Micro-movements Improve Stimulus Detection Beyond the Nyquist Limit in the Peripheral Retina %@Matthias H. Hennig,Florentin Wörgötter %t2003 %cNIPS %f/NIPS/NIPS-2003-5457.pdf %*Bounded Invariance and the Formation of Place Fields %@Reto Wyss,Paul F. Verschure %t2003 %cNIPS %f/NIPS/NIPS-2003-5458.pdf %*Discriminating Deformable Shape Classes %@Salvador Ruiz-correa,Linda G. Shapiro,Marina Meila,Gabriel Berson %t2003 %cNIPS %f/NIPS/NIPS-2003-5459.pdf %*Using the Forest to See the Trees: A Graphical Model Relating Features, Objects, and Scenes %@Kevin P. Murphy,Antonio Torralba,William T. Freeman %t2003 %cNIPS %f/NIPS/NIPS-2003-5460.pdf %*Factorization with Uncertainty and Missing Data: Exploiting Temporal Coherence %@Amit Gruber,Yair Weiss %t2003 %cNIPS %f/NIPS/NIPS-2003-5461.pdf %*Mutual Boosting for Contextual Inference %@Michael Fink,Pietro Perona %t2003 %cNIPS %f/NIPS/NIPS-2003-5462.pdf %*Learning a Rare Event Detection Cascade by Direct Feature Selection %@Jianxin Wu,James M. Rehg,Matthew D. Mullin %t2003 %cNIPS %f/NIPS/NIPS-2003-5463.pdf %*Discriminative Fields for Modeling Spatial Dependencies in Natural Images %@Sanjiv Kumar,Martial Hebert %t2003 %cNIPS %f/NIPS/NIPS-2003-5464.pdf %*Attractive People: Assembling Loose-Limbed Models using Non-parametric Belief Propagation %@Leonid Sigal,Michael Isard,Benjamin H. Sigelman,Michael J. Black %t2003 %cNIPS %f/NIPS/NIPS-2003-5465.pdf %*Automatic Annotation of Everyday Movements %@Deva Ramanan,David A. Forsyth %t2003 %cNIPS %f/NIPS/NIPS-2003-5466.pdf %*Learning Non-Rigid 3D Shape from 2D Motion %@Lorenzo Torresani,Aaron Hertzmann,Christoph Bregler %t2003 %cNIPS %f/NIPS/NIPS-2003-5467.pdf %*Towards Social Robots: Automatic Evaluation of Human-Robot Interaction by Facial Expression Classification %@G.C. Littlewort,M.S. Bartlett,I.R. Fasel,J. Chenu,T. Kanda,H. Ishiguro,J.R. Movellan %t2003 %cNIPS %f/NIPS/NIPS-2003-5468.pdf %*Salient Boundary Detection using Ratio Contour %@Song Wang,Toshiro Kubota,Jeffrey M. Siskind %t2003 %cNIPS %f/NIPS/NIPS-2003-5469.pdf %*Geometric Analysis of Constrained Curves %@Anuj Srivastava,Washington Mio,Xiuwen Liu,Eric Klassen %t2003 %cNIPS %f/NIPS/NIPS-2003-5470.pdf %*A Sampled Texture Prior for Image Super-Resolution %@Lyndsey C. Pickup,Stephen J. Roberts,Andrew Zisserman %t2003 %cNIPS %f/NIPS/NIPS-2003-5471.pdf %*Bayesian Color Constancy with Non-Gaussian Models %@Charles Rosenberg,Alok Ladsariya,Tom Minka %t2003 %cNIPS %f/NIPS/NIPS-2003-5472.pdf %*An Improved Scheme for Detection and Labelling in Johansson Displays %@Claudio Fanti,Marzia Polito,Pietro Perona %t2003 %cNIPS %f/NIPS/NIPS-2003-5473.pdf %*Fast Exact Inference with a Factored Model for Natural Language Parsing %@Dan Klein,Christopher D. Manning %t2002 %cNIPS %f/NIPS/NIPS-2002-5474.pdf %*Prediction and Semantic Association %@Thomas L. Griffiths,Mark Steyvers %t2002 %cNIPS %f/NIPS/NIPS-2002-5475.pdf %*Replay, Repair and Consolidation %@Szabolcs Káli,Peter Dayan %t2002 %cNIPS %f/NIPS/NIPS-2002-5476.pdf %*A Minimal Intervention Principle for Coordinated Movement %@Emanuel Todorov,Michael I. Jordan %t2002 %cNIPS %f/NIPS/NIPS-2002-5477.pdf %*Categorization Under Complexity: A Unified MDL Account of Human Learning of Regular and Irregular Categories %@David Fass,Jacob Feldman %t2002 %cNIPS %f/NIPS/NIPS-2002-5478.pdf %*Theory-Based Causal Inference %@Joshua B. Tenenbaum,Thomas L. Griffiths %t2002 %cNIPS %f/NIPS/NIPS-2002-5479.pdf %*Bayesian Models of Inductive Generalization %@Neville E. Sanjana,Joshua B. Tenenbaum %t2002 %cNIPS %f/NIPS/NIPS-2002-5480.pdf %*Combining Dimensions and Features in Similarity-Based Representations %@Daniel J. Navarro,Michael D. Lee %t2002 %cNIPS %f/NIPS/NIPS-2002-5481.pdf %*Modeling Midazolam's Effect on the Hippocampus and Recognition Memory %@Kenneth J. Malmberg,René Zeelenberg,Richard M. Shiffrin %t2002 %cNIPS %f/NIPS/NIPS-2002-5482.pdf %*Dynamical Causal Learning %@David Danks,Thomas L. Griffiths,Joshua B. Tenenbaum %t2002 %cNIPS %f/NIPS/NIPS-2002-5483.pdf %*Visual Development Aids the Acquisition of Motion Velocity Sensitivities %@Robert A. Jacobs,Melissa Dominguez %t2002 %cNIPS %f/NIPS/NIPS-2002-5484.pdf %*Timing and Partial Observability in the Dopamine System %@Nathaniel D. Daw,Aaron C. Courville,David S. Touretzky %t2002 %cNIPS %f/NIPS/NIPS-2002-5485.pdf %*Automatic Acquisition and Efficient Representation of Syntactic Structures %@Zach Solan,Eytan Ruppin,David Horn,Shimon Edelman %t2002 %cNIPS %f/NIPS/NIPS-2002-5486.pdf %*Binary Coding in Auditory Cortex %@Michael R. Deweese,Anthony M. Zador %t2002 %cNIPS %f/NIPS/NIPS-2002-5487.pdf %*How Linear are Auditory Cortical Responses? %@Maneesh Sahani,Jennifer F. Linden %t2002 %cNIPS %f/NIPS/NIPS-2002-5488.pdf %*Neural Decoding of Cursor Motion Using a Kalman Filter %@W Wu,M. J. Black,Y. Gao,M. Serruya,A. Shaikhouni,J. P. Donoghue,Elie Bienenstock %t2002 %cNIPS %f/NIPS/NIPS-2002-5489.pdf %*Spikernels: Embedding Spiking Neurons in Inner-Product Spaces %@Lavi Shpigelman,Yoram Singer,Rony Paz,Eilon Vaadia %t2002 %cNIPS %f/NIPS/NIPS-2002-5490.pdf %*Spectro-Temporal Receptive Fields of Subthreshold Responses in Auditory Cortex %@Christian K. Machens,Michael Wehr,Anthony M. Zador %t2002 %cNIPS %f/NIPS/NIPS-2002-5491.pdf %*Temporal Coherence, Natural Image Sequences, and the Visual Cortex %@Jarmo Hurri,Aapo Hyvärinen %t2002 %cNIPS %f/NIPS/NIPS-2002-5492.pdf %*Expected and Unexpected Uncertainty: ACh and NE in the Neocortex %@Peter Dayan,Angela J. Yu %t2002 %cNIPS %f/NIPS/NIPS-2002-5493.pdf %*Dopamine Induced Bistability Enhances Signal Processing in Spiny Neurons %@Aaron J. Gruber,Sara A. Solla,James C. Houk %t2002 %cNIPS %f/NIPS/NIPS-2002-5494.pdf %*Branching Law for Axons %@Dmitri B. Chklovskii,Armen Stepanyants %t2002 %cNIPS %f/NIPS/NIPS-2002-5495.pdf %*Binary Tuning is Optimal for Neural Rate Coding with High Temporal Resolution %@Matthias Bethge,David Rotermund,Klaus Pawelzik %t2002 %cNIPS %f/NIPS/NIPS-2002-5496.pdf %*An Information Theoretic Approach to the Functional Classification of Neurons %@Elad Schneidman,William Bialek,Michael Ii %t2002 %cNIPS %f/NIPS/NIPS-2002-5497.pdf %*Morton-Style Factorial Coding of Color in Primary Visual Cortex %@Javier R. Movellan,Thomas Wachtler,Thomas D. Albright,Terrence Sejnowski %t2002 %cNIPS %f/NIPS/NIPS-2002-5498.pdf %*A Model for Real-Time Computation in Generic Neural Microcircuits %@Wolfgang Maass,Thomas Natschläger,Henry Markram %t2002 %cNIPS %f/NIPS/NIPS-2002-5499.pdf %*Adaptation and Unsupervised Learning %@Peter Dayan,Maneesh Sahani,Gregoire Deback %t2002 %cNIPS %f/NIPS/NIPS-2002-5500.pdf %*A Digital Antennal Lobe for Pattern Equalization: Analysis and Design %@Alex Holub,Gilles Laurent,Pietro Perona %t2002 %cNIPS %f/NIPS/NIPS-2002-5501.pdf %*Hidden Markov Model of Cortical Synaptic Plasticity: Derivation of the Learning Rule %@Michael Eisele,Kenneth D. Miller %t2002 %cNIPS %f/NIPS/NIPS-2002-5502.pdf %*Selectivity and Metaplasticity in a Unified Calcium-Dependent Model %@Luk Chong Yeung,Brian S. Blais,Leon N. Cooper,Harel Z. Shouval %t2002 %cNIPS %f/NIPS/NIPS-2002-5503.pdf %*Kernel-Based Extraction of Slow Features: Complex Cells Learn Disparity and Translation Invariance from Natural Images %@Alistair Bray,Dominique Martinez %t2002 %cNIPS %f/NIPS/NIPS-2002-5504.pdf %*Maximally Informative Dimensions: Analyzing Neural Responses to Natural Signals %@Tatyana Sharpee,Nicole C. Rust,William Bialek %t2002 %cNIPS %f/NIPS/NIPS-2002-5505.pdf %*Dynamical Constraints on Computing with Spike Timing in the Cortex %@Arunava Banerjee,Alexandre Pouget %t2002 %cNIPS %f/NIPS/NIPS-2002-5506.pdf %*Interpreting Neural Response Variability as Monte Carlo Sampling of the Posterior %@Patrik O. Hoyer,Aapo Hyvärinen %t2002 %cNIPS %f/NIPS/NIPS-2002-5507.pdf %*A Neural Edge-Detection Model for Enhanced Auditory Sensitivity in Modulated Noise %@Alon Fishbach,Bradford J. May %t2002 %cNIPS %f/NIPS/NIPS-2002-5508.pdf %*Evidence Optimization Techniques for Estimating Stimulus-Response Functions %@Maneesh Sahani,Jennifer F. Linden %t2002 %cNIPS %f/NIPS/NIPS-2002-5509.pdf %*Data-Dependent Bounds for Bayesian Mixture Methods %@Ron Meir,Tong Zhang %t2002 %cNIPS %f/NIPS/NIPS-2002-5510.pdf %*A Statistical Mechanics Approach to Approximate Analytical Bootstrap Averages %@Dörthe Malzahn,Manfred Opper %t2002 %cNIPS %f/NIPS/NIPS-2002-5511.pdf %*Maximum Likelihood and the Information Bottleneck %@Noam Slonim,Yair Weiss %t2002 %cNIPS %f/NIPS/NIPS-2002-5512.pdf %*Concentration Inequalities for the Missing Mass and for Histogram Rule Error %@Luis E. Ortiz,David A. McAllester %t2002 %cNIPS %f/NIPS/NIPS-2002-5513.pdf %*Dyadic Classification Trees via Structural Risk Minimization %@Clayton Scott,Robert Nowak %t2002 %cNIPS %f/NIPS/NIPS-2002-5514.pdf %*The Stability of Kernel Principal Components Analysis and its Relation to the Process Eigenspectrum %@Christopher Williams,John S. Shawe-taylor %t2002 %cNIPS %f/NIPS/NIPS-2002-5515.pdf %*Information Diffusion Kernels %@Guy Lebanon,John D. Lafferty %t2002 %cNIPS %f/NIPS/NIPS-2002-5516.pdf %*The Effect of Singularities in a Learning Machine when the True Parameters Do Not Lie on such Singularities %@Sumio Watanabe,Shun-ichi Amari %t2002 %cNIPS %f/NIPS/NIPS-2002-5517.pdf %*On the Complexity of Learning the Kernel Matrix %@Olivier Bousquet,Daniel Herrmann %t2002 %cNIPS %f/NIPS/NIPS-2002-5518.pdf %*Rate Distortion Function in the Spin Glass State: A Toy Model %@Tatsuto Murayama,Masato Okada %t2002 %cNIPS %f/NIPS/NIPS-2002-5519.pdf %*Conditional Models on the Ranking Poset %@Guy Lebanon,John D. Lafferty %t2002 %cNIPS %f/NIPS/NIPS-2002-5520.pdf %*Fractional Belief Propagation %@Wim Wiegerinck,Tom Heskes %t2002 %cNIPS %f/NIPS/NIPS-2002-5521.pdf %*PAC-Bayes & Margins %@John Langford,John Shawe-Taylor %t2002 %cNIPS %f/NIPS/NIPS-2002-5522.pdf %*A Note on the Representational Incompatibility of Function Approximation and Factored Dynamics %@Eric Allender,Sanjeev Arora,Michael Kearns,Cristopher Moore,Alexander Russell %t2002 %cNIPS %f/NIPS/NIPS-2002-5523.pdf %*Margin Analysis of the LVQ Algorithm %@Koby Crammer,Ran Gilad-bachrach,Amir Navot,Naftali Tishby %t2002 %cNIPS %f/NIPS/NIPS-2002-5524.pdf %*Margin-Based Algorithms for Information Filtering %@Nicolò Cesa-bianchi,Alex Conconi,Claudio Gentile %t2002 %cNIPS %f/NIPS/NIPS-2002-5525.pdf %*Hyperkernels %@Cheng S. Ong,Robert C. Williamson,Alex J. Smola %t2002 %cNIPS %f/NIPS/NIPS-2002-5526.pdf %*Bayesian Monte Carlo %@Zoubin Ghahramani,Carl E. Rasmussen %t2002 %cNIPS %f/NIPS/NIPS-2002-5527.pdf %*Mean Field Approach to a Probabilistic Model in Information Retrieval %@Bin Wu,K. Wong,David Bodoff %t2002 %cNIPS %f/NIPS/NIPS-2002-5528.pdf %*Distance Metric Learning with Application to Clustering with Side-Information %@Eric P. Xing,Michael I. Jordan,Stuart J. Russell,Andrew Y. Ng %t2002 %cNIPS %f/NIPS/NIPS-2002-5529.pdf %*Adapting Codes and Embeddings for Polychotomies %@Gunnar Rätsch,Sebastian Mika,Alex J. Smola %t2002 %cNIPS %f/NIPS/NIPS-2002-5530.pdf %*Knowledge-Based Support Vector Machine Classifiers %@Glenn M. Fung,Olvi L. Mangasarian,Jude W. Shavlik %t2002 %cNIPS %f/NIPS/NIPS-2002-5531.pdf %*Gaussian Process Priors with Uncertain Inputs Application to Multiple-Step Ahead Time Series Forecasting %@Agathe Girard,Carl Edward Rasmussen,Joaquin Quiñonero Candela,Roderick Murray-Smith %t2002 %cNIPS %f/NIPS/NIPS-2002-5532.pdf %*Kernel Design Using Boosting %@Koby Crammer,Joseph Keshet,Yoram Singer %t2002 %cNIPS %f/NIPS/NIPS-2002-5533.pdf %*Coulomb Classifiers: Generalizing Support Vector Machines via an Analogy to Electrostatic Systems %@Sepp Hochreiter,Michael C. Mozer,Klaus Obermayer %t2002 %cNIPS %f/NIPS/NIPS-2002-5534.pdf %*Adaptive Scaling for Feature Selection in SVMs %@Yves Grandvalet,Stéphane Canu %t2002 %cNIPS %f/NIPS/NIPS-2002-5535.pdf %*Support Vector Machines for Multiple-Instance Learning %@Stuart Andrews,Ioannis Tsochantaridis,Thomas Hofmann %t2002 %cNIPS %f/NIPS/NIPS-2002-5536.pdf %*Fast Kernels for String and Tree Matching %@Alex J. Smola,S.v.n. Vishwanathan %t2002 %cNIPS %f/NIPS/NIPS-2002-5537.pdf %*Cluster Kernels for Semi-Supervised Learning %@Olivier Chapelle,Jason Weston,Bernhard Schölkopf %t2002 %cNIPS %f/NIPS/NIPS-2002-5538.pdf %*Rational Kernels %@Corinna Cortes,Patrick Haffner,Mehryar Mohri %t2002 %cNIPS %f/NIPS/NIPS-2002-5539.pdf %*Fast Sparse Gaussian Process Methods: The Informative Vector Machine %@Ralf Herbrich,Neil D. Lawrence,Matthias Seeger %t2002 %cNIPS %f/NIPS/NIPS-2002-5540.pdf %*Stability-Based Model Selection %@Tilman Lange,Mikio L. Braun,Volker Roth,Joachim M. Buhmann %t2002 %cNIPS %f/NIPS/NIPS-2002-5541.pdf %*Feature Selection in Mixture-Based Clustering %@Martin H. Law,Anil K. Jain,Mário Figueiredo %t2002 %cNIPS %f/NIPS/NIPS-2002-5542.pdf %*String Kernels, Fisher Kernels and Finite State Automata %@Craig Saunders,Alexei Vinokourov,John S. Shawe-taylor %t2002 %cNIPS %f/NIPS/NIPS-2002-5543.pdf %*Boosting Density Estimation %@Saharon Rosset,Eran Segal %t2002 %cNIPS %f/NIPS/NIPS-2002-5544.pdf %*Independent Components Analysis through Product Density Estimation %@Trevor Hastie,Rob Tibshirani %t2002 %cNIPS %f/NIPS/NIPS-2002-5545.pdf %*Learning Semantic Similarity %@Jaz Kandola,Nello Cristianini,John S. Shawe-taylor %t2002 %cNIPS %f/NIPS/NIPS-2002-5546.pdf %*Self Supervised Boosting %@Max Welling,Richard S. Zemel,Geoffrey E. Hinton %t2002 %cNIPS %f/NIPS/NIPS-2002-5547.pdf %*Automatic Derivation of Statistical Algorithms: The EM Family and Beyond %@Bernd Fischer,Johann Schumann,Wray Buntine,Alexander G. Gray %t2002 %cNIPS %f/NIPS/NIPS-2002-5548.pdf %*Half-Lives of EigenFlows for Spectral Clustering %@Chakra Chennubhotla,Allan D. Jepson %t2002 %cNIPS %f/NIPS/NIPS-2002-5549.pdf %*On the Dirichlet Prior and Bayesian Regularization %@Harald Steck,Tommi S. Jaakkola %t2002 %cNIPS %f/NIPS/NIPS-2002-5550.pdf %*Global Versus Local Methods in Nonlinear Dimensionality Reduction %@Vin D. Silva,Joshua B. Tenenbaum %t2002 %cNIPS %f/NIPS/NIPS-2002-5551.pdf %*Parametric Mixture Models for Multi-Labeled Text %@Naonori Ueda,Kazumi Saito %t2002 %cNIPS %f/NIPS/NIPS-2002-5552.pdf %*Clustering with the Fisher Score %@Koji Tsuda,Motoaki Kawanabe,Klaus-Robert Müller %t2002 %cNIPS %f/NIPS/NIPS-2002-5553.pdf %*Adaptive Classification by Variational Kalman Filtering %@Peter Sykacek,Stephen J. Roberts %t2002 %cNIPS %f/NIPS/NIPS-2002-5554.pdf %*Boosted Dyadic Kernel Discriminants %@Baback Moghaddam,Gregory Shakhnarovich %t2002 %cNIPS %f/NIPS/NIPS-2002-5555.pdf %*Regularized Greedy Importance Sampling %@Finnegan Southey,Dale Schuurmans,Ali Ghodsi %t2002 %cNIPS %f/NIPS/NIPS-2002-5556.pdf %*One-Class LP Classifiers for Dissimilarity Representations %@Elzbieta Pekalska,David M.J. Tax,Robert Duin %t2002 %cNIPS %f/NIPS/NIPS-2002-5557.pdf %*A Formulation for Minimax Probability Machine Regression %@Thomas Strohmann,Gregory Z. Grudic %t2002 %cNIPS %f/NIPS/NIPS-2002-5558.pdf %*VIBES: A Variational Inference Engine for Bayesian Networks %@Christopher M. Bishop,David Spiegelhalter,John Winn %t2002 %cNIPS %f/NIPS/NIPS-2002-5559.pdf %*A Differential Semantics for Jointree Algorithms %@James D. Park,Adnan Darwiche %t2002 %cNIPS %f/NIPS/NIPS-2002-5560.pdf %*Constraint Classification for Multiclass Classification and Ranking %@Sariel Har-Peled,Dan Roth,Dav Zimak %t2002 %cNIPS %f/NIPS/NIPS-2002-5561.pdf %*Nash Propagation for Loopy Graphical Games %@Luis E. Ortiz,Michael Kearns %t2002 %cNIPS %f/NIPS/NIPS-2002-5562.pdf %*Using Tarjan's Red Rule for Fast Dependency Tree Construction %@Dan Pelleg,Andrew W. Moore %t2002 %cNIPS %f/NIPS/NIPS-2002-5563.pdf %*Exact MAP Estimates by (Hyper)tree Agreement %@Martin J. Wainwright,Tommi S. Jaakkola,Alan S. Willsky %t2002 %cNIPS %f/NIPS/NIPS-2002-5564.pdf %*Going Metric: Denoising Pairwise Data %@Volker Roth,Julian Laub,Klaus-Robert Müller,Joachim M. Buhmann %t2002 %cNIPS %f/NIPS/NIPS-2002-5565.pdf %*Manifold Parzen Windows %@Pascal Vincent,Yoshua Bengio %t2002 %cNIPS %f/NIPS/NIPS-2002-5566.pdf %*Stochastic Neighbor Embedding %@Geoffrey E. Hinton,Sam T. Roweis %t2002 %cNIPS %f/NIPS/NIPS-2002-5567.pdf %*Automatic Alignment of Local Representations %@Yee W. Teh,Sam T. Roweis %t2002 %cNIPS %f/NIPS/NIPS-2002-5568.pdf %*Extracting Relevant Structures with Side Information %@Gal Chechik,Naftali Tishby %t2002 %cNIPS %f/NIPS/NIPS-2002-5569.pdf %*Critical Lines in Symmetry of Mixture Models and its Application to Component Splitting %@Kenji Fukumizu,Shotaro Akaho,Shun-ichi Amari %t2002 %cNIPS %f/NIPS/NIPS-2002-5570.pdf %*Kernel Dependency Estimation %@Jason Weston,Olivier Chapelle,Vladimir Vapnik,André Elisseeff,Bernhard Schölkopf %t2002 %cNIPS %f/NIPS/NIPS-2002-5571.pdf %*Handling Missing Data with Variational Bayesian Learning of ICA %@Kwokleung Chan,Te-Won Lee,Terrence J. Sejnowski %t2002 %cNIPS %f/NIPS/NIPS-2002-5572.pdf %*Feature Selection and Classification on Matrix Data: From Large Margins to Small Covering Numbers %@Sepp Hochreiter,Klaus Obermayer %t2002 %cNIPS %f/NIPS/NIPS-2002-5573.pdf %*Learning with Multiple Labels %@Rong Jin,Zoubin Ghahramani %t2002 %cNIPS %f/NIPS/NIPS-2002-5574.pdf %*Robust Novelty Detection with Single-Class MPM %@Laurent E. Ghaoui,Michael I. Jordan,Gert R. Lanckriet %t2002 %cNIPS %f/NIPS/NIPS-2002-5575.pdf %*Artefactual Structure from Least-Squares Multidimensional Scaling %@Nicholas P. Hughes,David Lowe %t2002 %cNIPS %f/NIPS/NIPS-2002-5576.pdf %*The Decision List Machine %@Marina Sokolova,Mario Marchand,Nathalie Japkowicz,John S. Shawe-taylor %t2002 %cNIPS %f/NIPS/NIPS-2002-5577.pdf %*Using Manifold Stucture for Partially Labeled Classification %@Mikhail Belkin,Partha Niyogi %t2002 %cNIPS %f/NIPS/NIPS-2002-5578.pdf %*Ranking with Large Margin Principle: Two Approaches %@Amnon Shashua,Anat Levin %t2002 %cNIPS %f/NIPS/NIPS-2002-5579.pdf %*Multiclass Learning by Probabilistic Embeddings %@Ofer Dekel,Yoram Singer %t2002 %cNIPS %f/NIPS/NIPS-2002-5580.pdf %*Transductive and Inductive Methods for Approximate Gaussian Process Regression %@Anton Schwaighofer,Volker Tresp %t2002 %cNIPS %f/NIPS/NIPS-2002-5581.pdf %*Annealing and the Rate Distortion Problem %@Albert E. Parker,Tomá\v S. Gedeon,Alexander G. Dimitrov %t2002 %cNIPS %f/NIPS/NIPS-2002-5582.pdf %*Discriminative Learning for Label Sequences via Boosting %@Yasemin Altun,Thomas Hofmann,Mark Johnson %t2002 %cNIPS %f/NIPS/NIPS-2002-5583.pdf %*Discriminative Densities from Maximum Contrast Estimation %@Peter Meinicke,Thorsten Twellmann,Helge Ritter %t2002 %cNIPS %f/NIPS/NIPS-2002-5584.pdf %*FloatBoost Learning for Classification %@Stan Z. Li,Zhenqiu Zhang,Heung-yeung Shum,Hongjiang Zhang %t2002 %cNIPS %f/NIPS/NIPS-2002-5585.pdf %*Incremental Gaussian Processes %@Joaquin Quiñonero-candela,Ole Winther %t2002 %cNIPS %f/NIPS/NIPS-2002-5586.pdf %*Learning Graphical Models with Mercer Kernels %@Francis R. Bach,Michael I. Jordan %t2002 %cNIPS %f/NIPS/NIPS-2002-5587.pdf %*Multiple Cause Vector Quantization %@David A. Ross,Richard S. Zemel %t2002 %cNIPS %f/NIPS/NIPS-2002-5588.pdf %*Information Regularization with Partially Labeled Data %@Martin Szummer,Tommi S. Jaakkola %t2002 %cNIPS %f/NIPS/NIPS-2002-5589.pdf %*Derivative Observations in Gaussian Process Models of Dynamic Systems %@E. Solak,R. Murray-smith,W. E. Leithead,D. J. Leith,Carl E. Rasmussen %t2002 %cNIPS %f/NIPS/NIPS-2002-5590.pdf %*Multiplicative Updates for Nonnegative Quadratic Programming in Support Vector Machines %@Fei Sha,Lawrence K. Saul,Daniel D. Lee %t2002 %cNIPS %f/NIPS/NIPS-2002-5591.pdf %*Location Estimation with a Differential Update Network %@Ali Rahimi,Trevor Darrell %t2002 %cNIPS %f/NIPS/NIPS-2002-5592.pdf %*Real-Time Particle Filters %@Cody Kwok,Dieter Fox,Marina Meila %t2002 %cNIPS %f/NIPS/NIPS-2002-5593.pdf %*Optoelectronic Implementation of a FitzHugh-Nagumo Neural Model %@Alexandre R. Romariz,Kelvin Wagner %t2002 %cNIPS %f/NIPS/NIPS-2002-5594.pdf %*Circuit Model of Short-Term Synaptic Dynamics %@Shih-Chii Liu,Malte Boegershausen,Pascal Suter %t2002 %cNIPS %f/NIPS/NIPS-2002-5595.pdf %*Adaptive Quantization and Density Estimation in Silicon %@David Hsu,Seth Bridges,Miguel Figueroa,Chris Diorio %t2002 %cNIPS %f/NIPS/NIPS-2002-5596.pdf %*Retinal Processing Emulation in a Programmable 2-Layer Analog Array Processor CMOS Chip %@R. Carmona,F. Jiménez-garrido,R. Dominguez-castro,S. Espejo,A. Rodriguez-vázquez %t2002 %cNIPS %f/NIPS/NIPS-2002-5597.pdf %*Improving Transfer Rates in Brain Computer Interfacing: A Case Study %@Peter Meinicke,Matthias Kaper,Florian Hoppe,Manfred Heumann,Helge Ritter %t2002 %cNIPS %f/NIPS/NIPS-2002-5598.pdf %*Combining Features for BCI %@Guido Dornhege,Benjamin Blankertz,Gabriel Curio,Klaus-Robert Müller %t2002 %cNIPS %f/NIPS/NIPS-2002-5599.pdf %*Classifying Patterns of Visual Motion - a Neuromorphic Approach %@Jakob Heinzle,Alan Stocker %t2002 %cNIPS %f/NIPS/NIPS-2002-5600.pdf %*Developing Topography and Ocular Dominance Using Two aVLSI Vision Sensors and a Neurotrophic Model of Plasticity %@Terry Elliott,Jörg Kramer %t2002 %cNIPS %f/NIPS/NIPS-2002-5601.pdf %*Topographic Map Formation by Silicon Growth Cones %@Brian Taba,Kwabena A. Boahen %t2002 %cNIPS %f/NIPS/NIPS-2002-5602.pdf %*Spike Timing-Dependent Plasticity in the Address Domain %@R. J. Vogelstein,Francesco Tenore,Ralf Philipp,Miriam S. Adlerstein,David H. Goldberg,Gert Cauwenberghs %t2002 %cNIPS %f/NIPS/NIPS-2002-5603.pdf %*Field-Programmable Learning Arrays %@Seth Bridges,Miguel Figueroa,Chris Diorio,David Hsu %t2002 %cNIPS %f/NIPS/NIPS-2002-5604.pdf %*Forward-Decoding Kernel-Based Phone Recognition %@Shantanu Chakrabartty,Gert Cauwenberghs %t2002 %cNIPS %f/NIPS/NIPS-2002-5605.pdf %*A Probabilistic Approach to Single Channel Blind Signal Separation %@Gil-jin Jang,Te-Won Lee %t2002 %cNIPS %f/NIPS/NIPS-2002-5606.pdf %*Real Time Voice Processing with Audiovisual Feedback: Toward Autonomous Agents with Perfect Pitch %@Lawrence K. Saul,Daniel D. Lee,Charles L. Isbell,Yann L. Cun %t2002 %cNIPS %f/NIPS/NIPS-2002-5607.pdf %*Analysis of Information in Speech Based on MANOVA %@Sachin S. Kajarekar,Hynek Hermansky %t2002 %cNIPS %f/NIPS/NIPS-2002-5608.pdf %*Bayesian Estimation of Time-Frequency Coefficients for Audio Signal Enhancement %@Patrick J. Wolfe,Simon J. Godsill %t2002 %cNIPS %f/NIPS/NIPS-2002-5609.pdf %*Monaural Speech Separation %@Guoning Hu,Deliang Wang %t2002 %cNIPS %f/NIPS/NIPS-2002-5610.pdf %*Discriminative Binaural Sound Localization %@Ehud Ben-reuven,Yoram Singer %t2002 %cNIPS %f/NIPS/NIPS-2002-5611.pdf %*Application of Variational Bayesian Approach to Speech Recognition %@Shinji Watanabe,Yasuhiro Minami,Atsushi Nakamura,Naonori Ueda %t2002 %cNIPS %f/NIPS/NIPS-2002-5612.pdf %*Learning to Perceive Transparency from the Statistics of Natural Scenes %@Anat Levin,Assaf Zomet,Yair Weiss %t2002 %cNIPS %f/NIPS/NIPS-2002-5613.pdf %*Learning to Detect Natural Image Boundaries Using Brightness and Texture %@David R. Martin,Charless C. Fowlkes,Jitendra Malik %t2002 %cNIPS %f/NIPS/NIPS-2002-5614.pdf %*Fast Transformation-Invariant Factor Analysis %@Anitha Kannan,Nebojsa Jojic,Brendan Frey %t2002 %cNIPS %f/NIPS/NIPS-2002-5615.pdf %*A Prototype for Automatic Recognition of Spontaneous Facial Actions %@M.S. Bartlett,G.C. Littlewort,T.J. Sejnowski,J.R. Movellan %t2002 %cNIPS %f/NIPS/NIPS-2002-5616.pdf %*Bayesian Image Super-Resolution %@Michael E. Tipping,Christopher M. Bishop %t2002 %cNIPS %f/NIPS/NIPS-2002-5617.pdf %*A Bilinear Model for Sparse Coding %@David B. Grimes,Rajesh P. N. Rao %t2002 %cNIPS %f/NIPS/NIPS-2002-5618.pdf %*Unsupervised Color Constancy %@Kinh Tieu,Erik G. Miller %t2002 %cNIPS %f/NIPS/NIPS-2002-5619.pdf %*Recovering Articulated Model Topology from Observed Rigid Motion %@Leonid Taycher,John Iii,Trevor Darrell %t2002 %cNIPS %f/NIPS/NIPS-2002-5620.pdf %*Linear Combinations of Optic Flow Vectors for Estimating Self-Motion - a Real-World Test of a Neural Model %@Matthias O. Franz,Javaan S. Chahl %t2002 %cNIPS %f/NIPS/NIPS-2002-5621.pdf %*Learning Sparse Multiscale Image Representations %@Phil Sallee,Bruno A. Olshausen %t2002 %cNIPS %f/NIPS/NIPS-2002-5622.pdf %*Shape Recipes: Scene Representations that Refer to the Image %@William T. Freeman,Antonio Torralba %t2002 %cNIPS %f/NIPS/NIPS-2002-5623.pdf %*Recovering Intrinsic Images from a Single Image %@Marshall F. Tappen,William T. Freeman,Edward H. Adelson %t2002 %cNIPS %f/NIPS/NIPS-2002-5624.pdf %*Learning Sparse Topographic Representations with Products of Student-t Distributions %@Max Welling,Simon Osindero,Geoffrey E. Hinton %t2002 %cNIPS %f/NIPS/NIPS-2002-5625.pdf %*A Model for Learning Variance Components of Natural Images %@Yan Karklin,Michael S. Lewicki %t2002 %cNIPS %f/NIPS/NIPS-2002-5626.pdf %*How to Combine Color and Shape Information for 3D Object Recognition: Kernels do the Trick %@B. Caputo,Gy. Dorkó %t2002 %cNIPS %f/NIPS/NIPS-2002-5627.pdf %*Concurrent Object Recognition and Segmentation by Graph Partitioning %@Stella X. Yu,Ralph Gross,Jianbo Shi %t2002 %cNIPS %f/NIPS/NIPS-2002-5628.pdf %*Learning About Multiple Objects in Images: Factorial Learning without Factorial Search %@Christopher K. I. Williams,Michalis K. Titsias %t2002 %cNIPS %f/NIPS/NIPS-2002-5629.pdf %*Identity Uncertainty and Citation Matching %@Hanna Pasula,Bhaskara Marthi,Brian Milch,Stuart J. Russell,Ilya Shpitser %t2002 %cNIPS %f/NIPS/NIPS-2002-5630.pdf %*The RA Scanner: Prediction of Rheumatoid Joint Inflammation Based on Laser Imaging %@Anton Schwaighofer,Volker Tresp,Peter Mayer,Alexander K. Scheel,Gerhard A. Müller %t2002 %cNIPS %f/NIPS/NIPS-2002-5631.pdf %*Mismatch String Kernels for SVM Protein Classification %@Eleazar Eskin,Jason Weston,William S. Noble,Christina S. Leslie %t2002 %cNIPS %f/NIPS/NIPS-2002-5632.pdf %*Graph-Driven Feature Extraction From Microarray Data Using Diffusion Kernels and Kernel CCA %@Jean-philippe Vert,Minoru Kanehisa %t2002 %cNIPS %f/NIPS/NIPS-2002-5633.pdf %*Real-Time Monitoring of Complex Industrial Processes with Particle Filters %@Rubén Morales-Menéndez,Nando de Freitas,David Poole %t2002 %cNIPS %f/NIPS/NIPS-2002-5634.pdf %*A Maximum Entropy Approach to Collaborative Filtering in Dynamic, Sparse, High-Dimensional Domains %@Dmitry Y. Pavlov,David M. Pennock %t2002 %cNIPS %f/NIPS/NIPS-2002-5635.pdf %*Prediction of Protein Topologies Using Generalized IOHMMs and RNNs %@Gianluca Pollastri,Pierre Baldi,Alessandro Vullo,Paolo Frasconi %t2002 %cNIPS %f/NIPS/NIPS-2002-5636.pdf %*Approximate Inference and Protein-Folding %@Chen Yanover,Yair Weiss %t2002 %cNIPS %f/NIPS/NIPS-2002-5637.pdf %*Adaptive Caching by Refetching %@Robert B. Gramacy,Manfred K. Warmuth,Scott A. Brandt,Ismail Ari %t2002 %cNIPS %f/NIPS/NIPS-2002-5638.pdf %*Inferring a Semantic Representation of Text via Cross-Language Correlation Analysis %@Alexei Vinokourov,Nello Cristianini,John Shawe-Taylor %t2002 %cNIPS %f/NIPS/NIPS-2002-5639.pdf %*A Hierarchical Bayesian Markovian Model for Motifs in Biopolymer Sequences %@Eric P. Xing,Michael I. Jordan,Richard M. Karp,Stuart J. Russell %t2002 %cNIPS %f/NIPS/NIPS-2002-5640.pdf %*Learning to Classify Galaxy Shapes Using the EM Algorithm %@Sergey Kirshner,Igor V. Cadez,Padhraic Smyth,Chandrika Kamath %t2002 %cNIPS %f/NIPS/NIPS-2002-5641.pdf %*"Name That Song!" A Probabilistic Approach to Querying on Music and Text %@Brochu Eric,Nando de Freitas %t2002 %cNIPS %f/NIPS/NIPS-2002-5642.pdf %*A Probabilistic Model for Learning Concatenative Morphology %@Matthew G. Snover,Michael R. Brent %t2002 %cNIPS %f/NIPS/NIPS-2002-5643.pdf %*Learning Attractor Landscapes for Learning Motor Primitives %@Auke J. Ijspeert,Jun Nakanishi,Stefan Schaal %t2002 %cNIPS %f/NIPS/NIPS-2002-5644.pdf %*Learning a Forward Model of a Reflex %@Bernd Porr,Florentin Wörgötter %t2002 %cNIPS %f/NIPS/NIPS-2002-5645.pdf %*Minimax Differential Dynamic Programming: An Application to Robust Biped Walking %@Jun Morimoto,Christopher G. Atkeson %t2002 %cNIPS %f/NIPS/NIPS-2002-5646.pdf %*Value-Directed Compression of POMDPs %@Pascal Poupart,Craig Boutilier %t2002 %cNIPS %f/NIPS/NIPS-2002-5647.pdf %*Speeding up the Parti-Game Algorithm %@Maxim Likhachev,Sven Koenig %t2002 %cNIPS %f/NIPS/NIPS-2002-5648.pdf %*Reinforcement Learning to Play an Optimal Nash Equilibrium in Team Markov Games %@Xiaofeng Wang,Tuomas Sandholm %t2002 %cNIPS %f/NIPS/NIPS-2002-5649.pdf %*Convergent Combinations of Reinforcement Learning with Linear Function Approximation %@Ralf Schoknecht,Artur Merke %t2002 %cNIPS %f/NIPS/NIPS-2002-5650.pdf %*Approximate Linear Programming for Average-Cost Dynamic Programming %@Benjamin V. Roy,Daniela D. Farias %t2002 %cNIPS %f/NIPS/NIPS-2002-5651.pdf %*A Convergent Form of Approximate Policy Iteration %@Theodore J. Perkins,Doina Precup %t2002 %cNIPS %f/NIPS/NIPS-2002-5652.pdf %*Efficient Learning Equilibrium %@Ronen I. Brafman,Moshe Tennenholtz %t2002 %cNIPS %f/NIPS/NIPS-2002-5653.pdf %*Nonparametric Representation of Policies and Value Functions: A Trajectory-Based Approach %@Christopher G. Atkeson,Jun Morimoto %t2002 %cNIPS %f/NIPS/NIPS-2002-5654.pdf %*Learning to Take Concurrent Actions %@Khashayar Rohanimanesh,Sridhar Mahadevan %t2002 %cNIPS %f/NIPS/NIPS-2002-5655.pdf %*Learning in Zero-Sum Team Markov Games Using Factored Value Functions %@Michail G. Lagoudakis,Ronald Parr %t2002 %cNIPS %f/NIPS/NIPS-2002-5656.pdf %*Exponential Family PCA for Belief Compression in POMDPs %@Nicholas Roy,Geoffrey J. Gordon %t2002 %cNIPS %f/NIPS/NIPS-2002-5657.pdf %*Modeling Temporal Structure in Classical Conditioning %@Aaron C. Courville,David S. Touretzky %t2001 %cNIPS %f/NIPS/NIPS-2001-5658.pdf %*Probabilistic principles in unsupervised learning of visual structure: human data and a model %@Shimon Edelman,Benjamin P. Hiles,Hwajin Yang,Nathan Intrator %t2001 %cNIPS %f/NIPS/NIPS-2001-5659.pdf %*Fragment Completion in Humans and Machines %@David Jacobs,Bas Rokers,Archisman Rudra,Zili Liu %t2001 %cNIPS %f/NIPS/NIPS-2001-5660.pdf %*Natural Language Grammar Induction Using a Constituent-Context Model %@Dan Klein,Christopher D. Manning %t2001 %cNIPS %f/NIPS/NIPS-2001-5661.pdf %*The Emergence of Multiple Movement Units in the Presence of Noise and Feedback Delay %@Michael Kositsky,Andrew G. Barto %t2001 %cNIPS %f/NIPS/NIPS-2001-5662.pdf %*A Rational Analysis of Cognitive Control in a Speeded Discrimination Task %@Michael C. Mozer,Michael D. Colagrosso,David E. Huber %t2001 %cNIPS %f/NIPS/NIPS-2001-5663.pdf %*A Bayesian Model Predicts Human Parse Preference and Reading Times in Sentence Processing %@S. Narayanan,Daniel Jurafsky %t2001 %cNIPS %f/NIPS/NIPS-2001-5664.pdf %*Grammar Transfer in a Second Order Recurrent Neural Network %@Michiro Negishi,Stephen J. Hanson %t2001 %cNIPS %f/NIPS/NIPS-2001-5665.pdf %*Generalizable Relational Binding from Coarse-coded Distributed Representations %@Randall C. O'Reilly,R. S. Busby %t2001 %cNIPS %f/NIPS/NIPS-2001-5666.pdf %*A Model of the Phonological Loop: Generalization and Binding %@Randall C. O'Reilly,R. Soto %t2001 %cNIPS %f/NIPS/NIPS-2001-5667.pdf %*Reinforcement Learning and Time Perception -- a Model of Animal Experiments %@Jonathan L. Shapiro,J. Wearden %t2001 %cNIPS %f/NIPS/NIPS-2001-5668.pdf %*A Quantitative Model of Counterfactual Reasoning %@Daniel Yarlett,Michael Ramscar %t2001 %cNIPS %f/NIPS/NIPS-2001-5669.pdf %*Bayesian morphometry of hippocampal cells suggests same-cell somatodendritic repulsion %@Giorgio A. Ascoli,Alexei V. Samsonovich %t2001 %cNIPS %f/NIPS/NIPS-2001-5670.pdf %*Modularity in the motor system: decomposition of muscle patterns as combinations of time-varying synergies %@A. D'avella,M. C. Tresch %t2001 %cNIPS %f/NIPS/NIPS-2001-5671.pdf %*Receptive field structure of flow detectors for heading perception %@J. A. Beintema,M. Lappe,Alexander C. Berg %t2001 %cNIPS %f/NIPS/NIPS-2001-5672.pdf %*Classifying Single Trial EEG: Towards Brain Computer Interfacing %@Benjamin Blankertz,Gabriel Curio,Klaus-Robert Müller %t2001 %cNIPS %f/NIPS/NIPS-2001-5673.pdf %*Orientational and Geometric Determinants of Place and Head-direction %@Neil Burgess,Tom Hartley %t2001 %cNIPS %f/NIPS/NIPS-2001-5674.pdf %*Group Redundancy Measures Reveal Redundancy Reduction in the Auditory Pathway %@Gal Chechik,Amir Globerson,M. J. Anderson,E. D. Young,Israel Nelken,Naftali Tishby %t2001 %cNIPS %f/NIPS/NIPS-2001-5675.pdf %*A Maximum-Likelihood Approach to Modeling Multisensory Enhancement %@H. Colonius,A. Diederich %t2001 %cNIPS %f/NIPS/NIPS-2001-5676.pdf %*ACh, Uncertainty, and Cortical Inference %@Peter Dayan,Angela J. Yu %t2001 %cNIPS %f/NIPS/NIPS-2001-5677.pdf %*Linking Motor Learning to Function Approximation: Learning in an Unlearnable Force Field %@O. Donchin,Reza Shadmehr %t2001 %cNIPS %f/NIPS/NIPS-2001-5678.pdf %*Exact differential equation population dynamics for integrate-and-fire neurons %@Julian Eggert,Berthold Bäuml %t2001 %cNIPS %f/NIPS/NIPS-2001-5679.pdf %*Probabilistic Inference of Hand Motion from Neural Activity in Motor Cortex %@Yun Gao,Michael J. Black,Elie Bienenstock,Shy Shoham,John P. Donoghue %t2001 %cNIPS %f/NIPS/NIPS-2001-5680.pdf %*A theory of neural integration in the head-direction system %@Richard Hahnloser,Xiaohui Xie,H. S. Seung %t2001 %cNIPS %f/NIPS/NIPS-2001-5681.pdf %*3 state neurons for contextual processing %@Ádám Kepecs,S. Raghavachari %t2001 %cNIPS %f/NIPS/NIPS-2001-5682.pdf %*Self-regulation Mechanism of Temporally Asymmetric Hebbian Plasticity %@N. Matsumoto,M. Okada %t2001 %cNIPS %f/NIPS/NIPS-2001-5683.pdf %*Information-Geometric Decomposition in Spike Analysis %@Hiroyuki Nakahara,Shun-ichi Amari %t2001 %cNIPS %f/NIPS/NIPS-2001-5684.pdf %*Eye movements and the maturation of cortical orientation selectivity %@Antonino Casile,Michele Rucci %t2001 %cNIPS %f/NIPS/NIPS-2001-5685.pdf %*Characterizing Neural Gain Control using Spike-triggered Covariance %@Odelia Schwartz,E. J. Chichilnisky,Eero P. Simoncelli %t2001 %cNIPS %f/NIPS/NIPS-2001-5686.pdf %*Correlation Codes in Neuronal Populations %@Maoz Shamir,Haim Sompolinsky %t2001 %cNIPS %f/NIPS/NIPS-2001-5687.pdf %*Why Neuronal Dynamics Should Control Synaptic Learning Rules %@Jesper Tegnér,Ádám Kepecs %t2001 %cNIPS %f/NIPS/NIPS-2001-5688.pdf %*Effective Size of Receptive Fields of Inferior Temporal Visual Cortex Neurons in Natural Scenes %@Thomas P. Trappenberg,Edmund T. Rolls,Simon M. Stringer %t2001 %cNIPS %f/NIPS/NIPS-2001-5689.pdf %*Activity Driven Adaptive Stochastic Resonance %@Gregor Wenning,Klaus Obermayer %t2001 %cNIPS %f/NIPS/NIPS-2001-5690.pdf %*Spike timing and the coding of naturalistic sounds in a central auditory area of songbirds %@B. D. Wright,Kamal Sen,William Bialek,A. J. Doupe %t2001 %cNIPS %f/NIPS/NIPS-2001-5691.pdf %*Neural Implementation of Bayesian Inference in Population Codes %@Si Wu,Shun-ichi Amari %t2001 %cNIPS %f/NIPS/NIPS-2001-5692.pdf %*Generating velocity tuning by asymmetric recurrent connections %@Xiaohui Xie,Martin A. Giese %t2001 %cNIPS %f/NIPS/NIPS-2001-5693.pdf %*Sampling Techniques for Kernel Methods %@Dimitris Achlioptas,Frank Mcsherry,Bernhard Schölkopf %t2001 %cNIPS %f/NIPS/NIPS-2001-5694.pdf %*Geometrical Singularities in the Neuromanifold of Multilayer Perceptrons %@Shun-ichi Amari,Hyeyoung Park,Tomoko Ozeki %t2001 %cNIPS %f/NIPS/NIPS-2001-5695.pdf %*The Noisy Euclidean Traveling Salesman Problem and Learning %@Mikio L. Braun,Joachim M. Buhmann %t2001 %cNIPS %f/NIPS/NIPS-2001-5696.pdf %*On the Generalization Ability of On-Line Learning Algorithms %@Nicolò Cesa-bianchi,Alex Conconi,Claudio Gentile %t2001 %cNIPS %f/NIPS/NIPS-2001-5697.pdf %*On Kernel-Target Alignment %@Nello Cristianini,John Shawe-Taylor,André Elisseeff,Jaz S. Kandola %t2001 %cNIPS %f/NIPS/NIPS-2001-5698.pdf %*PAC Generalization Bounds for Co-training %@Sanjoy Dasgupta,Michael L. Littman,David A. McAllester %t2001 %cNIPS %f/NIPS/NIPS-2001-5699.pdf %*Analysis of Sparse Bayesian Learning %@Anita C. Faul,Michael E. Tipping %t2001 %cNIPS %f/NIPS/NIPS-2001-5700.pdf %*Algorithmic Luckiness %@Ralf Herbrich,Robert C. Williamson %t2001 %cNIPS %f/NIPS/NIPS-2001-5701.pdf %*Information Geometrical Framework for Analyzing Belief Propagation Decoder %@Shiro Ikeda,Toshiyuki Tanaka,Shun-ichi Amari %t2001 %cNIPS %f/NIPS/NIPS-2001-5702.pdf %*Novel iteration schemes for the Cluster Variation Method %@Hilbert J. Kappen,Wim Wiegerinck %t2001 %cNIPS %f/NIPS/NIPS-2001-5703.pdf %*Efficiency versus Convergence of Boolean Kernels for On-Line Learning Algorithms %@Roni Khardon,Dan Roth,Rocco A. Servedio %t2001 %cNIPS %f/NIPS/NIPS-2001-5704.pdf %*Kernel Machines and Boolean Functions %@Adam Kowalczyk,Alex J. Smola,Robert C. Williamson %t2001 %cNIPS %f/NIPS/NIPS-2001-5705.pdf %*Boosting and Maximum Likelihood for Exponential Models %@Guy Lebanon,John D. Lafferty %t2001 %cNIPS %f/NIPS/NIPS-2001-5706.pdf %*Means, Correlations and Bounds %@Martijn Leisink,Bert Kappen %t2001 %cNIPS %f/NIPS/NIPS-2001-5707.pdf %*A Variational Approach to Learning Curves %@Dörthe Malzahn,Manfred Opper %t2001 %cNIPS %f/NIPS/NIPS-2001-5708.pdf %*Entropy and Inference, Revisited %@Ilya Nemenman,F. Shafee,William Bialek %t2001 %cNIPS %f/NIPS/NIPS-2001-5709.pdf %*Asymptotic Universality for Learning Curves of Support Vector Machines %@Manfred Opper,Robert Urbanczik %t2001 %cNIPS %f/NIPS/NIPS-2001-5710.pdf %*On the Convergence of Leveraging %@Gunnar Rätsch,Sebastian Mika,Manfred K. Warmuth %t2001 %cNIPS %f/NIPS/NIPS-2001-5711.pdf %*Scaling Laws and Local Minima in Hebbian ICA %@Magnus Rattray,Gleb Basalyga %t2001 %cNIPS %f/NIPS/NIPS-2001-5712.pdf %*On the Concentration of Spectral Properties %@John Shawe-Taylor,Nello Cristianini,Jaz S. Kandola %t2001 %cNIPS %f/NIPS/NIPS-2001-5713.pdf %*Information-Geometrical Significance of Sparsity in Gallager Codes %@Toshiyuki Tanaka,Shiro Ikeda,Shun-ichi Amari %t2001 %cNIPS %f/NIPS/NIPS-2001-5714.pdf %*Fast Parameter Estimation Using Green's Functions %@K. Wong,F. Li %t2001 %cNIPS %f/NIPS/NIPS-2001-5715.pdf %*Semi-supervised MarginBoost %@Florence D'alché-buc,Yves Grandvalet,Christophe Ambroise %t2001 %cNIPS %f/NIPS/NIPS-2001-5716.pdf %*Rao-Blackwellised Particle Filtering via Data Augmentation %@Christophe Andrieu,Nando D. Freitas,Arnaud Doucet %t2001 %cNIPS %f/NIPS/NIPS-2001-5717.pdf %*Thin Junction Trees %@Francis R. Bach,Michael I. Jordan %t2001 %cNIPS %f/NIPS/NIPS-2001-5718.pdf %*The Infinite Hidden Markov Model %@Matthew J. Beal,Zoubin Ghahramani,Carl E. Rasmussen %t2001 %cNIPS %f/NIPS/NIPS-2001-5719.pdf %*Laplacian Eigenmaps and Spectral Techniques for Embedding and Clustering %@Mikhail Belkin,Partha Niyogi %t2001 %cNIPS %f/NIPS/NIPS-2001-5720.pdf %*Duality, Geometry, and Support Vector Regression %@J. Bi,Kristin P. Bennett %t2001 %cNIPS %f/NIPS/NIPS-2001-5721.pdf %*Latent Dirichlet Allocation %@David M. Blei,Andrew Y. Ng,Michael I. Jordan %t2001 %cNIPS %f/NIPS/NIPS-2001-5722.pdf %*Incorporating Invariances in Non-Linear Support Vector Machines %@Olivier Chapelle,Bernhard Schölkopf %t2001 %cNIPS %f/NIPS/NIPS-2001-5723.pdf %*A Generalization of Principal Components Analysis to the Exponential Family %@Michael Collins,S. Dasgupta,Robert E. Schapire %t2001 %cNIPS %f/NIPS/NIPS-2001-5724.pdf %*Convolution Kernels for Natural Language %@Michael Collins,Nigel Duffy %t2001 %cNIPS %f/NIPS/NIPS-2001-5725.pdf %*A Parallel Mixture of SVMs for Very Large Scale Problems %@Ronan Collobert,Samy Bengio,Yoshua Bengio %t2001 %cNIPS %f/NIPS/NIPS-2001-5726.pdf %*Pranking with Ranking %@Koby Crammer,Yoram Singer %t2001 %cNIPS %f/NIPS/NIPS-2001-5727.pdf %*Spectral Kernel Methods for Clustering %@Nello Cristianini,John Shawe-Taylor,Jaz S. Kandola %t2001 %cNIPS %f/NIPS/NIPS-2001-5728.pdf %*TAP Gibbs Free Energy, Belief Propagation and Sparsity %@Lehel Csató,Manfred Opper,Ole Winther %t2001 %cNIPS %f/NIPS/NIPS-2001-5729.pdf %*Adaptive Nearest Neighbor Classification Using Support Vector Machines %@Carlotta Domeniconi,Dimitrios Gunopulos %t2001 %cNIPS %f/NIPS/NIPS-2001-5730.pdf %*Learning from Infinite Data in Finite Time %@Pedro Domingos,Geoff Hulten %t2001 %cNIPS %f/NIPS/NIPS-2001-5731.pdf %*A kernel method for multi-labelled classification %@André Elisseeff,Jason Weston %t2001 %cNIPS %f/NIPS/NIPS-2001-5732.pdf %*Approximate Dynamic Programming via Linear Programming %@Daniela Farias,Benjamin V. Roy %t2001 %cNIPS %f/NIPS/NIPS-2001-5733.pdf %*Incremental Learning and Selective Sampling via Parametric Optimization Framework for SVM %@Shai Fine,Katya Scheinberg %t2001 %cNIPS %f/NIPS/NIPS-2001-5734.pdf %*Fast, Large-Scale Transformation-Invariant Clustering %@Brendan J. Frey,Nebojsa Jojic %t2001 %cNIPS %f/NIPS/NIPS-2001-5735.pdf %*Product Analysis: Learning to Model Observations as Products of Hidden Variables %@Brendan J. Frey,Anitha Kannan,Nebojsa Jojic %t2001 %cNIPS %f/NIPS/NIPS-2001-5736.pdf %*Very loopy belief propagation for unwrapping phase images %@Brendan J. Frey,Ralf Koetter,Nemanja Petrovic %t2001 %cNIPS %f/NIPS/NIPS-2001-5737.pdf %*Kernel Feature Spaces and Nonlinear Blind Souce Separation %@Stefan Harmeling,Andreas Ziehe,Motoaki Kawanabe,Klaus-Robert Müller %t2001 %cNIPS %f/NIPS/NIPS-2001-5738.pdf %*The Method of Quantum Clustering %@David Horn,Assaf Gottlieb %t2001 %cNIPS %f/NIPS/NIPS-2001-5739.pdf %*Active Information Retrieval %@Tommi Jaakkola,Hava T. Siegelmann %t2001 %cNIPS %f/NIPS/NIPS-2001-5740.pdf %*Online Learning with Kernels %@Jyrki Kivinen,Alex J. Smola,Robert C. Williamson %t2001 %cNIPS %f/NIPS/NIPS-2001-5741.pdf %*A Dynamic HMM for On-line Segmentation of Sequential Data %@Jens Kohlmorgen,Steven Lemm %t2001 %cNIPS %f/NIPS/NIPS-2001-5742.pdf %*Minimax Probability Machine %@Gert Lanckriet,Laurent E. Ghaoui,Chiranjib Bhattacharyya,Michael I. Jordan %t2001 %cNIPS %f/NIPS/NIPS-2001-5743.pdf %*(Not) Bounding the True Error %@John Langford,Rich Caruana %t2001 %cNIPS %f/NIPS/NIPS-2001-5744.pdf %*An Efficient, Exact Algorithm for Solving Tree-Structured Graphical Games %@Michael L. Littman,Michael J. Kearns,Satinder P. Singh %t2001 %cNIPS %f/NIPS/NIPS-2001-5745.pdf %*Quantizing Density Estimators %@Peter Meinicke,Helge Ritter %t2001 %cNIPS %f/NIPS/NIPS-2001-5746.pdf %*Linear-time inference in Hierarchical HMMs %@Kevin P. Murphy,Mark A. Paskin %t2001 %cNIPS %f/NIPS/NIPS-2001-5747.pdf %*On Discriminative vs. Generative Classifiers: A comparison of logistic regression and naive Bayes %@Andrew Y. Ng,Michael I. Jordan %t2001 %cNIPS %f/NIPS/NIPS-2001-5748.pdf %*On Spectral Clustering: Analysis and an algorithm %@Andrew Y. Ng,Michael I. Jordan,Yair Weiss %t2001 %cNIPS %f/NIPS/NIPS-2001-5749.pdf %*Learning Hierarchical Structures with Linear Relational Embedding %@Alberto Paccanaro,Geoffrey E. Hinton %t2001 %cNIPS %f/NIPS/NIPS-2001-5750.pdf %*MIME: Mutual Information Minimization and Entropy Maximization for Bayesian Belief Propagation %@Anand Rangarajan,Alan L. Yuille %t2001 %cNIPS %f/NIPS/NIPS-2001-5751.pdf %*Infinite Mixtures of Gaussian Process Experts %@Carl E. Rasmussen,Zoubin Ghahramani %t2001 %cNIPS %f/NIPS/NIPS-2001-5752.pdf %*Global Coordination of Local Linear Models %@Sam T. Roweis,Lawrence K. Saul,Geoffrey E. Hinton %t2001 %cNIPS %f/NIPS/NIPS-2001-5753.pdf %*Multiplicative Updates for Classification by Mixture Models %@Lawrence K. Saul,Daniel D. Lee %t2001 %cNIPS %f/NIPS/NIPS-2001-5754.pdf %*Probabilistic Abstraction Hierarchies %@Eran Segal,Daphne Koller,Dirk Ormoneit %t2001 %cNIPS %f/NIPS/NIPS-2001-5755.pdf %*Dynamic Time-Alignment Kernel in Support Vector Machine %@Hiroshi Shimodaira,Ken-ichi Noma,Mitsuru Nakai,Shigeki Sagayama %t2001 %cNIPS %f/NIPS/NIPS-2001-5756.pdf %*Agglomerative Multivariate Information Bottleneck %@Noam Slonim,Nir Friedman,Naftali Tishby %t2001 %cNIPS %f/NIPS/NIPS-2001-5757.pdf %*Bayesian time series classification %@Peter Sykacek,Stephen J. Roberts %t2001 %cNIPS %f/NIPS/NIPS-2001-5758.pdf %*Partially labeled classification with Markov random walks %@Martin Szummer,Tommi Jaakkola %t2001 %cNIPS %f/NIPS/NIPS-2001-5759.pdf %*The Unified Propagation and Scaling Algorithm %@Yee W. Teh,Max Welling %t2001 %cNIPS %f/NIPS/NIPS-2001-5760.pdf %*Risk Sensitive Particle Filters %@Sebastian Thrun,John Langford,Vandi Verma %t2001 %cNIPS %f/NIPS/NIPS-2001-5761.pdf %*A New Discriminative Kernel From Probabilistic Models %@Koji Tsuda,Motoaki Kawanabe,Gunnar Rätsch,Sören Sonnenburg,Klaus-Robert Müller %t2001 %cNIPS %f/NIPS/NIPS-2001-5762.pdf %*K-Local Hyperplane and Convex Distance Nearest Neighbor Algorithms %@Pascal Vincent,Yoshua Bengio %t2001 %cNIPS %f/NIPS/NIPS-2001-5763.pdf %*Multi Dimensional ICA to Separate Correlated Sources %@Roland Vollgraf,Klaus Obermayer %t2001 %cNIPS %f/NIPS/NIPS-2001-5764.pdf %*Tree-based reparameterization for approximate inference on loopy graphs %@Martin J. Wainwright,Tommi Jaakkola,Alan S. Willsky %t2001 %cNIPS %f/NIPS/NIPS-2001-5765.pdf %*Products of Gaussians %@Christopher Williams,Felix V. Agakov,Stephen N. Felderhof %t2001 %cNIPS %f/NIPS/NIPS-2001-5766.pdf %*Iterative Double Clustering for Unsupervised and Semi-Supervised Learning %@Ran El-Yaniv,Oren Souroujon %t2001 %cNIPS %f/NIPS/NIPS-2001-5767.pdf %*The Concave-Convex Procedure (CCCP) %@Alan L. Yuille,Anand Rangarajan %t2001 %cNIPS %f/NIPS/NIPS-2001-5768.pdf %*Blind Source Separation via Multinode Sparse Representation %@Michael Zibulevsky,Pavel Kisilev,Yehoshua Y. Zeevi,Barak A. Pearlmutter %t2001 %cNIPS %f/NIPS/NIPS-2001-5769.pdf %*Spectral Relaxation for K-means Clustering %@Hongyuan Zha,Xiaofeng He,Chris Ding,Ming Gu,Horst D. Simon %t2001 %cNIPS %f/NIPS/NIPS-2001-5770.pdf %*EM-DD: An Improved Multiple-Instance Learning Technique %@Qi Zhang,Sally A. Goldman %t2001 %cNIPS %f/NIPS/NIPS-2001-5771.pdf %*Kernel Logistic Regression and the Import Vector Machine %@Ji Zhu,Trevor Hastie %t2001 %cNIPS %f/NIPS/NIPS-2001-5772.pdf %*Citcuits for VLSI Implementation of Temporally Asymmetric Hebbian Learning %@A. Bofill,D. P. Thompson,Alan F. Murray %t2001 %cNIPS %f/NIPS/NIPS-2001-5773.pdf %*Stochastic Mixed-Signal VLSI Architecture for High-Dimensional Kernel Machines %@Roman Genov,Gert Cauwenberghs %t2001 %cNIPS %f/NIPS/NIPS-2001-5774.pdf %*Orientation-Selective aVLSI Spiking Neurons %@Shih-Chii Liu,Jörg Kramer,Giacomo Indiveri,Tobi Delbrück,Rodney J. Douglas %t2001 %cNIPS %f/NIPS/NIPS-2001-5775.pdf %*An Efficient Clustering Algorithm Using Stochastic Association Model and Its Implementation Using Nanostructures %@Takashi Morie,Tomohiro Matsuura,Makoto Nagata,Atsushi Iwata %t2001 %cNIPS %f/NIPS/NIPS-2001-5776.pdf %*Learning Spike-Based Correlations and Conditional Probabilities in Silicon %@Aaron P. Shon,David Hsu,Chris Diorio %t2001 %cNIPS %f/NIPS/NIPS-2001-5777.pdf %*Analog Soft-Pattern-Matching Classifier using Floating-Gate MOS Technology %@Toshihiko Yamasaki,Tadashi Shibata %t2001 %cNIPS %f/NIPS/NIPS-2001-5778.pdf %*Intransitive Likelihood-Ratio Classifiers %@Jeff Bilmes,Gang Ji,Marina Meila %t2001 %cNIPS %f/NIPS/NIPS-2001-5779.pdf %*Relative Density Nets: A New Way to Combine Backpropagation with HMM's %@Andrew D. Brown,Geoffrey E. Hinton %t2001 %cNIPS %f/NIPS/NIPS-2001-5780.pdf %*ALGONQUIN - Learning Dynamic Noise Models From Noisy Speech for Robust Speech Recognition %@Brendan J. Frey,Trausti T. Kristjansson,Li Deng,Alex Acero %t2001 %cNIPS %f/NIPS/NIPS-2001-5781.pdf %*Audio-Visual Sound Separation Via Hidden Markov Models %@John R. Hershey,Michael Casey %t2001 %cNIPS %f/NIPS/NIPS-2001-5782.pdf %*Estimating the Reliability of ICA Projections %@Frank C. Meinecke,Andreas Ziehe,Motoaki Kawanabe,Klaus-Robert Müller %t2001 %cNIPS %f/NIPS/NIPS-2001-5783.pdf %*Speech Recognition with Missing Data using Recurrent Neural Nets %@S. Parveen,P. Green %t2001 %cNIPS %f/NIPS/NIPS-2001-5784.pdf %*Speech Recognition using SVMs %@N. Smith,Mark Gales %t2001 %cNIPS %f/NIPS/NIPS-2001-5785.pdf %*Sequential Noise Compensation by Sequential Monte Carlo Method %@K. Yao,S. Nakamura %t2001 %cNIPS %f/NIPS/NIPS-2001-5786.pdf %*A Neural Oscillator Model of Auditory Selective Attention %@Stuart N. Wrigley,Guy J. Brown %t2001 %cNIPS %f/NIPS/NIPS-2001-5787.pdf %*The g Factor: Relating Distributions on Features to Distributions on Images %@James M. Coughlan,Alan L. Yuille %t2001 %cNIPS %f/NIPS/NIPS-2001-5788.pdf %*Categorization by Learning and Combining Object Parts %@Bernd Heisele,Thomas Serre,Massimiliano Pontil,Thomas Vetter,Tomaso Poggio %t2001 %cNIPS %f/NIPS/NIPS-2001-5789.pdf %*Modeling the Modulatory Effect of Attention on Human Spatial Vision %@Laurent Itti,Jochen Braun,Christof Koch %t2001 %cNIPS %f/NIPS/NIPS-2001-5790.pdf %*Grouping and dimensionality reduction by locally linear embedding %@Marzia Polito,Pietro Perona %t2001 %cNIPS %f/NIPS/NIPS-2001-5791.pdf %*Learning Body Pose via Specialized Maps %@Rómer Rosales,Stan Sclaroff %t2001 %cNIPS %f/NIPS/NIPS-2001-5792.pdf %*A Hierarchical Model of Complex Cells in Visual Cortex for the Binocular Perception of Motion-in-Depth %@Silvio P. Sabatini,Fabio Solari,Giulia Andreani,Chiara Bartolozzi,Giacomo M. Bisio %t2001 %cNIPS %f/NIPS/NIPS-2001-5793.pdf %*The Fidelity of Local Ordinal Encoding %@Javid Sadr,Sayan Mukherjee,Keith Thoresz,Pawan Sinha %t2001 %cNIPS %f/NIPS/NIPS-2001-5794.pdf %*Unsupervised Learning of Human Motion Models %@Yang Song,Luis Goncalves,Pietro Perona %t2001 %cNIPS %f/NIPS/NIPS-2001-5795.pdf %*Transform-invariant Image Decomposition with Similarity Templates %@Chris Stauffer,Erik Miller,Kinh Tieu %t2001 %cNIPS %f/NIPS/NIPS-2001-5796.pdf %*Fast and Robust Classification using Asymmetric AdaBoost and a Detector Cascade %@Paul Viola,Michael Jones %t2001 %cNIPS %f/NIPS/NIPS-2001-5797.pdf %*A Rotation and Translation Invariant Discrete Saliency Network %@Lance R. Williams,John W. Zweck %t2001 %cNIPS %f/NIPS/NIPS-2001-5798.pdf %*Grouping with Bias %@Stella X. Yu,Jianbo Shi %t2001 %cNIPS %f/NIPS/NIPS-2001-5799.pdf %*Model Based Population Tracking and Automatic Detection of Distribution Changes %@Igor V. Cadez,P. S. Bradley %t2001 %cNIPS %f/NIPS/NIPS-2001-5800.pdf %*Bayesian Predictive Profiles With Applications to Retail Transaction Data %@Igor V. Cadez,Padhraic Smyth %t2001 %cNIPS %f/NIPS/NIPS-2001-5801.pdf %*Tempo tracking and rhythm quantization by sequential Monte Carlo %@Ali Taylan Cemgil,Bert Kappen %t2001 %cNIPS %f/NIPS/NIPS-2001-5802.pdf %*Estimating Car Insurance Premia: a Case Study in High-Dimensional Data Inference %@Nicolas Chapados,Yoshua Bengio,Pascal Vincent,Joumana Ghosn,Charles Dugas,Ichiro Takeuchi,Linyan Meng %t2001 %cNIPS %f/NIPS/NIPS-2001-5803.pdf %*Using Vocabulary Knowledge in Bayesian Multinomial Estimation %@Thomas L. Griffiths,Joshua B. Tenenbaum %t2001 %cNIPS %f/NIPS/NIPS-2001-5804.pdf %*Cobot: A Social Reinforcement Learning Agent %@Charles Lee Isbell Jr.,Christian R. Shelton %t2001 %cNIPS %f/NIPS/NIPS-2001-5805.pdf %*Optimising Synchronisation Times for Mobile Devices %@Neil D. Lawrence,Antony I. T. Rowstron,Christopher M. Bishop,Michael J. Taylor %t2001 %cNIPS %f/NIPS/NIPS-2001-5806.pdf %*Prodding the ROC Curve: Constrained Optimization of Classifier Performance %@Michael C. Mozer,Robert Dodier,Michael D. Colagrosso,Cesar Guerra-Salcedo,Richard Wolniewicz %t2001 %cNIPS %f/NIPS/NIPS-2001-5807.pdf %*Hyperbolic Self-Organizing Maps for Semantic Navigation %@Jorg Ontrup,Helge Ritter %t2001 %cNIPS %f/NIPS/NIPS-2001-5808.pdf %*Learning a Gaussian Process Prior for Automatically Generating Music Playlists %@John C. Platt,Christopher J. C. Burges,Steven Swenson,Christopher Weare,Alice Zheng %t2001 %cNIPS %f/NIPS/NIPS-2001-5809.pdf %*The Intelligent surfer: Probabilistic Combination of Link and Content Information in PageRank %@Matthew Richardson,Pedro Domingos %t2001 %cNIPS %f/NIPS/NIPS-2001-5810.pdf %*Active Learning in the Drug Discovery Process %@Manfred K. Warmuth,Gunnar Rätsch,Michael Mathieson,Jun Liao,Christian Lemmen %t2001 %cNIPS %f/NIPS/NIPS-2001-5811.pdf %*Active Portfolio-Management based on Error Correction Neural Networks %@Hans-Georg Zimmermann,Ralph Neuneier,Ralph Grothmann %t2001 %cNIPS %f/NIPS/NIPS-2001-5812.pdf %*Playing is believing: The role of beliefs in multi-agent learning %@Yu-Han Chang,Leslie Pack Kaelbling %t2001 %cNIPS %f/NIPS/NIPS-2001-5813.pdf %*Batch Value Function Approximation via Support Vectors %@Thomas G. Dietterich,Xin Wang %t2001 %cNIPS %f/NIPS/NIPS-2001-5814.pdf %*Convergence of Optimistic and Incremental Q-Learning %@Eyal Even-dar,Yishay Mansour %t2001 %cNIPS %f/NIPS/NIPS-2001-5815.pdf %*Variance Reduction Techniques for Gradient Estimates in Reinforcement Learning %@Evan Greensmith,Peter L. Bartlett,Jonathan Baxter %t2001 %cNIPS %f/NIPS/NIPS-2001-5816.pdf %*Rates of Convergence of Performance Gradient Estimates Using Function Approximation and Bias in Reinforcement Learning %@Gregory Z. Grudic,Lyle H. Ungar %t2001 %cNIPS %f/NIPS/NIPS-2001-5817.pdf %*Multiagent Planning with Factored MDPs %@Carlos Guestrin,Daphne Koller,Ronald Parr %t2001 %cNIPS %f/NIPS/NIPS-2001-5818.pdf %*Incremental A* %@S. Koenig,M. Likhachev %t2001 %cNIPS %f/NIPS/NIPS-2001-5819.pdf %*Model-Free Least-Squares Policy Iteration %@Michail G. Lagoudakis,Ronald Parr %t2001 %cNIPS %f/NIPS/NIPS-2001-5820.pdf %*Predictive Representations of State %@Michael L. Littman,Richard S. Sutton %t2001 %cNIPS %f/NIPS/NIPS-2001-5821.pdf %*The Steering Approach for Multi-Criteria Reinforcement Learning %@Shie Mannor,Nahum Shimkin %t2001 %cNIPS %f/NIPS/NIPS-2001-5822.pdf %*Direct value-approximation for factored MDPs %@Dale Schuurmans,Relu Patrascu %t2001 %cNIPS %f/NIPS/NIPS-2001-5823.pdf %*Stabilizing Value Function Approximation with the BFBP Algorithm %@Xin Wang,Thomas G. Dietterich %t2001 %cNIPS %f/NIPS/NIPS-2001-5824.pdf %*Who Does What? A Novel Algorithm to Determine Function Localization %@Ranit Aharonov-Barki,Isaac Meilijson,Eytan Ruppin %t2000 %cNIPS %f/NIPS/NIPS-2000-5825.pdf %*A Productive, Systematic Framework for the Representation of Visual Structure %@Shimon Edelman,Nathan Intrator %t2000 %cNIPS %f/NIPS/NIPS-2000-5826.pdf %*The Interplay of Symbolic and Subsymbolic Processes in Anagram Problem Solving %@David B. Grimes,Michael C. Mozer %t2000 %cNIPS %f/NIPS/NIPS-2000-5827.pdf %*Hippocampally-Dependent Consolidation in a Hierarchical Model of Neocortex %@Szabolcs Káli,Peter Dayan %t2000 %cNIPS %f/NIPS/NIPS-2000-5828.pdf %*Position Variance, Recurrence and Perceptual Learning %@Zhaoping Li,Peter Dayan %t2000 %cNIPS %f/NIPS/NIPS-2000-5829.pdf %*The Use of MDL to Select among Computational Models of Cognition %@In Jae Myung,Mark A. Pitt,Shaobo Zhang,Vijay Balasubramanian %t2000 %cNIPS %f/NIPS/NIPS-2000-5830.pdf %*Active Inference in Concept Learning %@Jonathan D. Nelson,Javier R. Movellan %t2000 %cNIPS %f/NIPS/NIPS-2000-5831.pdf %*The Early Word Catches the Weights %@Mark A. Smith,Garrison W. Cottrell,Karen L. Anderson %t2000 %cNIPS %f/NIPS/NIPS-2000-5832.pdf %*Structure Learning in Human Causal Induction %@Joshua B. Tenenbaum,Thomas L. Griffiths %t2000 %cNIPS %f/NIPS/NIPS-2000-5833.pdf %*What Can a Single Neuron Compute? %@Blaise Agüera y Arcas,Adrienne L. Fairhall,William Bialek %t2000 %cNIPS %f/NIPS/NIPS-2000-5834.pdf %*Dendritic Compartmentalization Could Underlie Competition and Attentional Biasing of Simultaneous Visual Stimuli %@Kevin A. Archie,Bartlett W. Mel %t2000 %cNIPS %f/NIPS/NIPS-2000-5835.pdf %*Place Cells and Spatial Navigation Based on 2D Visual Feature Extraction, Path Integration, and Reinforcement Learning %@Angelo Arleo,Fabrizio Smeraldi,Stéphane Hug,Wulfram Gerstner %t2000 %cNIPS %f/NIPS/NIPS-2000-5836.pdf %*Modelling Spatial Recall, Mental Imagery and Neglect %@Suzanna Becker,Neil Burgess %t2000 %cNIPS %f/NIPS/NIPS-2000-5837.pdf %*Temporally Dependent Plasticity: An Information Theoretic Account %@Gal Chechik,Naftali Tishby %t2000 %cNIPS %f/NIPS/NIPS-2000-5838.pdf %*A New Model of Spatial Representation in Multimodal Brain Areas %@Sophie Denève,Jean-René Duhamel,Alexandre Pouget %t2000 %cNIPS %f/NIPS/NIPS-2000-5839.pdf %*Multiple Timescales of Adaptation in a Neural Code %@Adrienne L. Fairhall,Geoffrey D. Lewen,William Bialek,Robert R. de Ruyter van Steveninck %t2000 %cNIPS %f/NIPS/NIPS-2000-5840.pdf %*Dopamine Bonuses %@Sham Kakade,Peter Dayan %t2000 %cNIPS %f/NIPS/NIPS-2000-5841.pdf %*Finding the Key to a Synapse %@Thomas Natschläger,Wolfgang Maass %t2000 %cNIPS %f/NIPS/NIPS-2000-5842.pdf %*Processing of Time Series by Neural Circuits with Biologically Realistic Synaptic Dynamics %@Thomas Natschläger,Wolfgang Maass,Eduardo D. Sontag,Anthony M. Zador %t2000 %cNIPS %f/NIPS/NIPS-2000-5843.pdf %*Spike-Timing-Dependent Learning for Oscillatory Networks %@Silvia Scarpetta,Zhaoping Li,John A. Hertz %t2000 %cNIPS %f/NIPS/NIPS-2000-5844.pdf %*Universality and Individuality in a Neural Code %@Elad Schneidman,Naama Brenner,Naftali Tishby,Robert R. de Ruyter van Steveninck,William Bialek %t2000 %cNIPS %f/NIPS/NIPS-2000-5845.pdf %*Natural Sound Statistics and Divisive Normalization in the Auditory System %@Odelia Schwartz,Eero P. Simoncelli %t2000 %cNIPS %f/NIPS/NIPS-2000-5846.pdf %*Efficient Learning of Linear Perceptrons %@Shai Ben-David,Hans-Ulrich Simon %t2000 %cNIPS %f/NIPS/NIPS-2000-5847.pdf %*Algorithmic Stability and Generalization Performance %@Olivier Bousquet,André Elisseeff %t2000 %cNIPS %f/NIPS/NIPS-2000-5848.pdf %*From Margin to Sparsity %@Thore Graepel,Ralf Herbrich,Robert C. Williamson %t2000 %cNIPS %f/NIPS/NIPS-2000-5849.pdf %*Permitted and Forbidden Sets in Symmetric Threshold-Linear Networks %@Richard H. R. Hahnloser,H. Sebastian Seung %t2000 %cNIPS %f/NIPS/NIPS-2000-5850.pdf %*A PAC-Bayesian Margin Bound for Linear Classifiers: Why SVMs work %@Ralf Herbrich,Thore Graepel %t2000 %cNIPS %f/NIPS/NIPS-2000-5851.pdf %*On Reversing Jensen's Inequality %@Tony Jebara,Alex Pentland %t2000 %cNIPS %f/NIPS/NIPS-2000-5852.pdf %*Second Order Approximations for Probability Models %@Hilbert J. Kappen,Wim Wiegerinck %t2000 %cNIPS %f/NIPS/NIPS-2000-5853.pdf %*Some New Bounds on the Generalization Error of Combined Classifiers %@Vladimir Koltchinskii,Dmitriy Panchenko,Fernando Lozano %t2000 %cNIPS %f/NIPS/NIPS-2000-5854.pdf %*Foundations for a Circuit Complexity Theory of Sensory Processing %@Robert A. Legenstein,Wolfgang Maass %t2000 %cNIPS %f/NIPS/NIPS-2000-5855.pdf %*A Tighter Bound for Graphical Models %@Martijn A. R. Leisink,Hilbert J. Kappen %t2000 %cNIPS %f/NIPS/NIPS-2000-5856.pdf %*Learning Curves for Gaussian Processes Regression: A Framework for Good Approximations %@Dörthe Malzahn,Manfred Opper %t2000 %cNIPS %f/NIPS/NIPS-2000-5857.pdf %*Weak Learners and Improved Rates of Convergence in Boosting %@Shie Mannor,Ron Meir %t2000 %cNIPS %f/NIPS/NIPS-2000-5858.pdf %*Learning Continuous Distributions: Simulations With Field Theoretic Priors %@Ilya Nemenman,William Bialek %t2000 %cNIPS %f/NIPS/NIPS-2000-5859.pdf %*Occam's Razor %@Carl Edward Rasmussen,Zoubin Ghahramani %t2000 %cNIPS %f/NIPS/NIPS-2000-5860.pdf %*Regularization with Dot-Product Kernels %@Alex J. Smola,Zoltán L. Óvári,Robert C. Williamson %t2000 %cNIPS %f/NIPS/NIPS-2000-5861.pdf %*Error-correcting Codes on a Bethe-like Lattice %@Renato Vicente,David Saad,Yoshiyuki Kabashima %t2000 %cNIPS %f/NIPS/NIPS-2000-5862.pdf %*Stagewise Processing in Error-correcting Codes and Image Restoration %@K. Y. Michael Wong,Hidetoshi Nishimori %t2000 %cNIPS %f/NIPS/NIPS-2000-5863.pdf %*Learning Winner-take-all Competition Between Groups of Neurons in Lateral Inhibitory Networks %@Xiaohui Xie,Richard H. R. Hahnloser,H. Sebastian Seung %t2000 %cNIPS %f/NIPS/NIPS-2000-5864.pdf %*A Support Vector Method for Clustering %@Asa Ben-Hur,David Horn,Hava T. Siegelmann,Vladimir Vapnik %t2000 %cNIPS %f/NIPS/NIPS-2000-5865.pdf %*A Variational Mean-Field Theory for Sigmoidal Belief Networks %@Chiranjib Bhattacharyya,S. Sathiya Keerthi %t2000 %cNIPS %f/NIPS/NIPS-2000-5866.pdf %*Model Complexity, Goodness of Fit and Diminishing Returns %@Igor V. Cadez,Padhraic Smyth %t2000 %cNIPS %f/NIPS/NIPS-2000-5867.pdf %*A Linear Programming Approach to Novelty Detection %@Colin Campbell,Kristin P. Bennett %t2000 %cNIPS %f/NIPS/NIPS-2000-5868.pdf %*Overfitting in Neural Nets: Backpropagation, Conjugate Gradient, and Early Stopping %@Rich Caruana,Steve Lawrence,C. Lee Giles %t2000 %cNIPS %f/NIPS/NIPS-2000-5869.pdf %*Incremental and Decremental Support Vector Machine Learning %@Gert Cauwenberghs,Tomaso Poggio %t2000 %cNIPS %f/NIPS/NIPS-2000-5870.pdf %*Vicinal Risk Minimization %@Olivier Chapelle,Jason Weston,Léon Bottou,Vladimir Vapnik %t2000 %cNIPS %f/NIPS/NIPS-2000-5871.pdf %*Gaussianization %@Scott Saobing Chen,Ramesh A. Gopinath %t2000 %cNIPS %f/NIPS/NIPS-2000-5872.pdf %*The Missing Link - A Probabilistic Model of Document Content and Hypertext Connectivity %@David A. Cohn,Thomas Hofmann %t2000 %cNIPS %f/NIPS/NIPS-2000-5873.pdf %*Improved Output Coding for Classification Using Continuous Relaxation %@Koby Crammer,Yoram Singer %t2000 %cNIPS %f/NIPS/NIPS-2000-5874.pdf %*Sparse Representation for Gaussian Process Models %@Lehel Csató,Manfred Opper %t2000 %cNIPS %f/NIPS/NIPS-2000-5875.pdf %*Explaining Away in Weight Space %@Peter Dayan,Sham Kakade %t2000 %cNIPS %f/NIPS/NIPS-2000-5876.pdf %*An Adaptive Metric Machine for Pattern Classification %@Carlotta Domeniconi,Jing Peng,Dimitrios Gunopulos %t2000 %cNIPS %f/NIPS/NIPS-2000-5877.pdf %*Incorporating Second-Order Functional Knowledge for Better Option Pricing %@Charles Dugas,Yoshua Bengio,François Bélisle,Claude Nadeau,René Garcia %t2000 %cNIPS %f/NIPS/NIPS-2000-5878.pdf %*Discovering Hidden Variables: A Structure-Based Approach %@Gal Elidan,Noam Lotner,Nir Friedman,Daphne Koller %t2000 %cNIPS %f/NIPS/NIPS-2000-5879.pdf %*Accumulator Networks: Suitors of Local Probability Propagation %@Brendan J. Frey,Anitha Kannan %t2000 %cNIPS %f/NIPS/NIPS-2000-5880.pdf %*Sequentially Fitting ``Inclusive'' Trees for Inference in Noisy-OR Networks %@Brendan J. Frey,Relu Patrascu,Tommi Jaakkola,Jodi Moran %t2000 %cNIPS %f/NIPS/NIPS-2000-5881.pdf %*Propagation Algorithms for Variational Bayesian Learning %@Zoubin Ghahramani,Matthew J. Beal %t2000 %cNIPS %f/NIPS/NIPS-2000-5882.pdf %*The Kernel Gibbs Sampler %@Thore Graepel,Ralf Herbrich %t2000 %cNIPS %f/NIPS/NIPS-2000-5883.pdf %*`N-Body' Problems in Statistical Learning %@Alexander G. Gray,Andrew W. Moore %t2000 %cNIPS %f/NIPS/NIPS-2000-5884.pdf %*Large Scale Bayes Point Machines %@Ralf Herbrich,Thore Graepel %t2000 %cNIPS %f/NIPS/NIPS-2000-5885.pdf %*Beyond Maximum Likelihood and Density Estimation: A Sample-Based Criterion for Unsupervised Learning of Complex Models %@Sepp Hochreiter,Michael C. Mozer %t2000 %cNIPS %f/NIPS/NIPS-2000-5886.pdf %*Ensemble Learning and Linear Response Theory for ICA %@Pedro A. d. F. R. Højen-Sørensen,Ole Winther,Lars Kai Hansen %t2000 %cNIPS %f/NIPS/NIPS-2000-5887.pdf %*Generalizable Singular Value Decomposition for Ill-posed Datasets %@Ulrik Kjems,Lars Kai Hansen,Stephen C. Strother %t2000 %cNIPS %f/NIPS/NIPS-2000-5888.pdf %*Algorithms for Non-negative Matrix Factorization %@Daniel D. Lee,H. Sebastian Seung %t2000 %cNIPS %f/NIPS/NIPS-2000-5889.pdf %*Text Classification using String Kernels %@Huma Lodhi,John Shawe-Taylor,Nello Cristianini,Christopher J. C. H. Watkins %t2000 %cNIPS %f/NIPS/NIPS-2000-5890.pdf %*Constrained Independent Component Analysis %@Wei Lu,Jagath C. Rajapakse %t2000 %cNIPS %f/NIPS/NIPS-2000-5891.pdf %*Active Support Vector Machine Classification %@Olvi L. Mangasarian,David R. Musicant %t2000 %cNIPS %f/NIPS/NIPS-2000-5892.pdf %*The Unscented Particle Filter %@Rudolph van der Merwe,Arnaud Doucet,Nando de Freitas,Eric A. Wan %t2000 %cNIPS %f/NIPS/NIPS-2000-5893.pdf %*A Mathematical Programming Approach to the Kernel Fisher Algorithm %@Sebastian Mika,Gunnar Rätsch,Klaus-Robert Müller %t2000 %cNIPS %f/NIPS/NIPS-2000-5894.pdf %*On Iterative Krylov-Dogleg Trust-Region Steps for Solving Neural Networks Nonlinear Least Squares Problems %@Eiji Mizutani,James Demmel %t2000 %cNIPS %f/NIPS/NIPS-2000-5895.pdf %*An Information Maximization Approach to Overcomplete and Recurrent Representations %@Oren Shriki,Haim Sompolinsky,Daniel D. Lee %t2000 %cNIPS %f/NIPS/NIPS-2000-5896.pdf %*Sparse Greedy Gaussian Process Regression %@Alex J. Smola,Peter L. Bartlett %t2000 %cNIPS %f/NIPS/NIPS-2000-5897.pdf %*Kernel Expansions with Unlabeled Examples %@Martin Szummer,Tommi Jaakkola %t2000 %cNIPS %f/NIPS/NIPS-2000-5898.pdf %*Data Clustering by Markovian Relaxation and the Information Bottleneck Method %@Naftali Tishby,Noam Slonim %t2000 %cNIPS %f/NIPS/NIPS-2000-5899.pdf %*Active Learning for Parameter Estimation in Bayesian Networks %@Simon Tong,Daphne Koller %t2000 %cNIPS %f/NIPS/NIPS-2000-5900.pdf %*Tree-Based Modeling and Estimation of Gaussian Processes on Graphs with Cycles %@Martin J. Wainwright,Erik B. Sudderth,Alan S. Willsky %t2000 %cNIPS %f/NIPS/NIPS-2000-5901.pdf %*Feature Selection for SVMs %@Jason Weston,Sayan Mukherjee,Olivier Chapelle,Massimiliano Pontil,Tomaso Poggio,Vladimir Vapnik %t2000 %cNIPS %f/NIPS/NIPS-2000-5902.pdf %*Using the Nyström Method to Speed Up Kernel Machines %@Christopher K. I. Williams,Matthias Seeger %t2000 %cNIPS %f/NIPS/NIPS-2000-5903.pdf %*Generalized Belief Propagation %@Jonathan S. Yedidia,William T. Freeman,Yair Weiss %t2000 %cNIPS %f/NIPS/NIPS-2000-5904.pdf %*A Gradient-Based Boosting Algorithm for Regression Problems %@Richard S. Zemel,Toniann Pitassi %t2000 %cNIPS %f/NIPS/NIPS-2000-5905.pdf %*A Silicon Primitive for Competitive Learning %@David Hsu,Miguel Figueroa,Chris Diorio %t2000 %cNIPS %f/NIPS/NIPS-2000-5906.pdf %*Smart Vision Chip Fabricated Using Three Dimensional Integration Technology %@Hiroyuki Kurino,M. Nakagawa,Kang Wook Lee,Tomonori Nakamura,Yuusuke Yamada,Ki Tae Park,Mitsumasa Koyanagi %t2000 %cNIPS %f/NIPS/NIPS-2000-5907.pdf %*Homeostasis in a Silicon Integrate and Fire Neuron %@Shih-Chii Liu,Bradley A. Minch %t2000 %cNIPS %f/NIPS/NIPS-2000-5908.pdf %*Fast Training of Support Vector Classifiers %@Fernando Pérez-Cruz,Pedro Luis Alarcón-Diana,Angel Navia-Vázquez,Antonio Artés-Rodríguez %t2000 %cNIPS %f/NIPS/NIPS-2000-5909.pdf %*Four-legged Walking Gait Control Using a Neuromorphic Chip Interfaced to a Support Vector Learning Algorithm %@Susanne Still,Bernhard Schölkopf,Klaus Hepp,Rodney J. Douglas %t2000 %cNIPS %f/NIPS/NIPS-2000-5910.pdf %*New Approaches Towards Robust and Adaptive Speech Recognition %@Hervé Bourlard,Samy Bengio,Katrin Weber %t2000 %cNIPS %f/NIPS/NIPS-2000-5911.pdf %*Speech Denoising and Dereverberation Using Probabilistic Models %@Hagai Attias,John C. Platt,Alex Acero,Li Deng %t2000 %cNIPS %f/NIPS/NIPS-2000-5912.pdf %*Combining ICA and Top-Down Attention for Robust Speech Recognition %@Un-Min Bae,Soo-Young Lee %t2000 %cNIPS %f/NIPS/NIPS-2000-5913.pdf %*Learning Joint Statistical Models for Audio-Visual Fusion and Segregation %@John W. Fisher III,Trevor Darrell,William T. Freeman,Paul A. Viola %t2000 %cNIPS %f/NIPS/NIPS-2000-5914.pdf %*Higher-Order Statistical Properties Arising from the Non-Stationarity of Natural Signals %@Lucas C. Parra,Clay Spence,Paul Sajda %t2000 %cNIPS %f/NIPS/NIPS-2000-5915.pdf %*Minimum Bayes Error Feature Selection for Continuous Speech Recognition %@George Saon,Mukund Padmanabhan %t2000 %cNIPS %f/NIPS/NIPS-2000-5916.pdf %*Periodic Component Analysis: An Eigenvalue Method for Representing Periodic Structure in Speech %@Lawrence K. Saul,Jont B. Allen %t2000 %cNIPS %f/NIPS/NIPS-2000-5917.pdf %*FaceSync: A Linear Operator for Measuring Synchronization of Video Facial Images and Audio Tracks %@Malcolm Slaney,Michele Covell %t2000 %cNIPS %f/NIPS/NIPS-2000-5918.pdf %*Noise Suppression Based on Neurophysiologically-motivated SNR Estimation for Robust Speech Recognition %@Jürgen Tchorz,Michael Kleinschmidt,Birger Kollmeier %t2000 %cNIPS %f/NIPS/NIPS-2000-5919.pdf %*Shape Context: A New Descriptor for Shape Matching and Object Recognition %@Serge Belongie,Jitendra Malik,Jan Puzicha %t2000 %cNIPS %f/NIPS/NIPS-2000-5920.pdf %*Emergence of Movement Sensitive Neurons' Properties by Learning a Sparse Code for Natural Moving Images %@Rafal Bogacz,Malcolm W. Brown,Christophe G. Giraud-Carrier %t2000 %cNIPS %f/NIPS/NIPS-2000-5921.pdf %*The Manhattan World Assumption: Regularities in Scene Statistics which Enable Bayesian Inference %@James M. Coughlan,Alan L. Yuille %t2000 %cNIPS %f/NIPS/NIPS-2000-5922.pdf %*Feature Correspondence: A Markov Chain Monte Carlo Approach %@Frank Dellaert,Steven M. Seitz,Sebastian Thrun,Charles E. Thorpe %t2000 %cNIPS %f/NIPS/NIPS-2000-5923.pdf %*Keeping Flexible Active Contours on Track using Metropolis Updates %@Trausti T. Kristjansson,Brendan J. Frey %t2000 %cNIPS %f/NIPS/NIPS-2000-5924.pdf %*Color Opponency Constitutes a Sparse Representation for the Chromatic Structure of Natural Scenes %@Te-Won Lee,Thomas Wachtler,Terrence J. Sejnowski %t2000 %cNIPS %f/NIPS/NIPS-2000-5925.pdf %*Learning Segmentation by Random Walks %@Marina Meila,Jianbo Shi %t2000 %cNIPS %f/NIPS/NIPS-2000-5926.pdf %*Partially Observable SDE Models for Image Sequence Recognition Tasks %@Javier R. Movellan,Paul Mineiro,Ruth J. Williams %t2000 %cNIPS %f/NIPS/NIPS-2000-5927.pdf %*Learning Sparse Image Codes using a Wavelet Pyramid Architecture %@Bruno A. Olshausen,Phil Sallee,Michael S. Lewicki %t2000 %cNIPS %f/NIPS/NIPS-2000-5928.pdf %*Learning and Tracking Cyclic Human Motion %@Dirk Ormoneit,Hedvig Sidenbladh,Michael J. Black,Trevor Hastie %t2000 %cNIPS %f/NIPS/NIPS-2000-5929.pdf %*Rate-coded Restricted Boltzmann Machines for Face Recognition %@Yee Whye Teh,Geoffrey E. Hinton %t2000 %cNIPS %f/NIPS/NIPS-2000-5930.pdf %*Divisive and Subtractive Mask Effects: Linking Psychophysics and Biophysics %@Barbara Zenger,Christof Koch %t2000 %cNIPS %f/NIPS/NIPS-2000-5931.pdf %*From Mixtures of Mixtures to Adaptive Transform Coding %@Cynthia Archer,Todd K. Leen %t2000 %cNIPS %f/NIPS/NIPS-2000-5932.pdf %*A Neural Probabilistic Language Model %@Yoshua Bengio,Réjean Ducharme,Pascal Vincent %t2000 %cNIPS %f/NIPS/NIPS-2000-5933.pdf %*A Comparison of Image Processing Techniques for Visual Speech Recognition Applications %@Michael S. Gray,Terrence J. Sejnowski,Javier R. Movellan %t2000 %cNIPS %f/NIPS/NIPS-2000-5934.pdf %*Support Vector Novelty Detection Applied to Jet Engine Vibration Spectra %@Paul M. Hayton,Bernhard Schölkopf,Lionel Tarassenko,Paul Anuzis %t2000 %cNIPS %f/NIPS/NIPS-2000-5935.pdf %*Recognizing Hand-written Digits Using Hierarchical Products of Experts %@Guy Mayraz,Geoffrey E. Hinton %t2000 %cNIPS %f/NIPS/NIPS-2000-5936.pdf %*Sex with Support Vector Machines %@Baback Moghaddam,Ming-Hsuan Yang %t2000 %cNIPS %f/NIPS/NIPS-2000-5937.pdf %*Probabilistic Semantic Video Indexing %@Milind R. Naphade,Igor Kozintsev,Thomas S. Huang %t2000 %cNIPS %f/NIPS/NIPS-2000-5938.pdf %*Interactive Parts Model: An Application to Recognition of On-line Cursive Script %@Predrag Neskovic,Philip C. Davis,Leon N. Cooper %t2000 %cNIPS %f/NIPS/NIPS-2000-5939.pdf %*Learning Switching Linear Models of Human Motion %@Vladimir Pavlovic,James M. Rehg,John MacCormick %t2000 %cNIPS %f/NIPS/NIPS-2000-5940.pdf %*Bayes Networks on Ice: Robotic Search for Antarctic Meteorites %@Liam Pedersen,Dimitrios Apostolopoulos,William Whittaker %t2000 %cNIPS %f/NIPS/NIPS-2000-5941.pdf %*The Use of Classifiers in Sequential Inference %@Vasin Punyakanok,Dan Roth %t2000 %cNIPS %f/NIPS/NIPS-2000-5942.pdf %*Machine Learning for Video-Based Rendering %@Arno Schödl,Irfan A. Essa %t2000 %cNIPS %f/NIPS/NIPS-2000-5943.pdf %*Bayesian Video Shot Segmentation %@Nuno Vasconcelos,Andrew Lippman %t2000 %cNIPS %f/NIPS/NIPS-2000-5944.pdf %*Programmable Reinforcement Learning Agents %@David Andre,Stuart J. Russell %t2000 %cNIPS %f/NIPS/NIPS-2000-5945.pdf %*Exact Solutions to Time-Dependent MDPs %@Justin A. Boyan,Michael L. Littman %t2000 %cNIPS %f/NIPS/NIPS-2000-5946.pdf %*Hierarchical Memory-Based Reinforcement Learning %@Natalia Hernandez-Gardiol,Sridhar Mahadevan %t2000 %cNIPS %f/NIPS/NIPS-2000-5947.pdf %*Automated State Abstraction for Options using the U-Tree Algorithm %@Anders Jonsson,Andrew G. Barto %t2000 %cNIPS %f/NIPS/NIPS-2000-5948.pdf %*Robust Reinforcement Learning %@Jun Morimoto,Kenji Doya %t2000 %cNIPS %f/NIPS/NIPS-2000-5949.pdf %*Kernel-Based Reinforcement Learning in Average-Cost Problems: An Application to Optimal Portfolio Choice %@Dirk Ormoneit,Peter W. Glynn %t2000 %cNIPS %f/NIPS/NIPS-2000-5950.pdf %*Using Free Energies to Represent Q-values in a Multiagent Reinforcement Learning Task %@Brian Sallans,Geoffrey E. Hinton %t2000 %cNIPS %f/NIPS/NIPS-2000-5951.pdf %*APRICODD: Approximate Policy Construction Using Decision Diagrams %@Robert St-Aubin,Jesse Hoey,Craig Boutilier %t2000 %cNIPS %f/NIPS/NIPS-2000-5952.pdf %*Recognizing Evoked Potentials in a Virtual Environment %@Jessica D. Bayliss,Dana H. Ballard %t1999 %cNIPS %f/NIPS/NIPS-1999-5953.pdf %*A Neurodynamical Approach to Visual Attention %@Gustavo Deco,Josef Zihl %t1999 %cNIPS %f/NIPS/NIPS-1999-5954.pdf %*Effects of Spatial and Temporal Contiguity on the Acquisition of Spatial Information %@Thea B. Ghiselli-Crippa,Paul W. Munro %t1999 %cNIPS %f/NIPS/NIPS-1999-5955.pdf %*Acquisition in Autoshaping %@Sham Kakade,Peter Dayan %t1999 %cNIPS %f/NIPS/NIPS-1999-5956.pdf %*Robust Recognition of Noisy and Superimposed Patterns via Selective Attention %@Soo-Young Lee,Michael C. Mozer %t1999 %cNIPS %f/NIPS/NIPS-1999-5957.pdf %*Perceptual Organization Based on Temporal Dynamics %@Xiuwen Liu,DeLiang L. Wang %t1999 %cNIPS %f/NIPS/NIPS-1999-5958.pdf %*Information Factorization in Connectionist Models of Perception %@Javier R. Movellan,James L. McClelland %t1999 %cNIPS %f/NIPS/NIPS-1999-5959.pdf %*Graded Grammaticality in Prediction Fractal Machines %@Shan Parfitt,Peter Tiño,Georg Dorffner %t1999 %cNIPS %f/NIPS/NIPS-1999-5960.pdf %*Evolving Learnable Languages %@Bradley Tonkes,Alan Blair,Janet Wiles %t1999 %cNIPS %f/NIPS/NIPS-1999-5961.pdf %*Learning Statistically Neutral Tasks without Expert Guidance %@Ton Weijters,Antal van den Bosch,Eric O. Postma %t1999 %cNIPS %f/NIPS/NIPS-1999-5962.pdf %*A Generative Model for Attractor Dynamics %@Richard S. Zemel,Michael C. Mozer %t1999 %cNIPS %f/NIPS/NIPS-1999-5963.pdf %*Recurrent Cortical Competition: Strengthen or Weaken? %@Péter Adorján,Lars Schwabe,Christian Piepenbrock,Klaus Obermayer %t1999 %cNIPS %f/NIPS/NIPS-1999-5964.pdf %*Effective Learning Requires Neuronal Remodeling of Hebbian Synapses %@Gal Chechik,Isaac Meilijson,Eytan Ruppin %t1999 %cNIPS %f/NIPS/NIPS-1999-5965.pdf %*Wiring Optimization in the Brain %@Dmitri B. Chklovskii,Charles F. Stevens %t1999 %cNIPS %f/NIPS/NIPS-1999-5966.pdf %*Neural Representation of Multi-Dimensional Stimuli %@Christian W. Eurich,Stefan D. Wilke,Helmut Schwegler %t1999 %cNIPS %f/NIPS/NIPS-1999-5967.pdf %*Spiking Boltzmann Machines %@Geoffrey E. Hinton,Andrew D. Brown %t1999 %cNIPS %f/NIPS/NIPS-1999-5968.pdf %*Distributed Synchrony of Spiking Neurons in a Hebbian Cell Assembly %@David Horn,Nir Levy,Isaac Meilijson,Eytan Ruppin %t1999 %cNIPS %f/NIPS/NIPS-1999-5969.pdf %*Channel Noise in Excitable Neural Membranes %@Amit Manwani,Peter N. Steinmetz,Christof Koch %t1999 %cNIPS %f/NIPS/NIPS-1999-5970.pdf %*LTD Facilitates Learning in a Noisy Environment %@Paul W. Munro,Gerardina Hernández %t1999 %cNIPS %f/NIPS/NIPS-1999-5971.pdf %*Memory Capacity of Linear vs. Nonlinear Models of Dendritic Integration %@Panayiota Poirazi,Bartlett W. Mel %t1999 %cNIPS %f/NIPS/NIPS-1999-5972.pdf %*Predictive Sequence Learning in Recurrent Neocortical Circuits %@Rajesh P. N. Rao,Terrence J. Sejnowski %t1999 %cNIPS %f/NIPS/NIPS-1999-5973.pdf %*A Recurrent Model of the Interaction Between Prefrontal and Inferotemporal Cortex in Delay Tasks %@Alfonso Renart,Néstor Parga,Edmund T. Rolls %t1999 %cNIPS %f/NIPS/NIPS-1999-5974.pdf %*Information Capacity and Robustness of Stochastic Neuron Models %@Elad Schneidman,Idan Segev,Naftali Tishby %t1999 %cNIPS %f/NIPS/NIPS-1999-5975.pdf %*An MEG Study of Response Latency and Variability in the Human Visual System During a Visual-Motor Integration Task %@Akaysha C. Tang,Barak A. Pearlmutter,Tim A. Hely,Michael Zibulevsky,Michael P. Weisend %t1999 %cNIPS %f/NIPS/NIPS-1999-5976.pdf %*Population Decoding Based on an Unfaithful Model %@Si Wu,Hiroyuki Nakahara,Noboru Murata,Shun-ichi Amari %t1999 %cNIPS %f/NIPS/NIPS-1999-5977.pdf %*Spike-based Learning Rules and Stabilization of Persistent Neural Activity %@Xiaohui Xie,H. Sebastian Seung %t1999 %cNIPS %f/NIPS/NIPS-1999-5978.pdf %*Model Selection in Clustering by Uniform Convergence Bounds %@Joachim M. Buhmann,Marcus Held %t1999 %cNIPS %f/NIPS/NIPS-1999-5979.pdf %*Uniqueness of the SVM Solution %@Christopher J. C. Burges,David J. Crisp %t1999 %cNIPS %f/NIPS/NIPS-1999-5980.pdf %*Model Selection for Support Vector Machines %@Olivier Chapelle,Vladimir Vapnik %t1999 %cNIPS %f/NIPS/NIPS-1999-5981.pdf %*Dynamics of Supervised Learning with Restricted Training Sets and Noisy Teachers %@Anthony C. C. Coolen,C. W. H. Mace %t1999 %cNIPS %f/NIPS/NIPS-1999-5982.pdf %*A Geometric Interpretation of v-SVM Classifiers %@David J. Crisp,Christopher J. C. Burges %t1999 %cNIPS %f/NIPS/NIPS-1999-5983.pdf %*Efficient Approaches to Gaussian Process Classification %@Lehel Csató,Ernest Fokoué,Manfred Opper,Bernhard Schottky,Ole Winther %t1999 %cNIPS %f/NIPS/NIPS-1999-5984.pdf %*Potential Boosters? %@Nigel Duffy,David P. Helmbold %t1999 %cNIPS %f/NIPS/NIPS-1999-5985.pdf %*Regular and Irregular Gallager-zype Error-Correcting Codes %@Yoshiyuki Kabashima,Tatsuto Murayama,David Saad,Renato Vicente %t1999 %cNIPS %f/NIPS/NIPS-1999-5986.pdf %*Mixture Density Estimation %@Jonathan Q. Li,Andrew R. Barron %t1999 %cNIPS %f/NIPS/NIPS-1999-5987.pdf %*Statistical Dynamics of Batch Learning %@Song Li,K. Y. Michael Wong %t1999 %cNIPS %f/NIPS/NIPS-1999-5988.pdf %*Boosting with Multi-Way Branching in Decision Trees %@Yishay Mansour,David A. McAllester %t1999 %cNIPS %f/NIPS/NIPS-1999-5989.pdf %*Inference for the Generalization Error %@Claude Nadeau,Yoshua Bengio %t1999 %cNIPS %f/NIPS/NIPS-1999-5990.pdf %*Resonance in a Stochastic Neuron Model with Delayed Interaction %@Toru Ohira,Yuzuru Sato,Jack D. Cowan %t1999 %cNIPS %f/NIPS/NIPS-1999-5991.pdf %*Understanding Stepwise Generalization of Support Vector Machines: a Toy Model %@Sebastian Risau-Gusman,Mirta B. Gordon %t1999 %cNIPS %f/NIPS/NIPS-1999-5992.pdf %*Noisy Neural Networks and Generalizations %@Hava T. Siegelmann,Alexander Roitershtein,Asa Ben-Hur %t1999 %cNIPS %f/NIPS/NIPS-1999-5993.pdf %*The Entropy Regularization Information Criterion %@Alex J. Smola,John Shawe-Taylor,Bernhard Schölkopf,Robert C. Williamson %t1999 %cNIPS %f/NIPS/NIPS-1999-5994.pdf %*Semiparametric Approach to Multichannel Blind Deconvolution of Nonminimum Phase Systems %@Liqing Zhang,Shun-ichi Amari,Andrzej Cichocki %t1999 %cNIPS %f/NIPS/NIPS-1999-5995.pdf %*Robust Full Bayesian Methods for Neural Networks %@Christophe Andrieu,João F. G. de Freitas,Arnaud Doucet %t1999 %cNIPS %f/NIPS/NIPS-1999-5996.pdf %*Gaussian Fields for Approximate Inference in Layered Sigmoid Belief Networks %@David Barber,Peter Sollich %t1999 %cNIPS %f/NIPS/NIPS-1999-5997.pdf %*Modeling High-Dimensional Discrete Data with Multi-Layer Neural Networks %@Yoshua Bengio,Samy Bengio %t1999 %cNIPS %f/NIPS/NIPS-1999-5998.pdf %*Robust Neural Network Regression for Offline and Online Learning %@Thomas Briegel,Volker Tresp %t1999 %cNIPS %f/NIPS/NIPS-1999-5999.pdf %*Transductive Inference for Estimating Values of Functions %@Olivier Chapelle,Vladimir Vapnik,Jason Weston %t1999 %cNIPS %f/NIPS/NIPS-1999-6000.pdf %*The Nonnegative Boltzmann Machine %@Oliver B. Downs,David J. C. MacKay,Daniel D. Lee %t1999 %cNIPS %f/NIPS/NIPS-1999-6001.pdf %*Differentiating Functions of the Jacobian with Respect to the Weights %@Gary William Flake,Barak A. Pearlmutter %t1999 %cNIPS %f/NIPS/NIPS-1999-6002.pdf %*Variational Inference for Bayesian Mixtures of Factor Analysers %@Zoubin Ghahramani,Matthew J. Beal %t1999 %cNIPS %f/NIPS/NIPS-1999-6003.pdf %*Bayesian Transduction %@Thore Graepel,Ralf Herbrich,Klaus Obermayer %t1999 %cNIPS %f/NIPS/NIPS-1999-6004.pdf %*Learning to Parse Images %@Geoffrey E. Hinton,Zoubin Ghahramani,Yee Whye Teh %t1999 %cNIPS %f/NIPS/NIPS-1999-6005.pdf %*Maximum Entropy Discrimination %@Tommi Jaakkola,Marina Meila,Tony Jebara %t1999 %cNIPS %f/NIPS/NIPS-1999-6006.pdf %*Topographic Transformation as a Discrete Latent Variable %@Nebojsa Jojic,Brendan J. Frey %t1999 %cNIPS %f/NIPS/NIPS-1999-6007.pdf %*Algorithms for Independent Components Analysis and Higher Order Statistics %@Daniel D. Lee,Uri Rokni,Haim Sompolinsky %t1999 %cNIPS %f/NIPS/NIPS-1999-6008.pdf %*The Relaxed Online Maximum Margin Algorithm %@Yi Li,Philip M. Long %t1999 %cNIPS %f/NIPS/NIPS-1999-6009.pdf %*Bayesian Network Induction via Local Neighborhoods %@Dimitris Margaritis,Sebastian Thrun %t1999 %cNIPS %f/NIPS/NIPS-1999-6010.pdf %*Boosting Algorithms as Gradient Descent %@Llew Mason,Jonathan Baxter,Peter L. Bartlett,Marcus R. Frean %t1999 %cNIPS %f/NIPS/NIPS-1999-6011.pdf %*Invariant Feature Extraction and Classification in Kernel Spaces %@Sebastian Mika,Gunnar Rätsch,Jason Weston,Bernhard Schölkopf,Alex J. Smola,Klaus-Robert Müller %t1999 %cNIPS %f/NIPS/NIPS-1999-6012.pdf %*Approximate Inference A lgorithms for Two-Layer Bayesian Networks %@Andrew Y. Ng,Michael I. Jordan %t1999 %cNIPS %f/NIPS/NIPS-1999-6013.pdf %*Optimal Kernel Shapes for Local Linear Regression %@Dirk Ormoneit,Trevor Hastie %t1999 %cNIPS %f/NIPS/NIPS-1999-6014.pdf %*Large Margin DAGs for Multiclass Classification %@John C. Platt,Nello Cristianini,John Shawe-Taylor %t1999 %cNIPS %f/NIPS/NIPS-1999-6015.pdf %*v-Arc: Ensemble Learning in the Presence of Outliers %@Gunnar Rätsch,Bernhard Schölkopf,Alex J. Smola,Klaus-Robert Müller,Takashi Onoda,Sebastian Mika %t1999 %cNIPS %f/NIPS/NIPS-1999-6016.pdf %*Nonlinear Discriminant Analysis Using Kernel Functions %@Volker Roth,Volker Steinhage %t1999 %cNIPS %f/NIPS/NIPS-1999-6017.pdf %*An Analysis of Turbo Decoding with Gaussian Densities %@Paat Rusmevichientong,Benjamin Van Roy %t1999 %cNIPS %f/NIPS/NIPS-1999-6018.pdf %*Support Vector Method for Novelty Detection %@Bernhard Schölkopf,Robert C. Williamson,Alex J. Smola,John Shawe-Taylor,John C. Platt %t1999 %cNIPS %f/NIPS/NIPS-1999-6019.pdf %*Agglomerative Information Bottleneck %@Noam Slonim,Naftali Tishby %t1999 %cNIPS %f/NIPS/NIPS-1999-6020.pdf %*Training Data Selection for Optimal Generalization in Trigonometric Polynomial Networks %@Masashi Sugiyama,Hidemitsu Ogawa %t1999 %cNIPS %f/NIPS/NIPS-1999-6021.pdf %*Predictive App roaches for Choosing Hyperparameters in Gaussian Processes %@S. Sundararajan,S. Sathiya Keerthi %t1999 %cNIPS %f/NIPS/NIPS-1999-6022.pdf %*Building Predictive Models from Fractal Representations of Symbolic Sequences %@Peter Tiño,Georg Dorffner %t1999 %cNIPS %f/NIPS/NIPS-1999-6023.pdf %*Support Vector Method for Multivariate Density Estimation %@Vladimir Vapnik,Sayan Mukherjee %t1999 %cNIPS %f/NIPS/NIPS-1999-6024.pdf %*Dual Estimation and the Unscented Transformation %@Eric A. Wan,Rudolph van der Merwe,Alex T. Nelson %t1999 %cNIPS %f/NIPS/NIPS-1999-6025.pdf %*Correctness of Belief Propagation in Gaussian Graphical Models of Arbitrary Topology %@Yair Weiss,William T. Freeman %t1999 %cNIPS %f/NIPS/NIPS-1999-6026.pdf %*Data Visualization and Feature Selection: New Algorithms for Nongaussian Data %@Howard Hua Yang,John Moody %t1999 %cNIPS %f/NIPS/NIPS-1999-6027.pdf %*Manifold Stochastic Dynamics for Bayesian Learning %@Mark Zlochin,Yoram Baram %t1999 %cNIPS %f/NIPS/NIPS-1999-6028.pdf %*The Parallel Problems Server: an Interactive Tool for Large Scale Machine Learning %@Charles Lee Isbell Jr.,Parry Husbands %t1999 %cNIPS %f/NIPS/NIPS-1999-6029.pdf %*An Oculo-Motor System with Multi-Chip Neuromorphic Analog VLSI Control %@Oliver Landolt,Steve Gyger %t1999 %cNIPS %f/NIPS/NIPS-1999-6030.pdf %*A Neuromorphic VLSI System for Modeling the Neural Control of Axial Locomotion %@Girish N. Patel,Edgar A. Brown,Stephen P. DeWeerth %t1999 %cNIPS %f/NIPS/NIPS-1999-6031.pdf %*Bifurcation Analysis of a Silicon Neuron %@Girish N. Patel,Gennady S. Cymbalyuk,Ronald L. Calabrese,Stephen P. DeWeerth %t1999 %cNIPS %f/NIPS/NIPS-1999-6032.pdf %*An Oscillatory Correlation Frame work for Computational Auditory Scene Analysis %@Guy J. Brown,DeLiang L. Wang %t1999 %cNIPS %f/NIPS/NIPS-1999-6033.pdf %*Bayesian Modelling of fMRI lime Series %@Pedro A. d. F. R. Højen-Sørensen,Lars Kai Hansen,Carl Edward Rasmussen %t1999 %cNIPS %f/NIPS/NIPS-1999-6034.pdf %*Neural System Model of Human Sound Localization %@Craig T. Jin,Simon Carlile %t1999 %cNIPS %f/NIPS/NIPS-1999-6035.pdf %*Spectral Cues in Human Sound Localization %@Craig T. Jin,Anna Corderoy,Simon Carlile,André van Schaik %t1999 %cNIPS %f/NIPS/NIPS-1999-6036.pdf %*Broadband Direction-Of-Arrival Estimation Based on Second Order Statistics %@Justinian P. Rosca,Joseph Ó Ruanaidh,Alexander Jourjine,Scott Rickard %t1999 %cNIPS %f/NIPS/NIPS-1999-6037.pdf %*Online Independent Component Analysis with Local Learning Rate Adaptation %@Nicol N. Schraudolph,Xavier Giannakopoulos %t1999 %cNIPS %f/NIPS/NIPS-1999-6038.pdf %*Speech Modelling Using Subspace and EM Techniques %@Gavin Smith,João F. G. de Freitas,Tony Robinson,Mahesan Niranjan %t1999 %cNIPS %f/NIPS/NIPS-1999-6039.pdf %*Search for Information Bearing Components in Speech %@Howard Hua Yang,Hynek Hermansky %t1999 %cNIPS %f/NIPS/NIPS-1999-6040.pdf %*Audio Vision: Using Audio-Visual Synchrony to Locate Sounds %@John R. Hershey,Javier R. Movellan %t1999 %cNIPS %f/NIPS/NIPS-1999-6041.pdf %*Bayesian Reconstruction of 3D Human Motion from Single-Camera Video %@Nicholas R. Howe,Michael E. Leventon,William T. Freeman %t1999 %cNIPS %f/NIPS/NIPS-1999-6042.pdf %*Emergence of Topography and Complex Cell Properties from Natural Images using Extensions of ICA %@Aapo Hyvärinen,Patrik O. Hoyer %t1999 %cNIPS %f/NIPS/NIPS-1999-6043.pdf %*An Information-Theoretic Framework for Understanding Saccadic Eye Movements %@Tai Sing Lee,Stella X. Yu %t1999 %cNIPS %f/NIPS/NIPS-1999-6044.pdf %*Learning Sparse Codes with a Mixture-of-Gaussians Prior %@Bruno A. Olshausen,K. Jarrod Millman %t1999 %cNIPS %f/NIPS/NIPS-1999-6045.pdf %*Hierarchical Image Probability (H1P) Models %@Clay Spence,Lucas C. Parra %t1999 %cNIPS %f/NIPS/NIPS-1999-6046.pdf %*Scale Mixtures of Gaussians and the Statistics of Natural Images %@Martin J. Wainwright,Eero P. Simoncelli %t1999 %cNIPS %f/NIPS/NIPS-1999-6047.pdf %*A SNoW-Based Face Detector %@Ming-Hsuan Yang,Dan Roth,Narendra Ahuja %t1999 %cNIPS %f/NIPS/NIPS-1999-6048.pdf %*Managing Uncertainty in Cue Combination %@Zhiyong Yang,Richard S. Zemel %t1999 %cNIPS %f/NIPS/NIPS-1999-6049.pdf %*Robust Learning of Chaotic Attractors %@Rembrandt Bakker,Jaap C. Schouten,Marc-Olivier Coppens,Floris Takens,C. Lee Giles,Cor M. van den Bleek %t1999 %cNIPS %f/NIPS/NIPS-1999-6050.pdf %*Image Representations for Facial Expression Coding %@Marian Stewart Bartlett,Gianluca Donato,Javier R. Movellan,Joseph C. Hager,Paul Ekman,Terrence J. Sejnowski %t1999 %cNIPS %f/NIPS/NIPS-1999-6051.pdf %*Learning Informative Statistics: A Nonparametnic Approach %@John W. Fisher III,Alexander T. Ihler,Paul A. Viola %t1999 %cNIPS %f/NIPS/NIPS-1999-6052.pdf %*Constructing Heterogeneous Committees Using Input Feature Grouping: Application to Economic Forecasting %@Yuansong Liao,John E. Moody %t1999 %cNIPS %f/NIPS/NIPS-1999-6053.pdf %*From Coexpression to Coregulation: An Approach to Inferring Transcriptional Regulation among Gene Classes from Large-Scale Expression Data %@Eric Mjolsness,Tobias Mann,Rebecca Castaño,Barbara J. Wold %t1999 %cNIPS %f/NIPS/NIPS-1999-6054.pdf %*Churn Reduction in the Wireless Industry %@Michael C. Mozer,Richard H. Wolniewicz,David B. Grimes,Eric Johnson,Howard Kaushansky %t1999 %cNIPS %f/NIPS/NIPS-1999-6055.pdf %*Unmixing Hyperspectral Data %@Lucas C. Parra,Clay Spence,Paul Sajda,Andreas Ziehe,Klaus-Robert Müller %t1999 %cNIPS %f/NIPS/NIPS-1999-6056.pdf %*Application of Blind Separation of Sources to Optical Recording of Brain Activity %@Holger Schoner,Martin Stetter,Ingo Schießl,John E. W. Mayhew,Jennifer S. Lund,Niall McLoughlin,Klaus Obermayer %t1999 %cNIPS %f/NIPS/NIPS-1999-6057.pdf %*Reinforcement Learning for Spoken Dialogue Systems %@Satinder P. Singh,Michael J. Kearns,Diane J. Litman,Marilyn A. Walker %t1999 %cNIPS %f/NIPS/NIPS-1999-6058.pdf %*Image Recognition in Context: Application to Microscopic Urinalysis %@Xubo B. Song,Joseph Sill,Yaser S. Abu-Mostafa,Harvey Kasdan %t1999 %cNIPS %f/NIPS/NIPS-1999-6059.pdf %*Generalized Model Selection for Unsupervised Learning in High Dimensions %@Shivakumar Vaithyanathan,Byron Dom %t1999 %cNIPS %f/NIPS/NIPS-1999-6060.pdf %*Learning from User Feedback in Image Retrieval Systems %@Nuno Vasconcelos,Andrew Lippman %t1999 %cNIPS %f/NIPS/NIPS-1999-6061.pdf %*An Environment Model for Nonstationary Reinforcement Learning %@Samuel P. M. Choi,Dit-Yan Yeung,Nevin Lianwen Zhang %t1999 %cNIPS %f/NIPS/NIPS-1999-6062.pdf %*Approximate Planning in Large POMDPs via Reusable Trajectories %@Michael J. Kearns,Yishay Mansour,Andrew Y. Ng %t1999 %cNIPS %f/NIPS/NIPS-1999-6063.pdf %*Actor-Critic Algorithms %@Vijay R. Konda,John N. Tsitsiklis %t1999 %cNIPS %f/NIPS/NIPS-1999-6064.pdf %*Policy Search via Density Estimation %@Andrew Y. Ng,Ronald Parr,Daphne Koller %t1999 %cNIPS %f/NIPS/NIPS-1999-6065.pdf %*Neural Network Based Model Predictive Control %@Stephen Piche,James D. Keeler,Greg Martin,Gene Boe,Doug Johnson,Mark Gerules %t1999 %cNIPS %f/NIPS/NIPS-1999-6066.pdf %*Reinforcement Learning Using Approximate Belief States %@Andres C. Rodriguez,Ronald Parr,Daphne Koller %t1999 %cNIPS %f/NIPS/NIPS-1999-6067.pdf %*Coastal Navigation with Mobile Robots %@Nicholas Roy,Sebastian Thrun %t1999 %cNIPS %f/NIPS/NIPS-1999-6068.pdf %*Policy Gradient Methods for Reinforcement Learning with Function Approximation %@Richard S. Sutton,David A. McAllester,Satinder P. Singh,Yishay Mansour %t1999 %cNIPS %f/NIPS/NIPS-1999-6069.pdf %*Evidence for a Forward Dynamics Model in Human Adaptive Motor Control %@Nikhil Bhushan,Reza Shadmehr %t1998 %cNIPS %f/NIPS/NIPS-1998-6070.pdf %*Perceiving without Learning: From Spirals to Inside/Outside Relations %@Ke Chen,DeLiang L. Wang %t1998 %cNIPS %f/NIPS/NIPS-1998-6071.pdf %*A Model for Associative Multiplication %@G. Bjorn Christianson,Suzanna Becker %t1998 %cNIPS %f/NIPS/NIPS-1998-6072.pdf %*Facial Memory Is Kernel Density Estimation (Almost) %@Matthew N. Dailey,Garrison W. Cottrell,Thomas A. Busey %t1998 %cNIPS %f/NIPS/NIPS-1998-6073.pdf %*Multiple Paired Forward-Inverse Models for Human Motor Learning and Control %@Masahiko Haruno,Daniel M. Wolpert,Mitsuo Kawato %t1998 %cNIPS %f/NIPS/NIPS-1998-6074.pdf %*Mechanisms of Generalization in Perceptual Learning %@Zili Liu,Daphna Weinshall %t1998 %cNIPS %f/NIPS/NIPS-1998-6075.pdf %*Temporally Asymmetric Hebbian Learning, Spike liming and Neural Response Variability %@L. F. Abbott,Sen Song %t1998 %cNIPS %f/NIPS/NIPS-1998-6076.pdf %*Contrast Adaptation in Simple Cells by Changing the Transmitter Release Probability %@Péter Adorján,Klaus Obermayer %t1998 %cNIPS %f/NIPS/NIPS-1998-6077.pdf %*Where Does the Population Vector of Motor Cortical Cells Point during Reaching Movements? %@Pierre Baraduc,Emmanuel Guigon,Yves Burnod %t1998 %cNIPS %f/NIPS/NIPS-1998-6078.pdf %*Recurrent Cortical Amplification Produces Complex Cell Responses %@Frances S. Chance,Sacha B. Nelson,L. F. Abbott %t1998 %cNIPS %f/NIPS/NIPS-1998-6079.pdf %*Neuronal Regulation Implements Efficient Synaptic Pruning %@Gal Chechik,Isaac Meilijson,Eytan Ruppin %t1998 %cNIPS %f/NIPS/NIPS-1998-6080.pdf %*Divisive Normalization, Line Attractor Networks and Ideal Observers %@Sophie Denève,Alexandre Pouget,Peter E. Latham %t1998 %cNIPS %f/NIPS/NIPS-1998-6081.pdf %*Synergy and Redundancy among Brain Cells of Behaving Monkeys %@Itay Gat,Naftali Tishby %t1998 %cNIPS %f/NIPS/NIPS-1998-6082.pdf %*Analyzing and Visualizing Single-Trial Event-Related Potentials %@Tzyy-Ping Jung,Scott Makeig,Marissa Westerfield,Jeanne Townsend,Eric Courchesne,Terrence J. Sejnowski %t1998 %cNIPS %f/NIPS/NIPS-1998-6083.pdf %*Spike-Based Compared to Rate-Based Hebbian Learning %@Richard Kempter,Wulfram Gerstner,J. Leo van Hemmen %t1998 %cNIPS %f/NIPS/NIPS-1998-6084.pdf %*Signal Detection in Noisy Weakly-Active Dendrites %@Amit Manwani,Christof Koch %t1998 %cNIPS %f/NIPS/NIPS-1998-6085.pdf %*The Role of Lateral Cortical Competition in Ocular Dominance Development %@Christian Piepenbrock,Klaus Obermayer %t1998 %cNIPS %f/NIPS/NIPS-1998-6086.pdf %*Multi-Electrode Spike Sorting by Clustering Transfer Functions %@Dmitry Rinberg,Hanan Davidowitz,Naftali Tishby %t1998 %cNIPS %f/NIPS/NIPS-1998-6087.pdf %*Modeling Surround Suppression in V1 Neurons with a Statistically Derived Normalization Model %@Eero P. Simoncelli,Odelia Schwartz %t1998 %cNIPS %f/NIPS/NIPS-1998-6088.pdf %*Information Maximization in Single Neurons %@Martin Stemmler,Christof Koch %t1998 %cNIPS %f/NIPS/NIPS-1998-6089.pdf %*The Effect of Correlations on the Fisher Information of Population Codes %@Hyoungsoo Yoon,Haim Sompolinsky %t1998 %cNIPS %f/NIPS/NIPS-1998-6090.pdf %*Distributional Population Codes and Multiple Motion Models %@Richard S. Zemel,Peter Dayan %t1998 %cNIPS %f/NIPS/NIPS-1998-6091.pdf %*Tractable Variational Structures for Approximating Graphical Models %@David Barber,Wim Wiegerinck %t1998 %cNIPS %f/NIPS/NIPS-1998-6092.pdf %*Almost Linear VC Dimension Bounds for Piecewise Polynomial Networks %@Peter L. Bartlett,Vitaly Maiorov,Ron Meir %t1998 %cNIPS %f/NIPS/NIPS-1998-6093.pdf %*Dynamics of Supervised Learning with Restricted Training Sets %@Anthony C. C. Coolen,David Saad %t1998 %cNIPS %f/NIPS/NIPS-1998-6094.pdf %*Dynamically Adapting Kernels in Support Vector Machines %@Nello Cristianini,Colin Campbell,John Shawe-Taylor %t1998 %cNIPS %f/NIPS/NIPS-1998-6095.pdf %*Phase Diagram and Storage Capacity of Sequence-Storing Neural Networks %@A. Düring,Anthony C. C. Coolen,D. Sherrington %t1998 %cNIPS %f/NIPS/NIPS-1998-6096.pdf %*Finite-Dimensional Approximation of Gaussian Processes %@Giancarlo Ferrari-Trecate,Christopher K. I. Williams,Manfred Opper %t1998 %cNIPS %f/NIPS/NIPS-1998-6097.pdf %*Linear Hinge Loss and Average Margin %@Claudio Gentile,Manfred K. Warmuth %t1998 %cNIPS %f/NIPS/NIPS-1998-6098.pdf %*Unsupervised and Supervised Clustering: The Mutual Information between Parameters and Observations %@Didier Herschkowitz,Jean-Pierre Nadal %t1998 %cNIPS %f/NIPS/NIPS-1998-6099.pdf %*Convergence of the Wake-Sleep Algorithm %@Shiro Ikeda,Shun-ichi Amari,Hiroyuki Nakahara %t1998 %cNIPS %f/NIPS/NIPS-1998-6100.pdf %*The Belief in TAP %@Yoshiyuki Kabashima,David Saad %t1998 %cNIPS %f/NIPS/NIPS-1998-6101.pdf %*Optimizing Classifers for Imbalanced Training Sets %@Grigoris I. Karakoulas,John Shawe-Taylor %t1998 %cNIPS %f/NIPS/NIPS-1998-6102.pdf %*Inference in Multilayer Networks via Large Deviation Bounds %@Michael J. Kearns,Lawrence K. Saul %t1998 %cNIPS %f/NIPS/NIPS-1998-6103.pdf %*Stationarity and Stability of Autoregressive Neural Network Processes %@Friedrich Leisch,Adrian Trapletti,Kurt Hornik %t1998 %cNIPS %f/NIPS/NIPS-1998-6104.pdf %*Computational Differences between Asymmetrical and Symmetrical Networks %@Zhaoping Li,Peter Dayan %t1998 %cNIPS %f/NIPS/NIPS-1998-6105.pdf %*A Precise Characterization of the Class of Languages Recognized by Neural Nets under Gaussian and Other Common Noise Distributions %@Wolfgang Maass,Eduardo D. Sontag %t1998 %cNIPS %f/NIPS/NIPS-1998-6106.pdf %*Direct Optimization of Margins Improves Generalization in Combined Classifiers %@Llew Mason,Peter L. Bartlett,Jonathan Baxter %t1998 %cNIPS %f/NIPS/NIPS-1998-6107.pdf %*On the Optimality of Incremental Neural Network Algorithms %@Ron Meir,Vitaly Maiorov %t1998 %cNIPS %f/NIPS/NIPS-1998-6108.pdf %*General Bounds on Bayes Errors for Regression with Gaussian Processes %@Manfred Opper,Francesco Vivarelli %t1998 %cNIPS %f/NIPS/NIPS-1998-6109.pdf %*Mean Field Methods for Classification with Gaussian Processes %@Manfred Opper,Ole Winther %t1998 %cNIPS %f/NIPS/NIPS-1998-6110.pdf %*On-Line Learning with Restricted Training Sets: Exact Solution as Benchmark for General Theories %@H. C. Rae,Peter Sollich,Anthony C. C. Coolen %t1998 %cNIPS %f/NIPS/NIPS-1998-6111.pdf %*Shrinking the Tube: A New Support Vector Regression Algorithm %@Bernhard Schölkopf,Peter L. Bartlett,Alex J. Smola,Robert C. Williamson %t1998 %cNIPS %f/NIPS/NIPS-1998-6112.pdf %*Discontinuous Recall Transitions Induced by Competition Between Short- and Long-Range Interactions in Recurrent Networks %@N. S. Skantzos,C. F. Beckmann,Anthony C. C. Coolen %t1998 %cNIPS %f/NIPS/NIPS-1998-6113.pdf %*Semi-Supervised Support Vector Machines %@Kristin P. Bennett,Ayhan Demiriz %t1998 %cNIPS %f/NIPS/NIPS-1998-6114.pdf %*Lazy Learning Meets the Recursive Least Squares Algorithm %@Mauro Birattari,Gianluca Bontempi,Hugues Bersini %t1998 %cNIPS %f/NIPS/NIPS-1998-6115.pdf %*Learning Multi-Class Dynamics %@Andrew Blake,Ben North,Michael Isard %t1998 %cNIPS %f/NIPS/NIPS-1998-6116.pdf %*Approximate Learning of Dynamic Models %@Xavier Boyen,Daphne Koller %t1998 %cNIPS %f/NIPS/NIPS-1998-6117.pdf %*Fisher Scoring and a Mixture of Modes Approach for Approximate Inference and Learning in Nonlinear State Space Models %@Thomas Briegel,Volker Tresp %t1998 %cNIPS %f/NIPS/NIPS-1998-6118.pdf %*Global Optimisation of Neural Network Models via Sequential Sampling %@João F. G. de Freitas,Mahesan Niranjan,Arnaud Doucet,Andrew H. Gee %t1998 %cNIPS %f/NIPS/NIPS-1998-6119.pdf %*Efficient Bayesian Parameter Estimation in Large Discrete Domains %@Nir Friedman,Yoram Singer %t1998 %cNIPS %f/NIPS/NIPS-1998-6120.pdf %*A Randomized Algorithm for Pairwise Clustering %@Yoram Gdalyahu,Daphna Weinshall,Michael Werman %t1998 %cNIPS %f/NIPS/NIPS-1998-6121.pdf %*Learning Nonlinear Dynamical Systems Using an EM Algorithm %@Zoubin Ghahramani,Sam T. Roweis %t1998 %cNIPS %f/NIPS/NIPS-1998-6122.pdf %*Classification on Pairwise Proximity Data %@Thore Graepel,Ralf Herbrich,Peter Bollmann-Sdorra,Klaus Obermayer %t1998 %cNIPS %f/NIPS/NIPS-1998-6123.pdf %*Outcomes of the Equivalence of Adaptive Ridge with Least Absolute Shrinkage %@Yves Grandvalet,Stéphane Canu %t1998 %cNIPS %f/NIPS/NIPS-1998-6124.pdf %*Visualizing Group Structure %@Marcus Held,Jan Puzicha,Joachim M. Buhmann %t1998 %cNIPS %f/NIPS/NIPS-1998-6125.pdf %*Source Separation as a By-Product of Regularization %@Sepp Hochreiter,Juergen Schmidhuber %t1998 %cNIPS %f/NIPS/NIPS-1998-6126.pdf %*Learning from Dyadic Data %@Thomas Hofmann,Jan Puzicha,Michael I. Jordan %t1998 %cNIPS %f/NIPS/NIPS-1998-6127.pdf %*Sparse Code Shrinkage: Denoising by Nonlinear Maximum Likelihood Estimation %@Aapo Hyvärinen,Patrik O. Hoyer,Erkki Oja %t1998 %cNIPS %f/NIPS/NIPS-1998-6128.pdf %*Restructuring Sparse High Dimensional Data for Effective Retrieval %@Charles Lee Isbell Jr.,Paul A. Viola %t1998 %cNIPS %f/NIPS/NIPS-1998-6129.pdf %*Exploiting Generative Models in Discriminative Classifiers %@Tommi Jaakkola,David Haussler %t1998 %cNIPS %f/NIPS/NIPS-1998-6130.pdf %*Maximum Conditional Likelihood via Bound Maximization and the CEM Algorithm %@Tony Jebara,Alex Pentland %t1998 %cNIPS %f/NIPS/NIPS-1998-6131.pdf %*A Polygonal Line Algorithm for Constructing Principal Curves %@Balázs Kégl,Adam Krzyzak,Tamás Linder,Kenneth Zeger %t1998 %cNIPS %f/NIPS/NIPS-1998-6132.pdf %*Unsupervised Classification with Non-Gaussian Mixture Models Using ICA %@Te-Won Lee,Michael S. Lewicki,Terrence J. Sejnowski %t1998 %cNIPS %f/NIPS/NIPS-1998-6133.pdf %*Learning a Continuous Hidden Variable Model for Binary Data %@Daniel D. Lee,Haim Sompolinsky %t1998 %cNIPS %f/NIPS/NIPS-1998-6134.pdf %*Neural Networks for Density Estimation %@Malik Magdon-Ismail,Amir F. Atiya %t1998 %cNIPS %f/NIPS/NIPS-1998-6135.pdf %*Exploratory Data Analysis Using Radial Basis Function Latent Variable Models %@Alan D. Marrs,Andrew R. Webb %t1998 %cNIPS %f/NIPS/NIPS-1998-6136.pdf %*Kernel PCA and De-Noising in Feature Spaces %@Sebastian Mika,Bernhard Schölkopf,Alex J. Smola,Klaus-Robert Müller,Matthias Scholz,Gunnar Rätsch %t1998 %cNIPS %f/NIPS/NIPS-1998-6137.pdf %*Regularizing AdaBoost %@Gunnar Rätsch,Takashi Onoda,Klaus R. Müller %t1998 %cNIPS %f/NIPS/NIPS-1998-6138.pdf %*Boxlets: A Fast Convolution Algorithm for Signal Processing and Neural Networks %@Patrice Simard,Léon Bottou,Patrick Haffner,Yann LeCun %t1998 %cNIPS %f/NIPS/NIPS-1998-6139.pdf %*Batch and On-Line Parameter Estimation of Gaussian Mixtures Based on the Joint Entropy %@Yoram Singer,Manfred K. Warmuth %t1998 %cNIPS %f/NIPS/NIPS-1998-6140.pdf %*Semiparametric Support Vector and Linear Programming Machines %@Alex J. Smola,Thilo-Thomas Frieß,Bernhard Schölkopf %t1998 %cNIPS %f/NIPS/NIPS-1998-6141.pdf %*SMEM Algorithm for Mixture Models %@Naonori Ueda,Ryohei Nakano,Zoubin Ghahramani,Geoffrey E. Hinton %t1998 %cNIPS %f/NIPS/NIPS-1998-6142.pdf %*Learning Mixture Hierarchies %@Nuno Vasconcelos,Andrew Lippman %t1998 %cNIPS %f/NIPS/NIPS-1998-6143.pdf %*Discovering Hidden Features with Gaussian Processes Regression %@Francesco Vivarelli,Christopher K. I. Williams %t1998 %cNIPS %f/NIPS/NIPS-1998-6144.pdf %*The Bias-Variance Tradeoff and the Randomized GACV %@Grace Wahba,Xiwu Lin,Fangyu Gao,Dong Xiang,Ronald Klein,Barbara Klein %t1998 %cNIPS %f/NIPS/NIPS-1998-6145.pdf %*Basis Selection for Wavelet Regression %@Kevin R. Wheeler,Atam P. Dhawan %t1998 %cNIPS %f/NIPS/NIPS-1998-6146.pdf %*DTs: Dynamic Trees %@Christopher K. I. Williams,Nicholas J. Adams %t1998 %cNIPS %f/NIPS/NIPS-1998-6147.pdf %*Convergence Rates of Algorithms for Visual Search: Detecting Visual Contours %@Alan L. Yuille,James M. Coughlan %t1998 %cNIPS %f/NIPS/NIPS-1998-6148.pdf %*Blind Separation of Filtered Sources Using State-Space Approach %@Liqing Zhang,Andrzej Cichocki %t1998 %cNIPS %f/NIPS/NIPS-1998-6149.pdf %*Analog VLSI Cellular Implementation of the Boundary Contour System %@Gert Cauwenberghs,James Waskiewicz %t1998 %cNIPS %f/NIPS/NIPS-1998-6150.pdf %*Active Noise Canceling Using Analog Neuro-Chip with On-Chip Learning Capability %@Jung-Wook Cho,Soo-Young Lee %t1998 %cNIPS %f/NIPS/NIPS-1998-6151.pdf %*A Micropower CMOS Adaptive Amplitude and Shift Invariant Vector Quantiser %@Richard Coggins,Raymond J. Wang,Marwan A. Jabri %t1998 %cNIPS %f/NIPS/NIPS-1998-6152.pdf %*Optimizing Correlation Algorithms for Hardware-Based Transient Classification %@R. Timothy Edwards,Gert Cauwenberghs,Fernando J. Pineda %t1998 %cNIPS %f/NIPS/NIPS-1998-6153.pdf %*VLSI Implementation of Motion Centroid Localization for Autonomous Navigation %@Ralph Etienne-Cummings,Viktor Gruev,Mohammed Abdel Ghani %t1998 %cNIPS %f/NIPS/NIPS-1998-6154.pdf %*A Neuromorphic Monaural Sound Localizer %@John G. Harris,Chiang-Jung Pu,José Carlos Príncipe %t1998 %cNIPS %f/NIPS/NIPS-1998-6155.pdf %*An Integrated Vision Sensor for the Computation of Optical Flow Singular Points %@Charles M. Higgins,Christof Koch %t1998 %cNIPS %f/NIPS/NIPS-1998-6156.pdf %*Computation of Smooth Optical Flow in a Feedback Connected Analog Network %@Alan Stocker,Rodney J. Douglas %t1998 %cNIPS %f/NIPS/NIPS-1998-6157.pdf %*A High Performance k-NN Classifier Using a Binary Correlation Matrix Memory %@Ping Zhou,Jim Austin,John Kennedy %t1998 %cNIPS %f/NIPS/NIPS-1998-6158.pdf %*Coding Time-Varying Signals Using Sparse, Shift-Invariant Representations %@Michael S. Lewicki,Terrence J. Sejnowski %t1998 %cNIPS %f/NIPS/NIPS-1998-6159.pdf %*Controlling the Complexity of HMM Systems by Regularization %@Christoph Neukirchen,Gerhard Rigoll %t1998 %cNIPS %f/NIPS/NIPS-1998-6160.pdf %*Maximum-Likelihood Continuity Mapping (MALCOM): An Alternative to HMMs %@David A. Nix,John E. Hogden %t1998 %cNIPS %f/NIPS/NIPS-1998-6161.pdf %*Markov Processes on Curves for Automatic Speech Recognition %@Lawrence K. Saul,Mazin G. Rahim %t1998 %cNIPS %f/NIPS/NIPS-1998-6162.pdf %*A Phase Space Approach to Minimax Entropy Learning and the Minutemax Approximations %@James M. Coughlan,Alan L. Yuille %t1998 %cNIPS %f/NIPS/NIPS-1998-6163.pdf %*Learning to Estimate Scenes from Images %@William T. Freeman,Egon C. Pasztor %t1998 %cNIPS %f/NIPS/NIPS-1998-6164.pdf %*Learning to Find Pictures of People %@Sergey Ioffe,David A. Forsyth %t1998 %cNIPS %f/NIPS/NIPS-1998-6165.pdf %*Attentional Modulation of Human Pattern Discrimination Psychophysics Reproduced by a Quantitative Model %@Laurent Itti,Jochen Braun,Dale K. Lee,Christof Koch %t1998 %cNIPS %f/NIPS/NIPS-1998-6166.pdf %*Learning Lie Groups for Invariant Visual Perception %@Rajesh P. N. Rao,Daniel L. Ruderman %t1998 %cNIPS %f/NIPS/NIPS-1998-6167.pdf %*Probabilistic Image Sensor Fusion %@Ravi K. Sharma,Todd K. Leen,Misha Pavel %t1998 %cNIPS %f/NIPS/NIPS-1998-6168.pdf %*Orientation, Scale, and Discontinuity as Emergent Properties of Illusory Contour Shape %@Karvel K. Thornber,Lance R. Williams %t1998 %cNIPS %f/NIPS/NIPS-1998-6169.pdf %*Classification in Non-Metric Spaces %@Daphna Weinshall,David W. Jacobs,Yoram Gdalyahu %t1998 %cNIPS %f/NIPS/NIPS-1998-6170.pdf %*Adding Constrained Discontinuities to Gaussian Process Models of Wind Fields %@Dan Cornford,Ian T. Nabney,Christopher K. I. Williams %t1998 %cNIPS %f/NIPS/NIPS-1998-6171.pdf %*Vertex Identification in High Energy Physics Experiments %@Gideon Dror,Halina Abramowicz,David Horn %t1998 %cNIPS %f/NIPS/NIPS-1998-6172.pdf %*Familiarity Discrimination of Radar Pulses %@Eric Granger,Stephen Grossberg,Mark A. Rubin,William W. Streilein %t1998 %cNIPS %f/NIPS/NIPS-1998-6173.pdf %*Fast Neural Network Emulation of Dynamical Systems for Computer Animation %@Radek Grzeszczuk,Demetri Terzopoulos,Geoffrey E. Hinton %t1998 %cNIPS %f/NIPS/NIPS-1998-6174.pdf %*Call-Based Fraud Detection in Mobile Communication Networks Using a Hierarchical Regime-Switching Model %@Jaakko Hollmén,Volker Tresp %t1998 %cNIPS %f/NIPS/NIPS-1998-6175.pdf %*Graph Matching for Shape Retrieval %@Benoit Huet,Andrew D. J. Cross,Edwin R. Hancock %t1998 %cNIPS %f/NIPS/NIPS-1998-6176.pdf %*Scheduling Straight-Line Code Using Reinforcement Learning and Rollouts %@Amy McGovern,J. Eliot B. Moss %t1998 %cNIPS %f/NIPS/NIPS-1998-6177.pdf %*Bayesian Modeling of Facial Similarity %@Baback Moghaddam,Tony Jebara,Alex Pentland %t1998 %cNIPS %f/NIPS/NIPS-1998-6178.pdf %*Reinforcement Learning for Trading %@John E. Moody,Matthew Saffell %t1998 %cNIPS %f/NIPS/NIPS-1998-6179.pdf %*Graphical Models for Recognizing Human Interactions %@Nuria Oliver,Barbara Rosario,Alex Pentland %t1998 %cNIPS %f/NIPS/NIPS-1998-6180.pdf %*Independent Component Analysis of Intracellular Calcium Spike Data %@Klaus Prank,Julia Börger,Alexander von zur Mühlen,Georg Brabant,Christof Schöfl %t1998 %cNIPS %f/NIPS/NIPS-1998-6181.pdf %*Applications of Multi-Resolution Neural Networks to Mammography %@Clay Spence,Paul Sajda %t1998 %cNIPS %f/NIPS/NIPS-1998-6182.pdf %*Robot Docking Using Mixtures of Gaussians %@Matthew M. Williamson,Roderick Murray-Smith,Volker Hansen %t1998 %cNIPS %f/NIPS/NIPS-1998-6183.pdf %*Using Collective Intelligence to Route Internet Traffic %@David Wolpert,Kagan Tumer,Jeremy Frank %t1998 %cNIPS %f/NIPS/NIPS-1998-6184.pdf %*Robust, Efficient, Globally-Optimized Reinforcement Learning with the Parti-Game Algorithm %@Mohammad A. Al-Ansari,Ronald J. Williams %t1998 %cNIPS %f/NIPS/NIPS-1998-6185.pdf %*Gradient Descent for General Reinforcement Learning %@Leemon C. Baird III,Andrew W. Moore %t1998 %cNIPS %f/NIPS/NIPS-1998-6186.pdf %*Non-Linear PI Control Inspired by Biological Control Systems %@Lyndon J. Brown,Gregory E. Gonye,James S. Schwaber %t1998 %cNIPS %f/NIPS/NIPS-1998-6187.pdf %*Optimizing Admission Control while Ensuring Quality of Service in Multimedia Networks via Reinforcement Learning %@Timothy X. Brown,Hui Tong,Satinder P. Singh %t1998 %cNIPS %f/NIPS/NIPS-1998-6188.pdf %*Viewing Classifier Systems as Model Free Learning in POMDPs %@Akira Hayashi,Nobuo Suematsu %t1998 %cNIPS %f/NIPS/NIPS-1998-6189.pdf %*Finite-Sample Convergence Rates for Q-Learning and Indirect Algorithms %@Michael J. Kearns,Satinder P. Singh %t1998 %cNIPS %f/NIPS/NIPS-1998-6190.pdf %*Learning Instance-Independent Value Functions to Enhance Local Search %@Robert Moll,Andrew G. Barto,Theodore J. Perkins,Richard S. Sutton %t1998 %cNIPS %f/NIPS/NIPS-1998-6191.pdf %*Barycentric Interpolators for Continuous Space and Time Reinforcement Learning %@Rémi Munos,Andrew W. Moore %t1998 %cNIPS %f/NIPS/NIPS-1998-6192.pdf %*Risk Sensitive Reinforcement Learning %@Ralph Neuneier,Oliver Mihatsch %t1998 %cNIPS %f/NIPS/NIPS-1998-6193.pdf %*Coordinate Transformation Learning of Hand Position Feedback Controller by Using Change of Position Error Norm %@Eimei Oyama,Susumu Tachi %t1998 %cNIPS %f/NIPS/NIPS-1998-6194.pdf %*Reinforcement Learning Based on On-Line EM Algorithm %@Masa-aki Sato,Shin Ishii %t1998 %cNIPS %f/NIPS/NIPS-1998-6195.pdf %*A Reinforcement Learning Algorithm in Partially Observable Environments Using Short-Term Memory %@Nobuo Suematsu,Akira Hayashi %t1998 %cNIPS %f/NIPS/NIPS-1998-6196.pdf %*Improved Switching among Temporally Abstract Actions %@Richard S. Sutton,Satinder P. Singh,Doina Precup,Balaraman Ravindran %t1998 %cNIPS %f/NIPS/NIPS-1998-6197.pdf %*Experimental Results on Learning Stochastic Memoryless Policies for Partially Observable Markov Decision Processes %@John K. Williams,Satinder P. Singh %t1998 %cNIPS %f/NIPS/NIPS-1998-6198.pdf %*On Parallel versus Serial Processing: A Computational Study of Visual Search %@Eyal Cohen,Eytan Ruppin %t1997 %cNIPS %f/NIPS/NIPS-1997-6199.pdf %*Task and Spatial Frequency Effects on Face Specialization %@Matthew N. Dailey,Garrison W. Cottrell %t1997 %cNIPS %f/NIPS/NIPS-1997-6200.pdf %*Neural Basis of Object-Centered Representations %@Sophie Denève,Alexandre Pouget %t1997 %cNIPS %f/NIPS/NIPS-1997-6201.pdf %*Adaptation in Speech Motor Control %@John F. Houde,Michael I. Jordan %t1997 %cNIPS %f/NIPS/NIPS-1997-6202.pdf %*Learning Human-like Knowledge by Singular Value Decomposition: A Progress Report %@Thomas K. Landauer,Darrell Laham,Peter W. Foltz %t1997 %cNIPS %f/NIPS/NIPS-1997-6203.pdf %*Multi-modular Associative Memory %@Nir Levy,David Horn,Eytan Ruppin %t1997 %cNIPS %f/NIPS/NIPS-1997-6204.pdf %*Serial Order in Reading Aloud: Connectionist Models and Neighborhood Structure %@Jeanne C. Milostan,Garrison W. Cottrell %t1997 %cNIPS %f/NIPS/NIPS-1997-6205.pdf %*A Superadditive-Impairment Theory of Optic Aphasia %@Michael C. Mozer,Mark Sitton,Martha J. Farah %t1997 %cNIPS %f/NIPS/NIPS-1997-6206.pdf %*A Hippocampal Model of Recognition Memory %@Randall C. O'Reilly,Kenneth A. Norman,James L. McClelland %t1997 %cNIPS %f/NIPS/NIPS-1997-6207.pdf %*Recurrent Neural Networks Can Learn to Implement Symbol-Sensitive Counting %@Paul Rodriguez,Janet Wiles %t1997 %cNIPS %f/NIPS/NIPS-1997-6208.pdf %*Comparison of Human and Machine Word Recognition %@Markus Schenkel,Cyril Latimer,Marwan A. Jabri %t1997 %cNIPS %f/NIPS/NIPS-1997-6209.pdf %*Coding of Naturalistic Stimuli by Auditory Midbrain Neurons %@Hagai Attias,Christoph E. Schreiner %t1997 %cNIPS %f/NIPS/NIPS-1997-6210.pdf %*Refractoriness and Neural Precision %@Michael J. Berry II,Markus Meister %t1997 %cNIPS %f/NIPS/NIPS-1997-6211.pdf %*Statistical Models of Conditioning %@Peter Dayan,Theresa Long %t1997 %cNIPS %f/NIPS/NIPS-1997-6212.pdf %*Characterizing Neurons in the Primary Auditory Cortex of the Awake Primate Using Reverse Correlation %@R. Christopher DeCharms,Michael Merzenich %t1997 %cNIPS %f/NIPS/NIPS-1997-6213.pdf %*Using Helmholtz Machines to Analyze Multi-channel Neuronal Recordings %@Virginia R. de Sa,R. Christopher DeCharms,Michael Merzenich %t1997 %cNIPS %f/NIPS/NIPS-1997-6214.pdf %*Instabilities in Eye Movement Control: A Model of Periodic Alternating Nystagmus %@Ernst R. Dow,Thomas J. Anastasio %t1997 %cNIPS %f/NIPS/NIPS-1997-6215.pdf %*Hippocampal Model of Rat Spatial Abilities Using Temporal Difference Learning %@David J. Foster,Richard G. M. Morris,Peter Dayan %t1997 %cNIPS %f/NIPS/NIPS-1997-6216.pdf %*Computing with Action Potentials %@John J. Hopfield,Carlos D. Brody,Sam Roweis %t1997 %cNIPS %f/NIPS/NIPS-1997-6217.pdf %*A Model of Early Visual Processing %@Laurent Itti,Jochen Braun,Dale K. Lee,Christof Koch %t1997 %cNIPS %f/NIPS/NIPS-1997-6218.pdf %*Perturbative M-Sequences for Auditory Systems Identification %@Mark Kvale,Christoph E. Schreiner %t1997 %cNIPS %f/NIPS/NIPS-1997-6219.pdf %*Dynamic Stochastic Synapses as Computational Units %@Wolfgang Maass,Anthony M. Zador %t1997 %cNIPS %f/NIPS/NIPS-1997-6220.pdf %*Synaptic Transmission: An Information-Theoretic Perspective %@Amit Manwani,Christof Koch %t1997 %cNIPS %f/NIPS/NIPS-1997-6221.pdf %*Toward a Single-Cell Account for Binocular Disparity Tuning: An Energy Model May Be Hiding in Your Dendrites %@Bartlett W. Mel,Daniel L. Ruderman,Kevin A. Archie %t1997 %cNIPS %f/NIPS/NIPS-1997-6222.pdf %*Just One View: Invariances in Inferotemporal Cell Tuning %@Maximilian Riesenhuber,Tomaso Poggio %t1997 %cNIPS %f/NIPS/NIPS-1997-6223.pdf %*On the Separation of Signals from Neighboring Cells in Tetrode Recordings %@Maneesh Sahani,John S. Pezaris,Richard A. Andersen %t1997 %cNIPS %f/NIPS/NIPS-1997-6224.pdf %*Independent Component Analysis for Identification of Artifacts in Magnetoencephalographic Recordings %@Ricardo Vigário,Veikko Jousmäki,Matti Hämäläinen,Riitta Hari,Erkki Oja %t1997 %cNIPS %f/NIPS/NIPS-1997-6225.pdf %*Modeling Complex Cells in an Awake Macaque during Natural Image Viewing %@William E. Vinje,Jack L. Gallant %t1997 %cNIPS %f/NIPS/NIPS-1997-6226.pdf %*The Canonical Distortion Measure in Feature Space and 1-NN Classification %@Jonathan Baxter,Peter L. Bartlett %t1997 %cNIPS %f/NIPS/NIPS-1997-6227.pdf %*Multiple Threshold Neural Logic %@Vasken Bohossian,Jehoshua Bruck %t1997 %cNIPS %f/NIPS/NIPS-1997-6228.pdf %*Generalization in Decision Trees and DNF: Does Size Matter? %@Mostefa Golea,Peter L. Bartlett,Wee Sun Lee,Llew Mason %t1997 %cNIPS %f/NIPS/NIPS-1997-6229.pdf %*Boltzmann Machine Learning Using Mean Field Theory and Linear Response Correction %@Hilbert J. Kappen,Francisco de Borja Rodríguez Ortiz %t1997 %cNIPS %f/NIPS/NIPS-1997-6230.pdf %*Relative Loss Bounds for Multidimensional Regression Problems %@Jyrki Kivinen,Manfred K. Warmuth %t1997 %cNIPS %f/NIPS/NIPS-1997-6231.pdf %*Two Approaches to Optimal Annealing %@Todd K. Leen,Bernhard Schottky,David Saad %t1997 %cNIPS %f/NIPS/NIPS-1997-6232.pdf %*Analytical Study of the Interplay between Architecture and Predictability %@Avner Priel,Ido Kanter,David A. Kessler %t1997 %cNIPS %f/NIPS/NIPS-1997-6233.pdf %*Globally Optimal On-line Learning Rules %@Magnus Rattray,David Saad %t1997 %cNIPS %f/NIPS/NIPS-1997-6234.pdf %*Minimax and Hamiltonian Dynamics of Excitatory-Inhibitory Networks %@H. Sebastian Seung,Tom J. Richardson,J. C. Lagarias,John J. Hopfield %t1997 %cNIPS %f/NIPS/NIPS-1997-6235.pdf %*Data-Dependent Structural Risk Minimization for Perceptron Decision Trees %@John Shawe-Taylor,Nello Cristianini %t1997 %cNIPS %f/NIPS/NIPS-1997-6236.pdf %*From Regularization Operators to Support Vector Kernels %@Alex J. Smola,Bernhard Schölkopf %t1997 %cNIPS %f/NIPS/NIPS-1997-6237.pdf %*The Rectified Gaussian Distribution %@Nicholas D. Socci,Daniel D. Lee,H. Sebastian Seung %t1997 %cNIPS %f/NIPS/NIPS-1997-6238.pdf %*On-line Learning from Finite Training Sets in Nonlinear Networks %@Peter Sollich,David Barber %t1997 %cNIPS %f/NIPS/NIPS-1997-6239.pdf %*The Storage Capacity of a Fully-Connected Committee Machine %@Yuansheng Xiong,Chulan Kwon,Jong-Hoon Oh %t1997 %cNIPS %f/NIPS/NIPS-1997-6240.pdf %*The Efficiency and the Robustness of Natural Gradient Descent Learning Rule %@Howard Hua Yang,Shun-ichi Amari %t1997 %cNIPS %f/NIPS/NIPS-1997-6241.pdf %*Ensemble Learning for Multi-Layer Networks %@David Barber,Christopher M. Bishop %t1997 %cNIPS %f/NIPS/NIPS-1997-6242.pdf %*Radial Basis Functions: A Bayesian Treatment %@David Barber,Bernhard Schottky %t1997 %cNIPS %f/NIPS/NIPS-1997-6243.pdf %*Shared Context Probabilistic Transducers %@Yoshua Bengio,Samy Bengio,Jean-Franc Isabelle,Yoram Singer %t1997 %cNIPS %f/NIPS/NIPS-1997-6244.pdf %*Approximating Posterior Distributions in Belief Networks Using Mixtures %@Christopher M. Bishop,Neil D. Lawrence,Tommi Jaakkola,Michael I. Jordan %t1997 %cNIPS %f/NIPS/NIPS-1997-6245.pdf %*Receptive Field Formation in Natural Scene Environments: Comparison of Single Cell Learning Rules %@Brian S. Blais,Nathan Intrator,Harel Z. Shouval,Leon N. Cooper %t1997 %cNIPS %f/NIPS/NIPS-1997-6246.pdf %*An Annealed Self-Organizing Map for Source Channel Coding %@Matthias Burger,Thore Graepel,Klaus Obermayer %t1997 %cNIPS %f/NIPS/NIPS-1997-6247.pdf %*Incorporating Test Inputs into Learning %@Zehra Cataltepe,Malik Magdon-Ismail %t1997 %cNIPS %f/NIPS/NIPS-1997-6248.pdf %*On Efficient Heuristic Ranking of Hypotheses %@Steve A. Chien,Andre Stechert,Darren Mutz %t1997 %cNIPS %f/NIPS/NIPS-1997-6249.pdf %*Learning to Order Things %@William W. Cohen,Robert E. Schapire,Yoram Singer %t1997 %cNIPS %f/NIPS/NIPS-1997-6250.pdf %*Regularisation in Sequential Learning Algorithms %@João F. G. de Freitas,Mahesan Niranjan,Andrew H. Gee %t1997 %cNIPS %f/NIPS/NIPS-1997-6251.pdf %*Agnostic Classification of Markovian Sequences %@Ran El-Yaniv,Shai Fine,Naftali Tishby %t1997 %cNIPS %f/NIPS/NIPS-1997-6252.pdf %*Ensemble and Modular Approaches for Face Detection: A Comparison %@Raphaël Feraud,Olivier Bernier %t1997 %cNIPS %f/NIPS/NIPS-1997-6253.pdf %*A Revolution: Belief Propagation in Graphs with Cycles %@Brendan J. Frey,David J. C. MacKay %t1997 %cNIPS %f/NIPS/NIPS-1997-6254.pdf %*Hierarchical Non-linear Factor Analysis and Topographic Maps %@Zoubin Ghahramani,Geoffrey E. Hinton %t1997 %cNIPS %f/NIPS/NIPS-1997-6255.pdf %*Regression with Input-dependent Noise: A Gaussian Process Treatment %@Paul W. Goldberg,Christopher K. I. Williams,Christopher M. Bishop %t1997 %cNIPS %f/NIPS/NIPS-1997-6256.pdf %*Linear Concepts and Hidden Variables: An Empirical Study %@Adam J. Grove,Dan Roth %t1997 %cNIPS %f/NIPS/NIPS-1997-6257.pdf %*Classification by Pairwise Coupling %@Trevor Hastie,Robert Tibshirani %t1997 %cNIPS %f/NIPS/NIPS-1997-6258.pdf %*Unsupervised On-line Learning of Decision Trees for Hierarchical Data Analysis %@Marcus Held,Joachim M. Buhmann %t1997 %cNIPS %f/NIPS/NIPS-1997-6259.pdf %*Nonlinear Markov Networks for Continuous Variables %@Reimar Hofmann,Volker Tresp %t1997 %cNIPS %f/NIPS/NIPS-1997-6260.pdf %*Active Data Clustering %@Thomas Hofmann,Joachim M. Buhmann %t1997 %cNIPS %f/NIPS/NIPS-1997-6261.pdf %*Function Approximation with the Sweeping Hinge Algorithm %@Don R. Hush,Fernando Lozano,Bill G. Horne %t1997 %cNIPS %f/NIPS/NIPS-1997-6262.pdf %*The Error Coding and Substitution PaCTs %@Gareth James,Trevor Hastie %t1997 %cNIPS %f/NIPS/NIPS-1997-6263.pdf %*S-Map: A Network with a Simple Self-Organization Algorithm for Generative Topographic Mappings %@Kimmo Kiviluoto,Erkki Oja %t1997 %cNIPS %f/NIPS/NIPS-1997-6264.pdf %*Learning Nonlinear Overcomplete Representations for Efficient Coding %@Michael S. Lewicki,Terrence J. Sejnowski %t1997 %cNIPS %f/NIPS/NIPS-1997-6265.pdf %*A Framework for Multiple-Instance Learning %@Oded Maron,Tomás Lozano-Pérez %t1997 %cNIPS %f/NIPS/NIPS-1997-6266.pdf %*Estimating Dependency Structure as a Hidden Variable %@Marina Meila,Michael I. Jordan %t1997 %cNIPS %f/NIPS/NIPS-1997-6267.pdf %*Learning Path Distributions Using Nonequilibrium Diffusion Networks %@Paul Mineiro,Javier R. Movellan,Ruth J. Williams %t1997 %cNIPS %f/NIPS/NIPS-1997-6268.pdf %*Learning Generative Models with the Up Propagation Algorithm %@Jong-Hoon Oh,H. Sebastian Seung %t1997 %cNIPS %f/NIPS/NIPS-1997-6269.pdf %*Local Dimensionality Reduction %@Stefan Schaal,Sethu Vijayakumar,Christopher G. Atkeson %t1997 %cNIPS %f/NIPS/NIPS-1997-6270.pdf %*Prior Knowledge in Support Vector Kernels %@Bernhard Schölkopf,Patrice Simard,Alex J. Smola,Vladimir Vapnik %t1997 %cNIPS %f/NIPS/NIPS-1997-6271.pdf %*Training Methods for Adaptive Boosting of Neural Networks %@Holger Schwenk,Yoshua Bengio %t1997 %cNIPS %f/NIPS/NIPS-1997-6272.pdf %*Stacked Density Estimation %@Padhraic Smyth,David Wolpert %t1997 %cNIPS %f/NIPS/NIPS-1997-6273.pdf %*Bidirectional Retrieval from Associative Memory %@Friedrich T. Sommer,Günther Palm %t1997 %cNIPS %f/NIPS/NIPS-1997-6274.pdf %*Graph Matching with Hierarchical Discrete Relaxation %@Richard C. Wilson,Edwin R. Hancock %t1997 %cNIPS %f/NIPS/NIPS-1997-6275.pdf %*Analog VLSI Model of Intersegmental Coordination with Nearest-Neighbor Coupling %@Girish N. Patel,Jeremy H. Holleman,Stephen P. DeWeerth %t1997 %cNIPS %f/NIPS/NIPS-1997-6276.pdf %*An Analog VLSI Neural Network for Phase-based Machine Vision %@Bertram Emil Shi,Kwok Fai Hui %t1997 %cNIPS %f/NIPS/NIPS-1997-6277.pdf %*Analysis of Drifting Dynamics with Neural Network Hidden Markov Models %@Jens Kohlmorgen,Klaus-Robert Müller,Klaus Pawelzik %t1997 %cNIPS %f/NIPS/NIPS-1997-6278.pdf %*Bayesian Robustification for Audio Visual Fusion %@Javier R. Movellan,Paul Mineiro %t1997 %cNIPS %f/NIPS/NIPS-1997-6279.pdf %*Modeling Acoustic Correlations by Factor Analysis %@Lawrence K. Saul,Mazin G. Rahim %t1997 %cNIPS %f/NIPS/NIPS-1997-6280.pdf %*Hybrid NN/HMM-Based Speech Recognition with a Discriminant Neural Feature Extraction %@Daniel Willett,Gerhard Rigoll %t1997 %cNIPS %f/NIPS/NIPS-1997-6281.pdf %*A Non-Parametric Multi-Scale Statistical Model for Natural Images %@Jeremy S. De Bonet,Paul A. Viola %t1997 %cNIPS %f/NIPS/NIPS-1997-6282.pdf %*Recovering Perspective Pose with a Dual Step EM Algorithm %@Andrew D. J. Cross,Edwin R. Hancock %t1997 %cNIPS %f/NIPS/NIPS-1997-6283.pdf %*Bayesian Model of Surface Perception %@William T. Freeman,Paul A. Viola %t1997 %cNIPS %f/NIPS/NIPS-1997-6284.pdf %*Features as Sufficient Statistics %@Davi Geiger,Archisman Rudra,Laurance T. Maloney %t1997 %cNIPS %f/NIPS/NIPS-1997-6285.pdf %*Detection of First and Second Order Motion %@Alexander Grunewald,Heiko Neumann %t1997 %cNIPS %f/NIPS/NIPS-1997-6286.pdf %*2D Observers for Human 3D Object Recognition? %@Zili Liu,Daniel Kersten %t1997 %cNIPS %f/NIPS/NIPS-1997-6287.pdf %*Self-similarity Properties of Natural Images %@Antonio Turiel,Germán Mato,Néstor Parga,Jean-Pierre Nadal %t1997 %cNIPS %f/NIPS/NIPS-1997-6288.pdf %*Multiresolution Tangent Distance for Affine-invariant Classification %@Nuno Vasconcelos,Andrew Lippman %t1997 %cNIPS %f/NIPS/NIPS-1997-6289.pdf %*Structure Driven Image Database Retrieval %@Jeremy S. De Bonet,Paul A. Viola %t1997 %cNIPS %f/NIPS/NIPS-1997-6290.pdf %*A General Purpose Image Processing Chip: Orientation Detection %@Ralph Etienne-Cummings,Donghui Cai %t1997 %cNIPS %f/NIPS/NIPS-1997-6291.pdf %*An Analog VLSI Model of the Fly Elementary Motion Detector %@Reid R. Harrison,Christof Koch %t1997 %cNIPS %f/NIPS/NIPS-1997-6292.pdf %*Extended ICA Removes Artifacts from Electroencephalographic Recordings %@Tzyy-Ping Jung,Colin Humphries,Te-Won Lee,Scott Makeig,Martin J. McKeown,Vicente Iragui,Terrence J. Sejnowski %t1997 %cNIPS %f/NIPS/NIPS-1997-6293.pdf %*A Generic Approach for Identification of Event Related Brain Potentials via a Competitive Neural Network Structure %@Daniel H. Lange,Hava T. Siegelmann,Hillel Pratt,Gideon F. Inbar %t1997 %cNIPS %f/NIPS/NIPS-1997-6294.pdf %*A Neural Network Based Head Tracking System %@Daniel D. Lee,H. S. Seung %t1997 %cNIPS %f/NIPS/NIPS-1997-6295.pdf %*Wavelet Models for Video Time-Series %@Sheng Ma,Chuanyi Ji %t1997 %cNIPS %f/NIPS/NIPS-1997-6296.pdf %*Reinforcement Learning for Call Admission Control and Routing in Integrated Service Networks %@Peter Marbach,Oliver Mihatsch,Miriam Schulte,John N. Tsitsiklis %t1997 %cNIPS %f/NIPS/NIPS-1997-6297.pdf %*Learning to Schedule Straight-Line Code %@J. Eliot B. Moss,Paul E. Utgoff,John Cavazos,Doina Precup,Darko Stefanovic,Carla E. Brodley,David Scheeff %t1997 %cNIPS %f/NIPS/NIPS-1997-6298.pdf %*Intrusion Detection with Neural Networks %@Jake Ryan,Meng-Jang Lin,Risto Miikkulainen %t1997 %cNIPS %f/NIPS/NIPS-1997-6299.pdf %*Incorporating Contextual Information in White Blood Cell Identification %@Xubo B. Song,Yaser S. Abu-Mostafa,Joseph Sill,Harvey Kasdan %t1997 %cNIPS %f/NIPS/NIPS-1997-6300.pdf %*Bach in a Box - Real-Time Harmony %@Randall R. Spangler,Rodney M. Goodman,Jim Hawkins %t1997 %cNIPS %f/NIPS/NIPS-1997-6301.pdf %*Experiences with Bayesian Learning in a Real World Application %@Peter Sykacek,Georg Dorffner,Peter Rappelsberger,Josef Zeitlhofer %t1997 %cNIPS %f/NIPS/NIPS-1997-6302.pdf %*A Solution for Missing Data in Recurrent Neural Networks with an Application to Blood Glucose Prediction %@Volker Tresp,Thomas Briegel %t1997 %cNIPS %f/NIPS/NIPS-1997-6303.pdf %*Use of a Multi-Layer Perceptron to Predict Malignancy in Ovarian Tumors %@Herman Verrelst,Yves Moreau,Joos Vandewalle,Dirk Timmerman %t1997 %cNIPS %f/NIPS/NIPS-1997-6304.pdf %*The Observer-Observation Dilemma in Neuro-Forecasting %@Hans-Georg Zimmermann,Ralph Neuneier %t1997 %cNIPS %f/NIPS/NIPS-1997-6305.pdf %*Generalized Prioritized Sweeping %@David Andre,Nir Friedman,Ronald Parr %t1997 %cNIPS %f/NIPS/NIPS-1997-6306.pdf %*Automated Aircraft Recovery via Reinforcement Learning: Initial Experiments %@Jeffrey F. Monaco,David G. Ward,Andrew G. Barto %t1997 %cNIPS %f/NIPS/NIPS-1997-6307.pdf %*Reinforcement Learning for Continuous Stochastic Control Problems %@Rémi Munos,Paul Bourgine %t1997 %cNIPS %f/NIPS/NIPS-1997-6308.pdf %*Reinforcement Learning with Hierarchies of Machines %@Ronald Parr,Stuart J. Russell %t1997 %cNIPS %f/NIPS/NIPS-1997-6309.pdf %*Multi-time Models for Temporally Abstract Planning %@Doina Precup,Richard S. Sutton %t1997 %cNIPS %f/NIPS/NIPS-1997-6310.pdf %*How to Dynamically Merge Markov Decision Processes %@Satinder P. Singh,David Cohn %t1997 %cNIPS %f/NIPS/NIPS-1997-6311.pdf %*Hybrid Reinforcement Learning and Its Application to Biped Robot Control %@Satoshi Yamada,Akira Watanabe,Michio Nakashima %t1997 %cNIPS %f/NIPS/NIPS-1997-6312.pdf %*Text-Based Information Retrieval Using Exponentiated Gradient Descent %@Ron Papka,James P. Callan,Andrew G. Barto %t1996 %cNIPS %f/NIPS/NIPS-1996-6313.pdf %*Why did TD-Gammon Work? %@Jordan B. Pollack,Alan D. Blair %t1996 %cNIPS %f/NIPS/NIPS-1996-6314.pdf %*Neural Models for Part-Whole Hierarchies %@Maximilian Riesenhuber,Peter Dayan %t1996 %cNIPS %f/NIPS/NIPS-1996-6315.pdf %*Temporal Low-Order Statistics of Natural Sounds %@Hagai Attias,Christoph E. Schreiner %t1996 %cNIPS %f/NIPS/NIPS-1996-6316.pdf %*Reconstructing Stimulus Velocity from Neuronal Responses in Area MT %@Wyeth Bair,James R. Cavanaugh,J. Anthony Movshon %t1996 %cNIPS %f/NIPS/NIPS-1996-6317.pdf %*3D Object Recognition: A Model of View-Tuned Neurons %@Emanuela Bricolo,Tomaso Poggio,Nikos K. Logothetis %t1996 %cNIPS %f/NIPS/NIPS-1996-6318.pdf %*Neural Network Models of Chemotaxis in the Nematode Caenorhabditis Elegans %@Thomas C. Ferrée,Ben A. Marcotte,Shawn R. Lockery %t1996 %cNIPS %f/NIPS/NIPS-1996-6319.pdf %*Extraction of Temporal Features in the Electrosensory System of Weakly Electric Fish %@Fabrizio Gabbiani,Walter Metzner,Ralf Wessel,Christof Koch %t1996 %cNIPS %f/NIPS/NIPS-1996-6320.pdf %*Learning Exact Patterns of Quasi-synchronization among Spiking Neurons from Data on Multi-unit Recordings %@Laura Martignon,Kathryn B. Laskey,Gustavo Deco,Eilon Vaadia %t1996 %cNIPS %f/NIPS/NIPS-1996-6321.pdf %*Complex-Cell Responses Derived from Center-Surround Inputs: The Surprising Power of Intradendritic Computation %@Bartlett W. Mel,Daniel L. Ruderman,Kevin A. Archie %t1996 %cNIPS %f/NIPS/NIPS-1996-6322.pdf %*Orientation Contrast Sensitivity from Long-range Interactions in Visual Cortex %@Klaus Pawelzik,Udo Ernst,Fred Wolf,Theo Geisel %t1996 %cNIPS %f/NIPS/NIPS-1996-6323.pdf %*Statistically Efficient Estimations Using Cortical Lateral Connections %@Alexandre Pouget,Kechen Zhang %t1996 %cNIPS %f/NIPS/NIPS-1996-6324.pdf %*An Architectural Mechanism for Direction-tuned Cortical Simple Cells: The Role of Mutual Inhibition %@Silvio P. Sabatini,Fabio Solari,Giacomo M. Bisio %t1996 %cNIPS %f/NIPS/NIPS-1996-6325.pdf %*Cholinergic Modulation Preserves Spike Timing Under Physiologically Realistic Fluctuating Input %@Akaysha C. Tang,Andreas M. Bartels,Terrence J. Sejnowski %t1996 %cNIPS %f/NIPS/NIPS-1996-6326.pdf %*A Model of Recurrent Interactions in Primary Visual Cortex %@Emanuel Todorov,Athanassios Siapas,David Somers %t1996 %cNIPS %f/NIPS/NIPS-1996-6327.pdf %*Dynamics of Training %@Siegfried Bös,Manfred Opper %t1996 %cNIPS %f/NIPS/NIPS-1996-6328.pdf %*Multilayer Neural Networks: One or Two Hidden Layers? %@Graham Brightwell,Claire Kenyon,Hélène Paugam-Moisy %t1996 %cNIPS %f/NIPS/NIPS-1996-6329.pdf %*Support Vector Regression Machines %@Harris Drucker,Christopher J. C. Burges,Linda Kaufman,Alex J. Smola,Vladimir Vapnik %t1996 %cNIPS %f/NIPS/NIPS-1996-6330.pdf %*Size of Multilayer Networks for Exact Learning: Analytic Approach %@André Elisseeff,Hélène Paugam-Moisy %t1996 %cNIPS %f/NIPS/NIPS-1996-6331.pdf %*The Effect of Correlated Input Data on the Dynamics of Learning %@Søren Halkjær,Ole Winther %t1996 %cNIPS %f/NIPS/NIPS-1996-6332.pdf %*Statistical Mechanics of the Mixture of Experts %@Kukjin Kang,Jong-Hoon Oh %t1996 %cNIPS %f/NIPS/NIPS-1996-6333.pdf %*MLP Can Provably Generalize Much Better than VC-bounds Indicate %@Adam Kowalczyk,Herman L. Ferrá %t1996 %cNIPS %f/NIPS/NIPS-1996-6334.pdf %*Radial Basis Function Networks and Complexity Regularization in Function Learning %@Adam Krzyzak,Tamás Linder %t1996 %cNIPS %f/NIPS/NIPS-1996-6335.pdf %*An Apobayesian Relative of Winnow %@Nick Littlestone,Chris Mesterharm %t1996 %cNIPS %f/NIPS/NIPS-1996-6336.pdf %*On the Effect of Analog Noise in Discrete-Time Analog Computations %@Wolfgang Maass,Pekka Orponen %t1996 %cNIPS %f/NIPS/NIPS-1996-6337.pdf %*A Mean Field Algorithm for Bayes Learning in Large Feed-forward Neural Networks %@Manfred Opper,Ole Winther %t1996 %cNIPS %f/NIPS/NIPS-1996-6338.pdf %*Are Hopfield Networks Faster than Conventional Computers? %@Ian Parberry,Hung-Li Tseng %t1996 %cNIPS %f/NIPS/NIPS-1996-6339.pdf %*Hebb Learning of Features based on their Information Content %@Ferdinand Peper,Hideki Noda %t1996 %cNIPS %f/NIPS/NIPS-1996-6340.pdf %*The Generalisation Cost of RAMnets %@Richard Rohwer,Michal Morciniec %t1996 %cNIPS %f/NIPS/NIPS-1996-6341.pdf %*Learning with Noise and Regularizers in Multilayer Neural Networks %@David Saad,Sara A. Solla %t1996 %cNIPS %f/NIPS/NIPS-1996-6342.pdf %*A Variational Principle for Model-based Morphing %@Lawrence K. Saul,Michael I. Jordan %t1996 %cNIPS %f/NIPS/NIPS-1996-6343.pdf %*Online Learning from Finite Training Sets: An Analytical Case Study %@Peter Sollich,David Barber %t1996 %cNIPS %f/NIPS/NIPS-1996-6344.pdf %*Support Vector Method for Function Approximation, Regression Estimation and Signal Processing %@Vladimir Vapnik,Steven E. Golowich,Alex J. Smola %t1996 %cNIPS %f/NIPS/NIPS-1996-6345.pdf %*The Learning Dynamcis of a Universal Approximator %@Ansgar H. L. West,David Saad,Ian T. Nabney %t1996 %cNIPS %f/NIPS/NIPS-1996-6346.pdf %*Time Series Prediction using Mixtures of Experts %@Assaf J. Zeevi,Ron Meir,Robert J. Adler %t1996 %cNIPS %f/NIPS/NIPS-1996-6347.pdf %*Bayesian Model Comparison by Monte Carlo Chaining %@David Barber,Christopher M. Bishop %t1996 %cNIPS %f/NIPS/NIPS-1996-6348.pdf %*Gaussian Processes for Bayesian Classification via Hybrid Monte Carlo %@David Barber,Christopher K. I. Williams %t1996 %cNIPS %f/NIPS/NIPS-1996-6349.pdf %*Regression with Input-Dependent Noise: A Bayesian Treatment %@Christopher M. Bishop,Cazhaow S. Quazaz %t1996 %cNIPS %f/NIPS/NIPS-1996-6350.pdf %*GTM: A Principled Alternative to the Self-Organizing Map %@Christopher M. Bishop,Markus Svensén,Christopher K. I. Williams %t1996 %cNIPS %f/NIPS/NIPS-1996-6351.pdf %*The CONDENSATION Algorithm - Conditional Density Propagation and Applications to Visual Tracking %@Andrew Blake,Michael Isard %t1996 %cNIPS %f/NIPS/NIPS-1996-6352.pdf %*Clustering via Concave Minimization %@Paul S. Bradley,Olvi L. Mangasarian,W. Nick Street %t1996 %cNIPS %f/NIPS/NIPS-1996-6353.pdf %*Improving the Accuracy and Speed of Support Vector Machines %@Christopher J. C. Burges,Bernhard Schölkopf %t1996 %cNIPS %f/NIPS/NIPS-1996-6354.pdf %*Promoting Poor Features to Supervisors: Some Inputs Work Better as Outputs %@Rich Caruana,Virginia R. de Sa %t1996 %cNIPS %f/NIPS/NIPS-1996-6355.pdf %*Self-Organizing and Adaptive Algorithms for Generalized Eigen-Decomposition %@Chanchal Chatterjee,Vwani P. Roychowdhury %t1996 %cNIPS %f/NIPS/NIPS-1996-6356.pdf %*Representation and Induction of Finite State Machines using Time-Delay Neural Networks %@Daniel S. Clouse,C. Lee Giles,Bill G. Horne,Garrison W. Cottrell %t1996 %cNIPS %f/NIPS/NIPS-1996-6357.pdf %*488 Solutions to the XOR Problem %@Frans Coetzee,Virginia L. Stonick %t1996 %cNIPS %f/NIPS/NIPS-1996-6358.pdf %*MIMIC: Finding Optima by Estimating Probability Densities %@Jeremy S. De Bonet,Charles Lee Isbell Jr.,Paul A. Viola %t1996 %cNIPS %f/NIPS/NIPS-1996-6359.pdf %*On a Modification to the Mean Field EM Algorithm in Factorial Learning %@A. P. Dunmur,D. M. Titterington %t1996 %cNIPS %f/NIPS/NIPS-1996-6360.pdf %*Softening Discrete Relaxation %@Andrew M. Finch,Richard C. Wilson,Edwin R. Hancock %t1996 %cNIPS %f/NIPS/NIPS-1996-6361.pdf %*Adaptively Growing Hierarchical Mixtures of Experts %@Jürgen Fritsch,Michael Finke,Alex Waibel %t1996 %cNIPS %f/NIPS/NIPS-1996-6362.pdf %*LSTM can Solve Hard Long Time Lag Problems %@Sepp Hochreiter,Juergen Schmidhuber %t1996 %cNIPS %f/NIPS/NIPS-1996-6363.pdf %*One-unit Learning Rules for Independent Component Analysis %@Aapo Hyvärinen,Erkki Oja %t1996 %cNIPS %f/NIPS/NIPS-1996-6364.pdf %*Recursive Algorithms for Approximating Probabilities in Graphical Models %@Tommi Jaakkola,Michael I. Jordan %t1996 %cNIPS %f/NIPS/NIPS-1996-6365.pdf %*Combinations of Weak Classifiers %@Chuanyi Ji,Sheng Ma %t1996 %cNIPS %f/NIPS/NIPS-1996-6366.pdf %*Hidden Markov Decision Trees %@Michael I. Jordan,Zoubin Ghahramani,Lawrence K. Saul %t1996 %cNIPS %f/NIPS/NIPS-1996-6367.pdf %*Unsupervised Learning by Convex and Conic Coding %@Daniel D. Lee,H. Sebastian Seung %t1996 %cNIPS %f/NIPS/NIPS-1996-6368.pdf %*ARC-LH: A New Adaptive Resampling Algorithm for Improving ANN Classifiers %@Friedrich Leisch,Kurt Hornik %t1996 %cNIPS %f/NIPS/NIPS-1996-6369.pdf %*Bayesian Unsupervised Learning of Higher Order Structure %@Michael S. Lewicki,Terrence J. Sejnowski %t1996 %cNIPS %f/NIPS/NIPS-1996-6370.pdf %*Source Separation and Density Estimation by Faithful Equivariant SOM %@Juan K. Lin,Jack D. Cowan,David G. Grier %t1996 %cNIPS %f/NIPS/NIPS-1996-6371.pdf %*NeuroScale: Novel Topographic Feature Extraction using RBF Networks %@David Lowe,Michael E. Tipping %t1996 %cNIPS %f/NIPS/NIPS-1996-6372.pdf %*Triangulation by Continuous Embedding %@Marina Meila,Michael I. Jordan %t1996 %cNIPS %f/NIPS/NIPS-1996-6373.pdf %*Combining Neural Network Regression Estimates with Regularized Linear Weights %@Christopher J. Merz,Michael J. Pazzani %t1996 %cNIPS %f/NIPS/NIPS-1996-6374.pdf %*A Mixture of Experts Classifier with Learning Based on Both Labelled and Unlabelled Data %@David J. Miller,Hasan S. Uyar %t1996 %cNIPS %f/NIPS/NIPS-1996-6375.pdf %*Learning Bayesian Belief Networks with Neural Network Estimators %@Stefano Monti,Gregory F. Cooper %t1996 %cNIPS %f/NIPS/NIPS-1996-6376.pdf %*Smoothing Regularizers for Projective Basis Function Networks %@John E. Moody,Thorsteinn S. Rögnvaldsson %t1996 %cNIPS %f/NIPS/NIPS-1996-6377.pdf %*Competition Among Networks Improves Committee Performance %@Paul W. Munro,Bambang Parmanto %t1996 %cNIPS %f/NIPS/NIPS-1996-6378.pdf %*Adaptive On-line Learning in Changing Environments %@Noboru Murata,Klaus-Robert Müller,Andreas Ziehe,Shun-ichi Amari %t1996 %cNIPS %f/NIPS/NIPS-1996-6379.pdf %*Using Curvature Information for Fast Stochastic Search %@Genevieve B. Orr,Todd K. Leen %t1996 %cNIPS %f/NIPS/NIPS-1996-6380.pdf %*Maximum Likelihood Blind Source Separation: A Context-Sensitive Generalization of ICA %@Barak A. Pearlmutter,Lucas C. Parra %t1996 %cNIPS %f/NIPS/NIPS-1996-6381.pdf %*A Convergence Proof for the Softassign Quadratic Assignment Algorithm %@Anand Rangarajan,Alan L. Yuille,Steven Gold,Eric Mjolsness %t1996 %cNIPS %f/NIPS/NIPS-1996-6382.pdf %*Second-order Learning Algorithm with Squared Penalty Term %@Kazumi Saito,Ryohei Nakano %t1996 %cNIPS %f/NIPS/NIPS-1996-6383.pdf %*Monotonicity Hints %@Joseph Sill,Yaser S. Abu-Mostafa %t1996 %cNIPS %f/NIPS/NIPS-1996-6384.pdf %*Training Algorithms for Hidden Markov Models using Entropy Based Distance Functions %@Yoram Singer,Manfred K. Warmuth %t1996 %cNIPS %f/NIPS/NIPS-1996-6385.pdf %*Fast Network Pruning and Feature Extraction by using the Unit-OBS Algorithm %@Achim Stahlberger,Martin Riedmiller %t1996 %cNIPS %f/NIPS/NIPS-1996-6386.pdf %*Separating Style and Content %@Joshua B. Tenenbaum,William T. Freeman %t1996 %cNIPS %f/NIPS/NIPS-1996-6387.pdf %*Early Brain Damage %@Volker Tresp,Ralph Neuneier,Hans-Georg Zimmermann %t1996 %cNIPS %f/NIPS/NIPS-1996-6388.pdf %*Probabilistic Interpretation of Population Codes %@Richard S. Zemel,Peter Dayan,Alexandre Pouget %t1996 %cNIPS %f/NIPS/NIPS-1996-6389.pdf %*VLSI Implementation of Cortical Visual Motion Detection Using an Analog Neural Computer %@Ralph Etienne-Cummings,Jan Van der Spiegel,Naomi Takahashi,Alyssa Apsel,Paul Mueller %t1996 %cNIPS %f/NIPS/NIPS-1996-6390.pdf %*A Spike Based Learning Neuron in Analog VLSI %@Philipp Häfliger,Misha Mahowald,Lloyd Watts %t1996 %cNIPS %f/NIPS/NIPS-1996-6391.pdf %*An Analog Implementation of the Constant Average Statistics Constraint For Sensor Calibration %@John G. Harris,Yu-Ming Chiang %t1996 %cNIPS %f/NIPS/NIPS-1996-6392.pdf %*Analog VLSI Circuits for Attention-Based, Visual Tracking %@Timothy K. Horiuchi,Tonia G. Morris,Christof Koch,Stephen P. DeWeerth %t1996 %cNIPS %f/NIPS/NIPS-1996-6393.pdf %*Dynamically Adaptable CMOS Winner-Take-All Neural Network %@Kunihiko Iizuka,Masayuki Miyamoto,Hirofumi Matsui %t1996 %cNIPS %f/NIPS/NIPS-1996-6394.pdf %*An Adaptive WTA using Floating Gate Technology %@W. Fritz Kruger,Paul E. Hasler,Bradley A. Minch,Christof Koch %t1996 %cNIPS %f/NIPS/NIPS-1996-6395.pdf %*A Micropower Analog VLSI HMM State Decoder for Wordspotting %@John Lazzaro,John Wawrzynek,Richard P. Lippmann %t1996 %cNIPS %f/NIPS/NIPS-1996-6396.pdf %*Bangs, Clicks, Snaps, Thuds and Whacks: An Architecture for Acoustic Transient Processing %@Fernando J. Pineda,Gert Cauwenberghs,R. Timothy Edwards %t1996 %cNIPS %f/NIPS/NIPS-1996-6397.pdf %*A Silicon Model of Amplitude Modulation Detection in the Auditory Brainstem %@André van Schaik,Eric Fragnière,Eric A. Vittoz %t1996 %cNIPS %f/NIPS/NIPS-1996-6398.pdf %*Dynamic Features for Visual Speechreading: A Systematic Comparison %@Michael S. Gray,Javier R. Movellan,Terrence J. Sejnowski %t1996 %cNIPS %f/NIPS/NIPS-1996-6399.pdf %*Blind Separation of Delayed and Convolved Sources %@Te-Won Lee,Anthony J. Bell,Russell H. Lambert %t1996 %cNIPS %f/NIPS/NIPS-1996-6400.pdf %*A Constructive RBF Network for Writer Adaptation %@John C. Platt,Nada Matic %t1996 %cNIPS %f/NIPS/NIPS-1996-6401.pdf %*A New Approach to Hybrid HMM/ANN Speech Recognition using Mutual Information Neural Networks %@Gerhard Rigoll,Christoph Neukirchen %t1996 %cNIPS %f/NIPS/NIPS-1996-6402.pdf %*A Constructive Learning Algorithm for Discriminant Tangent Models %@Diego Sona,Alessandro Sperduti,Antonina Starita %t1996 %cNIPS %f/NIPS/NIPS-1996-6403.pdf %*Dual Kalman Filtering Methods for Nonlinear Prediction, Smoothing and Estimation %@Eric A. Wan,Alex T. Nelson %t1996 %cNIPS %f/NIPS/NIPS-1996-6404.pdf %*Ensemble Methods for Phoneme Classification %@Steve R. Waterhouse,Gary Cook %t1996 %cNIPS %f/NIPS/NIPS-1996-6405.pdf %*Effective Training of a Neural Network Character Classifier for Word Recognition %@Larry S. Yaeger,Richard F. Lyon,Brandyn J. Webb %t1996 %cNIPS %f/NIPS/NIPS-1996-6406.pdf %*Viewpoint Invariant Face Recognition using Independent Component Analysis and Attractor Networks %@Marian Stewart Bartlett,Terrence J. Sejnowski %t1996 %cNIPS %f/NIPS/NIPS-1996-6407.pdf %*Edges are the 'Independent Components' of Natural Scenes. %@Anthony J. Bell,Terrence J. Sejnowski %t1996 %cNIPS %f/NIPS/NIPS-1996-6408.pdf %*Compositionality, MDL Priors, and Object Recognition %@Elie Bienenstock,Stuart Geman,Daniel Potter %t1996 %cNIPS %f/NIPS/NIPS-1996-6409.pdf %*Learning Appearance Based Models: Mixtures of Second Moment Experts %@Christoph Bregler,Jitendra Malik %t1996 %cNIPS %f/NIPS/NIPS-1996-6410.pdf %*Spatial Decorrelation in Orientation Tuned Cortical Cells %@Alexander Dimitrov,Jack D. Cowan %t1996 %cNIPS %f/NIPS/NIPS-1996-6411.pdf %*Selective Integration: A Model for Disparity Estimation %@Michael S. Gray,Alexandre Pouget,Richard S. Zemel,Steven J. Nowlan,Terrence J. Sejnowski %t1996 %cNIPS %f/NIPS/NIPS-1996-6412.pdf %*ARTEX: A Self-organizing Architecture for Classifying Image Regions %@Stephen Grossberg,James R. Williamson %t1996 %cNIPS %f/NIPS/NIPS-1996-6413.pdf %*Contour Organisation with the EM Algorithm %@José A. F. Leite,Edwin R. Hancock %t1996 %cNIPS %f/NIPS/NIPS-1996-6414.pdf %*Visual Cortex Circuitry and Orientation Tuning %@Trevor Mundel,Alexander Dimitrov,Jack D. Cowan %t1996 %cNIPS %f/NIPS/NIPS-1996-6415.pdf %*Representing Face Images for Emotion Classification %@Curtis Padgett,Garrison W. Cottrell %t1996 %cNIPS %f/NIPS/NIPS-1996-6416.pdf %*Rapid Visual Processing using Spike Asynchrony %@Simon J. Thorpe,Jacques Gautrais %t1996 %cNIPS %f/NIPS/NIPS-1996-6417.pdf %*Salient Contour Extraction by Temporal Binding in a Cortically-based Network %@Shih-Cheng Yen,Leif H. Finkel %t1996 %cNIPS %f/NIPS/NIPS-1996-6418.pdf %*An Orientation Selective Neural Network for Pattern Identification in Particle Detectors %@Halina Abramowicz,David Horn,Ury Naftaly,Carmit Sahar-Pikielny %t1996 %cNIPS %f/NIPS/NIPS-1996-6419.pdf %*Predicting Lifetimes in Dynamically Allocated Memory %@David A. Cohn,Satinder P. Singh %t1996 %cNIPS %f/NIPS/NIPS-1996-6420.pdf %*Multi-Task Learning for Stock Selection %@Joumana Ghosn,Yoshua Bengio %t1996 %cNIPS %f/NIPS/NIPS-1996-6421.pdf %*The Neurothermostat: Predictive Optimal Control of Residential Heating Systems %@Michael C. Mozer,Lucky Vidmar,Robert H. Dodier %t1996 %cNIPS %f/NIPS/NIPS-1996-6422.pdf %*A Comparison between Neural Networks and other Statistical Techniques for Modeling the Relationship between Tobacco and Alcohol and Cancer %@Tony Plate,Pierre Band,Joel Bert,John Grace %t1996 %cNIPS %f/NIPS/NIPS-1996-6423.pdf %*Reinforcement Learning for Dynamic Channel Allocation in Cellular Telephone Systems %@Satinder P. Singh,Dimitri P. Bertsekas %t1996 %cNIPS %f/NIPS/NIPS-1996-6424.pdf %*Spectroscopic Detection of Cervical Pre-Cancer through Radial Basis Function Networks %@Kagan Tumer,Nirmala Ramanujam,Rebecca R. Richards-Kortum,Joydeep Ghosh %t1996 %cNIPS %f/NIPS/NIPS-1996-6425.pdf %*Interpolating Earth-science Data using RBF Networks and Mixtures of Experts %@Ernest Wan,Don Bone %t1996 %cNIPS %f/NIPS/NIPS-1996-6426.pdf %*Multi-effect Decompositions for Financial Data Modeling %@Lizhong Wu,John E. Moody %t1996 %cNIPS %f/NIPS/NIPS-1996-6427.pdf %*Local Bandit Approximation for Optimal Learning Problems %@Michael O. Duff,Andrew G. Barto %t1996 %cNIPS %f/NIPS/NIPS-1996-6428.pdf %*Reinforcement Learning for Mixed Open-loop and Closed-loop Control %@Eric A. Hansen,Andrew G. Barto,Shlomo Zilberstein %t1996 %cNIPS %f/NIPS/NIPS-1996-6429.pdf %*Analytical Mean Squared Error Curves in Temporal Difference Learning %@Satinder P. Singh,Peter Dayan %t1996 %cNIPS %f/NIPS/NIPS-1996-6430.pdf %*Learning Decision Theoretic Utilities through Reinforcement Learning %@Magnus Stensmo,Terrence J. Sejnowski %t1996 %cNIPS %f/NIPS/NIPS-1996-6431.pdf %*On-line Policy Improvement using Monte-Carlo Search %@Gerald Tesauro,Gregory R. Galperin %t1996 %cNIPS %f/NIPS/NIPS-1996-6432.pdf %*Analysis of Temporal-Diffference Learning with Function Approximation %@John N. Tsitsiklis,Benjamin Van Roy %t1996 %cNIPS %f/NIPS/NIPS-1996-6433.pdf %*Approximate Solutions to Optimal Stopping Problems %@John N. Tsitsiklis,Benjamin Van Roy %t1996 %cNIPS %f/NIPS/NIPS-1996-6434.pdf %*A Model of Spatial Representations in Parietal Cortex Explains Hemineglect %@Alexandre Pouget,Terrence J. Sejnowski %t1995 %cNIPS %f/NIPS/NIPS-1995-6435.pdf %*Extracting Tree-Structured Representations of Trained Networks %@Mark Craven,Jude W. Shavlik %t1995 %cNIPS %f/NIPS/NIPS-1995-6436.pdf %*Dynamics of Attention as Near Saddle-Node Bifurcation Behavior %@Hiroyuki Nakahara,Kenji Doya %t1995 %cNIPS %f/NIPS/NIPS-1995-6437.pdf %*Rapid Quality Estimation of Neural Network Input Representations %@Kevin J. Cherkauer,Jude W. Shavlik %t1995 %cNIPS %f/NIPS/NIPS-1995-6438.pdf %*A Model of Auditory Streaming %@Susan L. McCabe,Michael J. Denham %t1995 %cNIPS %f/NIPS/NIPS-1995-6439.pdf %*Modeling Interactions of the Rat's Place and Head Direction Systems %@A. David Redish,David S. Touretzky %t1995 %cNIPS %f/NIPS/NIPS-1995-6440.pdf %*Correlated Neuronal Response: Time Scales and Mechanisms %@Wyeth Bair,Ehud Zohary,Christof Koch %t1995 %cNIPS %f/NIPS/NIPS-1995-6441.pdf %*Information through a Spiking Neuron %@Charles F. Stevens,Anthony M. Zador %t1995 %cNIPS %f/NIPS/NIPS-1995-6442.pdf %*Reorganisation of Somatosensory Cortex after Tactile Training %@Rasmus S. Petersen,John G. Taylor %t1995 %cNIPS %f/NIPS/NIPS-1995-6443.pdf %*A Dynamical Model of Context Dependencies for the Vestibulo-Ocular Reflex %@Olivier J. M. D. Coenen,Terrence J. Sejnowski %t1995 %cNIPS %f/NIPS/NIPS-1995-6444.pdf %*The Role of Activity in Synaptic Competition at the Neuromuscular Junction %@Samuel R. H. Joseph,David J. Willshaw %t1995 %cNIPS %f/NIPS/NIPS-1995-6445.pdf %*When is an Integrate-and-fire Neuron like a Poisson Neuron? %@Charles F. Stevens,Anthony M. Zador %t1995 %cNIPS %f/NIPS/NIPS-1995-6446.pdf %*The Geometry of Eye Rotations and Listing's Law %@Amir A. Handzel,Tamar Flash %t1995 %cNIPS %f/NIPS/NIPS-1995-6447.pdf %*Temporal coding in the sub-millisecond range: Model of barn owl auditory pathway %@Richard Kempter,Wulfram Gerstner,J. Leo van Hemmen,Hermann Wagner %t1995 %cNIPS %f/NIPS/NIPS-1995-6448.pdf %*Cholinergic suppression of transmission may allow combined associative memory function and self-organization in the neocortex %@Michael E. Hasselmo,Milos Cekic %t1995 %cNIPS %f/NIPS/NIPS-1995-6449.pdf %*A Predictive Switching Model of Cerebellar Movement Control %@Andrew G. Barto,James C. Houk %t1995 %cNIPS %f/NIPS/NIPS-1995-6450.pdf %*Independent Component Analysis of Electroencephalographic Data %@Scott Makeig,Anthony J. Bell,Tzyy-Ping Jung,Terrence J. Sejnowski %t1995 %cNIPS %f/NIPS/NIPS-1995-6451.pdf %*Plasticity of Center-Surround Opponent Receptive Fields in Real and Artificial Neural Systems of Vision %@S. Yasui,T. Furukawa,M. Yamada,T. Saito %t1995 %cNIPS %f/NIPS/NIPS-1995-6452.pdf %*Statistical Theory of Overtraining - Is Cross-Validation Asymptotically Effective? %@Shun-ichi Amari,Noboru Murata,Klaus-Robert Müller,Michael Finke,Howard Hua Yang %t1995 %cNIPS %f/NIPS/NIPS-1995-6453.pdf %*Learning with ensembles: How overfitting can be useful %@Peter Sollich,Anders Krogh %t1995 %cNIPS %f/NIPS/NIPS-1995-6454.pdf %*Neural Networks with Quadratic VC Dimension %@Pascal Koiran,Eduardo D. Sontag %t1995 %cNIPS %f/NIPS/NIPS-1995-6455.pdf %*Sample Complexity for Learning Recurrent Perceptron Mappings %@Bhaskar DasGupta,Eduardo D. Sontag %t1995 %cNIPS %f/NIPS/NIPS-1995-6456.pdf %*Estimating the Bayes Risk from Sample Data %@Robert R. Snapp,Tong Xu %t1995 %cNIPS %f/NIPS/NIPS-1995-6457.pdf %*Recursive Estimation of Dynamic Modular RBF Networks %@Visakan Kadirkamanathan,Maha Kadirkamanathan %t1995 %cNIPS %f/NIPS/NIPS-1995-6458.pdf %*On Neural Networks with Minimal Weights %@Vasken Bohossian,Jehoshua Bruck %t1995 %cNIPS %f/NIPS/NIPS-1995-6459.pdf %*Modern Analytic Techniques to Solve the Dynamics of Recurrent Neural Networks %@A.C.C. Coolen,S. N. Laughton,D. Sherrington %t1995 %cNIPS %f/NIPS/NIPS-1995-6460.pdf %*Implementation Issues in the Fourier Transform Algorithm %@Yishay Mansour,Sigal Sahar %t1995 %cNIPS %f/NIPS/NIPS-1995-6461.pdf %*Generalisation of A Class of Continuous Neural Networks %@John Shawe-Taylor,Jieyu Zhao %t1995 %cNIPS %f/NIPS/NIPS-1995-6462.pdf %*Gradient and Hamiltonian Dynamics Applied to Learning in Neural Networks %@James W. Howse,Chaouki T. Abdallah,Gregory L. Heileman %t1995 %cNIPS %f/NIPS/NIPS-1995-6463.pdf %*Strong Unimodality and Exact Learning of Constant Depth µ-Perceptron Networks %@Mario Marchand,Saeed Hadjifaradji %t1995 %cNIPS %f/NIPS/NIPS-1995-6464.pdf %*Dynamics of On-Line Gradient Descent Learning for Multilayer Neural Networks %@David Saad,Sara A. Solla %t1995 %cNIPS %f/NIPS/NIPS-1995-6465.pdf %*Worst-case Loss Bounds for Single Neurons %@David P. Helmbold,Jyrki Kivinen,Manfred K. Warmuth %t1995 %cNIPS %f/NIPS/NIPS-1995-6466.pdf %*Exponentially many local minima for single neurons %@Peter Auer,Mark Herbster,Manfred K. Warmuth %t1995 %cNIPS %f/NIPS/NIPS-1995-6467.pdf %*Adaptive Back-Propagation in On-Line Learning of Multilayer Networks %@Ansgar H. L. West,David Saad %t1995 %cNIPS %f/NIPS/NIPS-1995-6468.pdf %*Optimizing Cortical Mappings %@Geoffrey J. Goodhill,Steven Finch,Terrence J. Sejnowski %t1995 %cNIPS %f/NIPS/NIPS-1995-6469.pdf %*Examples of learning curves from a modified VC-formalism %@Adam Kowalczyk,Jacek Szymanski,Peter L. Bartlett,Robert C. Williamson %t1995 %cNIPS %f/NIPS/NIPS-1995-6470.pdf %*Bayesian Methods for Mixtures of Experts %@Steve R. Waterhouse,David MacKay,Anthony J. Robinson %t1995 %cNIPS %f/NIPS/NIPS-1995-6471.pdf %*Some results on convergent unlearning algorithm %@Serguei A. Semenov,Irina B. Shuvalova %t1995 %cNIPS %f/NIPS/NIPS-1995-6472.pdf %*Absence of Cycles in Symmetric Neural Networks %@Xin Wang,Arun K. Jagota,Fernanda Botelho,Max H. Garzon %t1995 %cNIPS %f/NIPS/NIPS-1995-6473.pdf %*REMAP: Recursive Estimation and Maximization of A Posteriori Probabilities - Application to Transition-Based Connectionist Speech Recognition %@Yochai Konig,Hervé Bourlard,Nelson Morgan %t1995 %cNIPS %f/NIPS/NIPS-1995-6474.pdf %*Recurrent Neural Networks for Missing or Asynchronous Data %@Yoshua Bengio,Francois Gingras %t1995 %cNIPS %f/NIPS/NIPS-1995-6475.pdf %*Discriminant Adaptive Nearest Neighbor Classification and Regression %@Trevor Hastie,Robert Tibshirani %t1995 %cNIPS %f/NIPS/NIPS-1995-6476.pdf %*Clustering data through an analogy to the Potts model %@Marcelo Blatt,Shai Wiseman,Eytan Domany %t1995 %cNIPS %f/NIPS/NIPS-1995-6477.pdf %*Generalized Learning Vector Quantization %@Atsushi Sato,Keiji Yamada %t1995 %cNIPS %f/NIPS/NIPS-1995-6478.pdf %*Stochastic Hillclimbing as a Baseline Method for Evaluating Genetic Algorithms %@Ari Juels,Martin Wattenberg %t1995 %cNIPS %f/NIPS/NIPS-1995-6479.pdf %*Universal Approximation and Learning of Trajectories Using Oscillators %@Pierre Baldi,Kurt Hornik %t1995 %cNIPS %f/NIPS/NIPS-1995-6480.pdf %*A Smoothing Regularizer for Recurrent Neural Networks %@Lizhong Wu,John E. Moody %t1995 %cNIPS %f/NIPS/NIPS-1995-6481.pdf %*EM Optimization of Latent-Variable Density Models %@Christopher M. Bishop,Markus Svensén,Christopher K. I. Williams %t1995 %cNIPS %f/NIPS/NIPS-1995-6482.pdf %*Factorial Hidden Markov Models %@Zoubin Ghahramani,Michael I. Jordan %t1995 %cNIPS %f/NIPS/NIPS-1995-6483.pdf %*Boosting Decision Trees %@Harris Drucker,Corinna Cortes %t1995 %cNIPS %f/NIPS/NIPS-1995-6484.pdf %*Exploiting Tractable Substructures in Intractable Networks %@Lawrence K. Saul,Michael I. Jordan %t1995 %cNIPS %f/NIPS/NIPS-1995-6485.pdf %*Hierarchical Recurrent Neural Networks for Long-Term Dependencies %@Salah El Hihi,Yoshua Bengio %t1995 %cNIPS %f/NIPS/NIPS-1995-6486.pdf %*Discovering Structure in Continuous Variables Using Bayesian Networks %@Reimar Hofmann,Volker Tresp %t1995 %cNIPS %f/NIPS/NIPS-1995-6487.pdf %*Using Pairs of Data-Points to Define Splits for Decision Trees %@Geoffrey E. Hinton,Michael Revow %t1995 %cNIPS %f/NIPS/NIPS-1995-6488.pdf %*Gaussian Processes for Regression %@Christopher K. I. Williams,Carl Edward Rasmussen %t1995 %cNIPS %f/NIPS/NIPS-1995-6489.pdf %*Pruning with generalization based weight saliencies: λOBD, λOBS %@Morten With Pedersen,Lars Kai Hansen,Jan Larsen %t1995 %cNIPS %f/NIPS/NIPS-1995-6490.pdf %*Fast Learning by Bounding Likelihoods in Sigmoid Type Belief Networks %@Tommi Jaakkola,Lawrence K. Saul,Michael I. Jordan %t1995 %cNIPS %f/NIPS/NIPS-1995-6491.pdf %*Generating Accurate and Diverse Members of a Neural-Network Ensemble %@David W. Opitz,Jude W. Shavlik %t1995 %cNIPS %f/NIPS/NIPS-1995-6492.pdf %*Improved Gaussian Mixture Density Estimates Using Bayesian Penalty Terms and Network Averaging %@Dirk Ormoneit,Volker Tresp %t1995 %cNIPS %f/NIPS/NIPS-1995-6493.pdf %*Explorations with the Dynamic Wave Model %@Thomas P. Rebotier,Jeffrey L. Elman %t1995 %cNIPS %f/NIPS/NIPS-1995-6494.pdf %*Tempering Backpropagation Networks: Not All Weights are Created Equal %@Nicol N. Schraudolph,Terrence J. Sejnowski %t1995 %cNIPS %f/NIPS/NIPS-1995-6495.pdf %*Investment Learning with Hierarchical PSOMs %@Jörg A. Walter,Helge Ritter %t1995 %cNIPS %f/NIPS/NIPS-1995-6496.pdf %*Learning long-term dependencies is not as difficult with NARX networks %@Tsungnan Lin,Bill G. Horne,Peter Tiño,C. Lee Giles %t1995 %cNIPS %f/NIPS/NIPS-1995-6497.pdf %*Constructive Algorithms for Hierarchical Mixtures of Experts %@Steve R. Waterhouse,Anthony J. Robinson %t1995 %cNIPS %f/NIPS/NIPS-1995-6498.pdf %*An Information-theoretic Learning Algorithm for Neural Network Classification %@David J. Miller,Ajit V. Rao,Kenneth Rose,Allen Gersho %t1995 %cNIPS %f/NIPS/NIPS-1995-6499.pdf %*From Isolation to Cooperation: An Alternative View of a System of Experts %@Stefan Schaal,Christopher G. Atkeson %t1995 %cNIPS %f/NIPS/NIPS-1995-6500.pdf %*SPERT-II: A Vector Microprocessor System and its Application to Large Problems in Backpropagation Training %@John Wawrzynek,Krste Asanovic,Brian Kingsbury,James Beck,David Johnson,Nelson Morgan %t1995 %cNIPS %f/NIPS/NIPS-1995-6501.pdf %*Softassign versus Softmax: Benchmarks in Combinatorial Optimization %@Steven Gold,Anand Rangarajan %t1995 %cNIPS %f/NIPS/NIPS-1995-6502.pdf %*A Multiscale Attentional Framework for Relaxation Neural Networks %@Dimitris I. Tsioutsias,Eric Mjolsness %t1995 %cNIPS %f/NIPS/NIPS-1995-6503.pdf %*Learning Sparse Perceptrons %@Jeffrey C. Jackson,Mark Craven %t1995 %cNIPS %f/NIPS/NIPS-1995-6504.pdf %*Does the Wake-sleep Algorithm Produce Good Density Estimators? %@Brendan J. Frey,Geoffrey E. Hinton,Peter Dayan %t1995 %cNIPS %f/NIPS/NIPS-1995-6505.pdf %*Improved Silicon Cochlea using Compatible Lateral Bipolar Transistors %@André van Schaik,Eric Fragnière,Eric A. Vittoz %t1995 %cNIPS %f/NIPS/NIPS-1995-6506.pdf %*Adaptive Retina with Center-Surround Receptive Field %@Shih-Chii Liu,Kwabena Boahen %t1995 %cNIPS %f/NIPS/NIPS-1995-6507.pdf %*Neuron-MOS Temporal Winner Search Hardware for Fully-Parallel Data Processing %@Tadashi Shibata,Tsutomu Nakai,Tatsuo Morimoto,Ryu Kaihara,Takeo Yamashita,Tadahiro Ohmi %t1995 %cNIPS %f/NIPS/NIPS-1995-6508.pdf %*Analog VLSI Processor Implementing the Continuous Wavelet Transform %@R. Timothy Edwards,Gert Cauwenberghs %t1995 %cNIPS %f/NIPS/NIPS-1995-6509.pdf %*Silicon Models for Auditory Scene Analysis %@John Lazzaro,John Wawrzynek %t1995 %cNIPS %f/NIPS/NIPS-1995-6510.pdf %*VLSI Model of Primate Visual Smooth Pursuit %@Ralph Etienne-Cummings,Jan Van der Spiegel,Paul Mueller %t1995 %cNIPS %f/NIPS/NIPS-1995-6511.pdf %*Model Matching and SFMD Computation %@Steven Rehfuss,Dan W. Hammerstrom %t1995 %cNIPS %f/NIPS/NIPS-1995-6512.pdf %*Parallel analog VLSI architectures for computation of heading direction and time-to-contact %@Giacomo Indiveri,Jörg Kramer,Christof Koch %t1995 %cNIPS %f/NIPS/NIPS-1995-6513.pdf %*Laterally Interconnected Self-Organizing Maps in Hand-Written Digit Recognition %@Yoonsuck Choe,Joseph Sirosh,Risto Miikkulainen %t1995 %cNIPS %f/NIPS/NIPS-1995-6514.pdf %*Forward-backward retraining of recurrent neural networks %@Andrew W. Senior,Anthony J. Robinson %t1995 %cNIPS %f/NIPS/NIPS-1995-6515.pdf %*Context-Dependent Classes in a Hybrid Recurrent Network-HMM Speech Recognition System %@Dan J. Kershaw,Anthony J. Robinson,Mike Hochberg %t1995 %cNIPS %f/NIPS/NIPS-1995-6516.pdf %*A New Learning Algorithm for Blind Signal Separation %@Shun-ichi Amari,Andrzej Cichocki,Howard Hua Yang %t1995 %cNIPS %f/NIPS/NIPS-1995-6517.pdf %*Handwritten Word Recognition using Contextual Hybrid Radial Basis Function Network/Hidden Markov Models %@Bernard Lemarié,Michel Gilloux,Manuel Leroux %t1995 %cNIPS %f/NIPS/NIPS-1995-6518.pdf %*KODAK lMAGELINK™ OCR Alphanumeric Handprint Module %@Alexander Shustorovich,Christopher W. Thrasher %t1995 %cNIPS %f/NIPS/NIPS-1995-6519.pdf %*The Gamma MLP for Speech Phoneme Recognition %@Steve Lawrence,Ah Chung Tsoi,Andrew D. Back %t1995 %cNIPS %f/NIPS/NIPS-1995-6520.pdf %*A Framework for Non-rigid Matching and Correspondence %@Suguna Pappu,Steven Gold,Anand Rangarajan %t1995 %cNIPS %f/NIPS/NIPS-1995-6521.pdf %*Control of Selective Visual Attention: Modeling the "Where" Pathway %@Ernst Niebur,Christof Koch %t1995 %cNIPS %f/NIPS/NIPS-1995-6522.pdf %*Learning to Predict Visibility and Invisibility from Occlusion Events %@Jonathan A. Marshall,Richard K. Alley,Robert S. Hubbard %t1995 %cNIPS %f/NIPS/NIPS-1995-6523.pdf %*Classifying Facial Action %@Marian Stewart Bartlett,Paul A. Viola,Terrence J. Sejnowski,Beatrice A. Golomb,Jan Larsen,Joseph C. Hager,Paul Ekman %t1995 %cNIPS %f/NIPS/NIPS-1995-6524.pdf %*Modeling Saccadic Targeting in Visual Search %@Rajesh P. N. Rao,Gregory J. Zelinsky,Mary M. Hayhoe,Dana H. Ballard %t1995 %cNIPS %f/NIPS/NIPS-1995-6525.pdf %*A Neural Network Model of 3-D Lightness Perception %@Luiz Pessoa,William D. Ross %t1995 %cNIPS %f/NIPS/NIPS-1995-6526.pdf %*Empirical Entropy Manipulation for Real-World Problems %@Paul A. Viola,Nicol N. Schraudolph,Terrence J. Sejnowski %t1995 %cNIPS %f/NIPS/NIPS-1995-6527.pdf %*Active Gesture Recognition using Learned Visual Attention %@Trevor Darrell,Alex Pentland %t1995 %cNIPS %f/NIPS/NIPS-1995-6528.pdf %*Human Face Detection in Visual Scenes %@Henry A. Rowley,Shumeet Baluja,Takeo Kanade %t1995 %cNIPS %f/NIPS/NIPS-1995-6529.pdf %*Improving Committee Diagnosis with Resampling Techniques %@Bambang Parmanto,Paul W. Munro,Howard R. Doyle %t1995 %cNIPS %f/NIPS/NIPS-1995-6530.pdf %*Beating a Defender in Robotic Soccer: Memory-Based Learning of a Continuous Function %@Peter Stone,Manuela M. Veloso %t1995 %cNIPS %f/NIPS/NIPS-1995-6531.pdf %*Visual gesture-based robot guidance with a modular neural system %@Enno Littmann,Andrea Drees,Helge Ritter %t1995 %cNIPS %f/NIPS/NIPS-1995-6532.pdf %*A Novel Channel Selection System in Cochlear Implants Using Artificial Neural Network %@Marwan A. Jabri,Raymond J. Wang %t1995 %cNIPS %f/NIPS/NIPS-1995-6533.pdf %*Prediction of Beta Sheets in Proteins %@Anders Krogh,Soren Kamaric Riis %t1995 %cNIPS %f/NIPS/NIPS-1995-6534.pdf %*A Neural Network Autoassociator for Induction Motor Failure Prediction %@Thomas Petsche,Angelo Marcantonio,Christian Darken,Stephen Jose Hanson,Gary M. Kuhn,N. Iwan Santoso %t1995 %cNIPS %f/NIPS/NIPS-1995-6535.pdf %*Using Feedforward Neural Networks to Monitor Alertness from Changes in EEG Correlation and Coherence %@Scott Makeig,Tzyy-Ping Jung,Terrence J. Sejnowski %t1995 %cNIPS %f/NIPS/NIPS-1995-6536.pdf %*A Neural Network Classifier for the I100 OCR Chip %@John C. Platt,Timothy P. Allen %t1995 %cNIPS %f/NIPS/NIPS-1995-6537.pdf %*Predictive Q-Routing: A Memory-based Reinforcement Learning Approach to Adaptive Traffic Control %@Samuel P. M. Choi,Dit-Yan Yeung %t1995 %cNIPS %f/NIPS/NIPS-1995-6538.pdf %*Using the Future to "Sort Out" the Present: Rankprop and Multitask Learning for Medical Risk Evaluation %@Rich Caruana,Shumeet Baluja,Tom Mitchell %t1995 %cNIPS %f/NIPS/NIPS-1995-6539.pdf %*Experiments with Neural Networks for Real Time Implementation of Control %@Peter K. Campbell,Michael Dale,Herman L. Ferrá,Adam Kowalczyk %t1995 %cNIPS %f/NIPS/NIPS-1995-6540.pdf %*High-Speed Airborne Particle Monitoring Using Artificial Neural Networks %@Alistair Ferguson,Theo Sabisch,Paul Kaye,Laurence C. Dixon,Hamid Bolouri %t1995 %cNIPS %f/NIPS/NIPS-1995-6541.pdf %*A Dynamical Systems Approach for a Learnable Autonomous Robot %@Jun Tani,Naohiro Fukumura %t1995 %cNIPS %f/NIPS/NIPS-1995-6542.pdf %*Parallel Optimization of Motion Controllers via Policy Iteration %@Jefferson A. Coelho Jr.,R. Sitaraman,Roderic A. Grupen %t1995 %cNIPS %f/NIPS/NIPS-1995-6543.pdf %*Learning Fine Motion by Markov Mixtures of Experts %@Marina Meila,Michael I. Jordan %t1995 %cNIPS %f/NIPS/NIPS-1995-6544.pdf %*Neural Control for Nonlinear Dynamic Systems %@Ssu-Hsin Yu,Anuradha M. Annaswamy %t1995 %cNIPS %f/NIPS/NIPS-1995-6545.pdf %*Improving Elevator Performance Using Reinforcement Learning %@Robert H. Crites,Andrew G. Barto %t1995 %cNIPS %f/NIPS/NIPS-1995-6546.pdf %*High-Performance Job-Shop Scheduling With A Time-Delay TD(λ) Network %@Wei Zhang,Thomas G. Dietterich %t1995 %cNIPS %f/NIPS/NIPS-1995-6547.pdf %*Competence Acquisition in an Autonomous Mobile Robot using Hardware Neural Techniques %@Geoffrey B. Jackson,Alan F. Murray %t1995 %cNIPS %f/NIPS/NIPS-1995-6548.pdf %*Stable LInear Approximations to Dynamic Programming for Stochastic Control Problems with Local Transitions %@Benjamin Van Roy,John N. Tsitsiklis %t1995 %cNIPS %f/NIPS/NIPS-1995-6549.pdf %*Improving Policies without Measuring Merits %@Peter Dayan,Satinder P. Singh %t1995 %cNIPS %f/NIPS/NIPS-1995-6550.pdf %*Memory-based Stochastic Optimization %@Andrew W. Moore,Jeff G. Schneider %t1995 %cNIPS %f/NIPS/NIPS-1995-6551.pdf %*Reinforcement Learning by Probability Matching %@Philip N. Sabes,Michael I. Jordan %t1995 %cNIPS %f/NIPS/NIPS-1995-6552.pdf %*Direction Selectivity In Primary Visual Cortex Using Massive Intracortical Connections %@Humbert Suarez,Christof Koch,Rodney Douglas %t1994 %cNIPS %f/NIPS/NIPS-1994-6553.pdf %*On the Computational Utility of Consciousness %@Donald W. Mathis,Michael C. Mozer %t1994 %cNIPS %f/NIPS/NIPS-1994-6554.pdf %*Catastrophic Interference in Human Motor Learning %@Tom Brashers-Krug,Reza Shadmehr,Emanuel Todorov %t1994 %cNIPS %f/NIPS/NIPS-1994-6555.pdf %*Patterns of damage in neural networks: The effects of lesion area, shape and number %@Eytan Ruppin,James A. Reggia %t1994 %cNIPS %f/NIPS/NIPS-1994-6556.pdf %*Forward dynamic models in human motor control: Psychophysical evidence %@Daniel M. Wolpert,Zoubin Ghahramani,Michael I. Jordan %t1994 %cNIPS %f/NIPS/NIPS-1994-6557.pdf %*A Model for Chemosensory Reception %@Rainer Malaka,Thomas Ragg,Martin Hammer %t1994 %cNIPS %f/NIPS/NIPS-1994-6558.pdf %*The Electrotonic Transformation: a Tool for Relating Neuronal Form to Function %@Nicholas T. Carnevale,Kenneth Y. Tsai,Brenda J. Claiborne,Thomas H. Brown %t1994 %cNIPS %f/NIPS/NIPS-1994-6559.pdf %*A model of the hippocampus combining self-organization and associative memory function %@Michael E. Hasselmo,Eric Schnell,Joshua Berke,Edi Barkai %t1994 %cNIPS %f/NIPS/NIPS-1994-6560.pdf %*Model of a Biological Neuron as a Temporal Neural Network %@Sean D. Murphy,Edward W. Kairiss %t1994 %cNIPS %f/NIPS/NIPS-1994-6561.pdf %*A Critical Comparison of Models for Orientation and Ocular Dominance Columns in the Striate Cortex %@E. Erwin,K. Obermayer,K. Schulten %t1994 %cNIPS %f/NIPS/NIPS-1994-6562.pdf %*A Novel Reinforcement Model of Birdsong Vocalization Learning %@Kenji Doya,Terrence J. Sejnowski %t1994 %cNIPS %f/NIPS/NIPS-1994-6563.pdf %*Ocular Dominance and Patterned Lateral Connections in a Self-Organizing Model of the Primary Visual Cortex %@Joseph Sirosh,Risto Miikkulainen %t1994 %cNIPS %f/NIPS/NIPS-1994-6564.pdf %*Anatomical origin and computational role of diversity in the response properties of cortical neurons %@Kalanit Grill Spector,Shimon Edelman,Rafael Malach %t1994 %cNIPS %f/NIPS/NIPS-1994-6565.pdf %*Reinforcement Learning Predicts the Site of Plasticity for Auditory Remapping in the Barn Owl %@Alexandre Pouget,Cedric Deffayet,Terrence J. Sejnowski %t1994 %cNIPS %f/NIPS/NIPS-1994-6566.pdf %*Morphogenesis of the Lateral Geniculate Nucleus: How Singularities Affect Global Structure %@Svilen Tzonev,Klaus Schulten,Joseph G. Malpeli %t1994 %cNIPS %f/NIPS/NIPS-1994-6567.pdf %*A Computational Model of Prefrontal Cortex Function %@Todd S. Braver,Jonathan D. Cohen,David Servan-Schreiber %t1994 %cNIPS %f/NIPS/NIPS-1994-6568.pdf %*A Neural Model of Delusions and Hallucinations in Schizophrenia %@Eytan Ruppin,James A. Reggia,David Horn %t1994 %cNIPS %f/NIPS/NIPS-1994-6569.pdf %*Spatial Representations in the Parietal Cortex May Use Basis Functions %@Alexandre Pouget,Terrence J. Sejnowski %t1994 %cNIPS %f/NIPS/NIPS-1994-6570.pdf %*Grouping Components of Three-Dimensional Moving Objects in Area MST of Visual Cortex %@Richard S. Zemel,Terrence J. Sejnowski %t1994 %cNIPS %f/NIPS/NIPS-1994-6571.pdf %*A Model of the Neural Basis of the Rat's Sense of Direction %@William E. Skaggs,James J. Knierim,Hemant S. Kudrimoti,Bruce L. McNaughton %t1994 %cNIPS %f/NIPS/NIPS-1994-6572.pdf %*H∞ Optimal Training Algorithms and their Relation to Backpropagation %@Babak Hassibi,Thomas Kailath %t1994 %cNIPS %f/NIPS/NIPS-1994-6573.pdf %*Synchrony and Desynchrony in Neural Oscillator Networks %@Deliang Wang,David Terman %t1994 %cNIPS %f/NIPS/NIPS-1994-6574.pdf %*Generalisation in Feedforward Networks %@Adam Kowalczyk,Herman L. Ferrá %t1994 %cNIPS %f/NIPS/NIPS-1994-6575.pdf %*Neural Network Ensembles, Cross Validation, and Active Learning %@Anders Krogh,Jesper Vedelsby %t1994 %cNIPS %f/NIPS/NIPS-1994-6576.pdf %*Limits on Learning Machine Accuracy Imposed by Data Quality %@Corinna Cortes,L. D. Jackel,Wan-Ping Chiang %t1994 %cNIPS %f/NIPS/NIPS-1994-6577.pdf %*Higher Order Statistical Decorrelation without Information Loss %@Gustavo Deco,Wilfried Brauer %t1994 %cNIPS %f/NIPS/NIPS-1994-6578.pdf %*Hyperparameters Evidence and Generalisation for an Unrealisable Rule %@Glenn Marion,David Saad %t1994 %cNIPS %f/NIPS/NIPS-1994-6579.pdf %*Temporal Dynamics of Generalization in Neural Networks %@Changfeng Wang,Santosh S. Venkatesh %t1994 %cNIPS %f/NIPS/NIPS-1994-6580.pdf %*Stochastic Dynamics of Three-State Neural Networks %@Toru Ohira,Jack D. Cowan %t1994 %cNIPS %f/NIPS/NIPS-1994-6581.pdf %*Learning Stochastic Perceptrons Under k-Blocking Distributions %@Mario Marchand,Saeed Hadjifaradji %t1994 %cNIPS %f/NIPS/NIPS-1994-6582.pdf %*Learning from queries for maximum information gain in imperfectly learnable problems %@Peter Sollich,David Saad %t1994 %cNIPS %f/NIPS/NIPS-1994-6583.pdf %*On-line Learning of Dichotomies %@N. Barkai,H. S. Seung,H. Sompolinsky %t1994 %cNIPS %f/NIPS/NIPS-1994-6584.pdf %*Dynamic Modelling of Chaotic Time Series with Neural Networks %@Jose C. Principe,Jyh-Ming Kuo %t1994 %cNIPS %f/NIPS/NIPS-1994-6585.pdf %*A Rigorous Analysis of Linsker-type Hebbian Learning %@J. Feng,H. Pan,V. P. Roychowdhury %t1994 %cNIPS %f/NIPS/NIPS-1994-6586.pdf %*Sample Size Requirements for Feedforward Neural Networks %@Michael J. Turmon,Terrence L. Fine %t1994 %cNIPS %f/NIPS/NIPS-1994-6587.pdf %*Asymptotics of Gradient-based Neural Network Training Algorithms %@Sayandev Mukherjee,Terrence L. Fine %t1994 %cNIPS %f/NIPS/NIPS-1994-6588.pdf %*Reinforcement Learning Algorithm for Partially Observable Markov Decision Problems %@Tommi Jaakkola,Satinder P. Singh,Michael I. Jordan %t1994 %cNIPS %f/NIPS/NIPS-1994-6589.pdf %*Advantage Updating Applied to a Differential Game %@Mance E. Harmon,Leemon C. Baird III,A. Harry Klopf %t1994 %cNIPS %f/NIPS/NIPS-1994-6590.pdf %*Reinforcement Learning with Soft State Aggregation %@Satinder P. Singh,Tommi Jaakkola,Michael I. Jordan %t1994 %cNIPS %f/NIPS/NIPS-1994-6591.pdf %*Generalization in Reinforcement Learning: Safely Approximating the Value Function %@Justin A. Boyan,Andrew W. Moore %t1994 %cNIPS %f/NIPS/NIPS-1994-6592.pdf %*Finding Structure in Reinforcement Learning %@Sebastian Thrun,Anton Schwartz %t1994 %cNIPS %f/NIPS/NIPS-1994-6593.pdf %*Reinforcement Learning Methods for Continuous-Time Markov Decision Problems %@Steven J. Bradtke,Michael O. Duff %t1994 %cNIPS %f/NIPS/NIPS-1994-6594.pdf %*An Actor/Critic Algorithm that is Equivalent to Q-Learning %@Robert H. Crites,Andrew G. Barto %t1994 %cNIPS %f/NIPS/NIPS-1994-6595.pdf %*Combining Estimators Using Non-Constant Weighting Functions %@Volker Tresp,Michiaki Taniguchi %t1994 %cNIPS %f/NIPS/NIPS-1994-6596.pdf %*An Input Output HMM Architecture %@Yoshua Bengio,Paolo Frasconi %t1994 %cNIPS %f/NIPS/NIPS-1994-6597.pdf %*Boltzmann Chains and Hidden Markov Models %@Lawrence K. Saul,Michael I. Jordan %t1994 %cNIPS %f/NIPS/NIPS-1994-6598.pdf %*Bayesian Query Construction for Neural Network Models %@Gerhard Paass,Jörg Kindermann %t1994 %cNIPS %f/NIPS/NIPS-1994-6599.pdf %*Using a Saliency Map for Active Spatial Selective Attention: Implementation & Initial Results %@Shumeet Baluja,Dean A. Pomerleau %t1994 %cNIPS %f/NIPS/NIPS-1994-6600.pdf %*Multidimensional Scaling and Data Clustering %@Thomas Hofmann,Joachim Buhmann %t1994 %cNIPS %f/NIPS/NIPS-1994-6601.pdf %*A Non-linear Information Maximisation Algorithm that Performs Blind Separation %@Anthony J. Bell,Terrence J. Sejnowski %t1994 %cNIPS %f/NIPS/NIPS-1994-6602.pdf %*Plasticity-Mediated Competitive Learning %@Nicol N. Schraudolph,Terrence J. Sejnowski %t1994 %cNIPS %f/NIPS/NIPS-1994-6603.pdf %*Phase-Space Learning %@Fu-Sheng Tsung,Garrison W. Cottrell %t1994 %cNIPS %f/NIPS/NIPS-1994-6604.pdf %*Learning Local Error Bars for Nonlinear Regression %@David A. Nix,Andreas S. Weigend %t1994 %cNIPS %f/NIPS/NIPS-1994-6605.pdf %*Dynamic Cell Structures %@Jörg Bruske,Gerald Sommer %t1994 %cNIPS %f/NIPS/NIPS-1994-6606.pdf %*Capacity and Information Efficiency of a Brain-like Associative Net %@Bruce Graham,David Willshaw %t1994 %cNIPS %f/NIPS/NIPS-1994-6607.pdf %*Boosting the Performance of RBF Networks with Dynamic Decay Adjustment %@Michael R. Berthold,Jay Diamond %t1994 %cNIPS %f/NIPS/NIPS-1994-6608.pdf %*SIMPLIFYING NEURAL NETS BY DISCOVERING FLAT MINIMA %@Sepp Hochreiter,Juergen Schmidhuber %t1994 %cNIPS %f/NIPS/NIPS-1994-6609.pdf %*Learning with Product Units %@Laurens R. Leerink,C. Lee Giles,Bill G. Horne,Marwan A. Jabri %t1994 %cNIPS %f/NIPS/NIPS-1994-6610.pdf %*Deterministic Annealing Variant of the EM Algorithm %@Naonori Ueda,Ryohei Nakano %t1994 %cNIPS %f/NIPS/NIPS-1994-6611.pdf %*Diffusion of Credit in Markovian Models %@Yoshua Bengio,Paolo Frasconi %t1994 %cNIPS %f/NIPS/NIPS-1994-6612.pdf %*Factorial Learning by Clustering Features %@Joshua B. Tenenbaum,Emanuel V. Todorov %t1994 %cNIPS %f/NIPS/NIPS-1994-6613.pdf %*Interior Point Implementations of Alternating Minimization Training %@Michael Lemmon,Peter T. Szymanski %t1994 %cNIPS %f/NIPS/NIPS-1994-6614.pdf %*SARDNET: A Self-Organizing Feature Map for Sequences %@Daniel L. James,Risto Miikkulainen %t1994 %cNIPS %f/NIPS/NIPS-1994-6615.pdf %*Convergence Properties of the K-Means Algorithms %@Léon Bottou,Yoshua Bengio %t1994 %cNIPS %f/NIPS/NIPS-1994-6616.pdf %*Active Learning for Function Approximation %@Kah Kay Sung,Partha Niyogi %t1994 %cNIPS %f/NIPS/NIPS-1994-6617.pdf %*Analysis of Unstandardized Contributions in Cross Connected Networks %@Thomas R. Shultz,Yuriko Oshima-Takane,Yoshio Takane %t1994 %cNIPS %f/NIPS/NIPS-1994-6618.pdf %*Template-Based Algorithms for Connectionist Rule Extraction %@Jay A. Alexander,Michael C. Mozer %t1994 %cNIPS %f/NIPS/NIPS-1994-6619.pdf %*An Alternative Model for Mixtures of Experts %@Lei Xu,Michael I. Jordan,Geoffrey E. Hinton %t1994 %cNIPS %f/NIPS/NIPS-1994-6620.pdf %*Estimating Conditional Probability Densities for Periodic Variables %@Chris M. Bishop,Claire Legleye %t1994 %cNIPS %f/NIPS/NIPS-1994-6621.pdf %*Effects of Noise on Convergence and Generalization in Recurrent Networks %@Kam Jim,Bill G. Horne,C. Lee Giles %t1994 %cNIPS %f/NIPS/NIPS-1994-6622.pdf %*A Rapid Graph-based Method for Arbitrary Transformation-Invariant Pattern Classification %@Alessandro Sperduti,David G. Stork %t1994 %cNIPS %f/NIPS/NIPS-1994-6623.pdf %*Recurrent Networks: Second Order Properties and Pruning %@Morten With Pedersen,Lars Kai Hansen %t1994 %cNIPS %f/NIPS/NIPS-1994-6624.pdf %*Classifying with Gaussian Mixtures and Clusters %@Nanda Kambhatla,Todd K. Leen %t1994 %cNIPS %f/NIPS/NIPS-1994-6625.pdf %*Efficient Methods for Dealing with Missing Data in Supervised Learning %@Volker Tresp,Ralph Neuneier,Subutai Ahmad %t1994 %cNIPS %f/NIPS/NIPS-1994-6626.pdf %*An experimental comparison of recurrent neural networks %@Bill G. Horne,C. Lee Giles %t1994 %cNIPS %f/NIPS/NIPS-1994-6627.pdf %*Active Learning with Statistical Models %@David A. Cohn,Zoubin Ghahramani,Michael I. Jordan %t1994 %cNIPS %f/NIPS/NIPS-1994-6628.pdf %*Learning with Preknowledge: Clustering with Point and Graph Matching Distance Measures %@Steven Gold,Anand Rangarajan,Eric Mjolsness %t1994 %cNIPS %f/NIPS/NIPS-1994-6629.pdf %*Direct Multi-Step Time Series Prediction Using TD(λ) %@Peter T. Kazlas,Andreas S. Weigend %t1994 %cNIPS %f/NIPS/NIPS-1994-6630.pdf %*ICEG Morphology Classification using an Analogue VLSI Neural Network %@Richard Coggins,Marwan A. Jabri,Barry Flower,Stephen Pickard %t1994 %cNIPS %f/NIPS/NIPS-1994-6631.pdf %*A Silicon Axon %@Bradley A. Minch,Paul E. Hasler,Chris Diorio,Carver Mead %t1994 %cNIPS %f/NIPS/NIPS-1994-6632.pdf %*The Ni1000: High Speed Parallel VLSI for Implementing Multilayer Perceptrons %@Michael P. Perrone,Leon N. Cooper %t1994 %cNIPS %f/NIPS/NIPS-1994-6633.pdf %*A Real Time Clustering CMOS Neural Engine %@Teresa Serrano-Gotarredona,Bernabé Linares-Barranco,José Luis Huertas %t1994 %cNIPS %f/NIPS/NIPS-1994-6634.pdf %*Pulsestream Synapses with Non-Volatile Analogue Amorphous-Silicon Memories %@A. J. Holmes,Alan F. Murray,Stephen Churcher,J. Hajto,M. J. Rose %t1994 %cNIPS %f/NIPS/NIPS-1994-6635.pdf %*A Lagrangian Formulation For Optical Backpropagation Training In Kerr-Type Optical Networks %@James Edward Steck,Steven R. Skinner,Alvaro A. Cruz-Cabrara,Elizabeth C. Behrman %t1994 %cNIPS %f/NIPS/NIPS-1994-6636.pdf %*A Charge-Based CMOS Parallel Analog Vector Quantizer %@Gert Cauwenberghs,Volnei Pedroni %t1994 %cNIPS %f/NIPS/NIPS-1994-6637.pdf %*An Analog Neural Network Inspired by Fractal Block Coding %@Fernando J. Pineda,Andreas G. Andreou %t1994 %cNIPS %f/NIPS/NIPS-1994-6638.pdf %*A Study of Parallel Perturbative Gradient Descent %@D. Lippe,Joshua Alspector %t1994 %cNIPS %f/NIPS/NIPS-1994-6639.pdf %*Implementation of Neural Hardware with the Neural VLSI of URAN in Applications with Reduced Representations %@Il Song Han,Ki-Chul Kim,Hwang-Soo Lee %t1994 %cNIPS %f/NIPS/NIPS-1994-6640.pdf %*Single Transistor Learning Synapses %@Paul E. Hasler,Chris Diorio,Bradley A. Minch,Carver Mead %t1994 %cNIPS %f/NIPS/NIPS-1994-6641.pdf %*Non-linear Prediction of Acoustic Vectors Using Hierarchical Mixtures of Experts %@Steve R. Waterhouse,Anthony J. Robinson %t1994 %cNIPS %f/NIPS/NIPS-1994-6642.pdf %*Glove-TalkII: Mapping Hand Gestures to Speech Using Neural Networks %@Sidney Fels,Geoffrey E. Hinton %t1994 %cNIPS %f/NIPS/NIPS-1994-6643.pdf %*Hierarchical Mixtures of Experts Methodology Applied to Continuous Speech Recognition %@Ying Zhao,Richard M. Schwartz,Jason J. Sroka,John Makhoul %t1994 %cNIPS %f/NIPS/NIPS-1994-6644.pdf %*Connectionist Speaker Normalization with Generalized Resource Allocating Networks %@Cesare Furlanello,Diego Giuliani,Edmondo Trentin %t1994 %cNIPS %f/NIPS/NIPS-1994-6645.pdf %*Using Voice Transformations to Create Additional Training Talkers for Word Spotting %@Eric I. Chang,Richard P. Lippmann %t1994 %cNIPS %f/NIPS/NIPS-1994-6646.pdf %*A Comparison of Discrete-Time Operator Models for Nonlinear System Identification %@Andrew D. Back,Ah Chung Tsoi %t1994 %cNIPS %f/NIPS/NIPS-1994-6647.pdf %*Learning Saccadic Eye Movements Using Multiscale Spatial Filters %@Rajesh P. N. Rao,Dana H. Ballard %t1994 %cNIPS %f/NIPS/NIPS-1994-6648.pdf %*A Convolutional Neural Network Hand Tracker %@Steven J. Nowlan,John C. Platt %t1994 %cNIPS %f/NIPS/NIPS-1994-6649.pdf %*Correlation and Interpolation Networks for Real-time Expression Analysis/Synthesis %@Trevor Darrell,Irfan A. Essa,Alex Pentland %t1994 %cNIPS %f/NIPS/NIPS-1994-6650.pdf %*Learning direction in global motion: two classes of psychophysically-motivated models %@V. Sundareswaran,Lucia M. Vaina %t1994 %cNIPS %f/NIPS/NIPS-1994-6651.pdf %*PCA-Pyramids for Image Compression %@Horst Bischof,Kurt Hornik %t1994 %cNIPS %f/NIPS/NIPS-1994-6652.pdf %*Unsupervised Classification of 3D Objects from 2D Views %@Satoshi Suzuki,Hiroshi Ando %t1994 %cNIPS %f/NIPS/NIPS-1994-6653.pdf %*New Algorithms for 2D and 3D Point Matching: Pose Estimation and Correspondence %@Steven Gold,Chien-Ping Lu,Anand Rangarajan,Suguna Pappu,Eric Mjolsness %t1994 %cNIPS %f/NIPS/NIPS-1994-6654.pdf %*Using a neural net to instantiate a deformable model %@Christopher K. I. Williams,Michael Revow,Geoffrey E. Hinton %t1994 %cNIPS %f/NIPS/NIPS-1994-6655.pdf %*Nonlinear Image Interpolation using Manifold Learning %@Christoph Bregler,Stephen M. Omohundro %t1994 %cNIPS %f/NIPS/NIPS-1994-6656.pdf %*Coarse-to-Fine Image Search Using Neural Networks %@Clay Spence,John C. Pearson,Jim Bergen %t1994 %cNIPS %f/NIPS/NIPS-1994-6657.pdf %*Transformation Invariant Autoassociation with Application to Handwritten Character Recognition %@Holger Schwenk,Maurice Milgram %t1994 %cNIPS %f/NIPS/NIPS-1994-6658.pdf %*Learning Prototype Models for Tangent Distance %@Trevor Hastie,Patrice Simard %t1994 %cNIPS %f/NIPS/NIPS-1994-6659.pdf %*Real-Time Control of a Tokamak Plasma Using Neural Networks %@Chris M. Bishop,Paul S. Haynes,Mike E U Smith,Tom N. Todd,David L. Trotman,Colin G. Windsor %t1994 %cNIPS %f/NIPS/NIPS-1994-6660.pdf %*Recognizing Handwritten Digits Using Mixtures of Linear Models %@Geoffrey E. Hinton,Michael Revow,Peter Dayan %t1994 %cNIPS %f/NIPS/NIPS-1994-6661.pdf %*An Integrated Architecture of Adaptive Neural Network Control for Dynamic Systems %@Ke Liu,Robert L. Tokar,Brain D. McVey %t1994 %cNIPS %f/NIPS/NIPS-1994-6662.pdf %*Predictive Coding with Neural Nets: Application to Text Compression %@Juergen Schmidhuber,Stefan Heil %t1994 %cNIPS %f/NIPS/NIPS-1994-6663.pdf %*Predicting the Risk of Complications in Coronary Artery Bypass Operations using Neural Networks %@Richard P. Lippmann,Linda Kukolich,David Shahian %t1994 %cNIPS %f/NIPS/NIPS-1994-6664.pdf %*Comparing the prediction accuracy of artificial neural networks and other statistical models for breast cancer survival %@Harry B. Burke,David B. Rosen,Philip H. Goodman %t1994 %cNIPS %f/NIPS/NIPS-1994-6665.pdf %*A Mixture Model System for Medical and Machine Diagnosis %@Magnus Stensmo,Terrence J. Sejnowski %t1994 %cNIPS %f/NIPS/NIPS-1994-6666.pdf %*Inferring Ground Truth from Subjective Labelling of Venus Images %@Padhraic Smyth,Usama M. Fayyad,Michael C. Burl,Pietro Perona,Pierre Baldi %t1994 %cNIPS %f/NIPS/NIPS-1994-6667.pdf %*The Use of Dynamic Writing Information in a Connectionist On-Line Cursive Handwriting Recognition System %@Stefan Manke,Michael Finke,Alex Waibel %t1994 %cNIPS %f/NIPS/NIPS-1994-6668.pdf %*Pairwise Neural Network Classifiers with Probabilistic Outputs %@David Price,Stefan Knerr,Léon Personnaz,Gérard Dreyfus %t1994 %cNIPS %f/NIPS/NIPS-1994-6669.pdf %*Interference in Learning Internal Models of Inverse Dynamics in Humans %@Reza Shadmehr,Tom Brashers-Krug,Ferdinando A. Mussa-Ivaldi %t1994 %cNIPS %f/NIPS/NIPS-1994-6670.pdf %*Computational Structure of coordinate transformations: A generalization study %@Zoubin Ghahramani,Daniel M. Wolpert,Michael I. Jordan %t1994 %cNIPS %f/NIPS/NIPS-1994-6671.pdf %*Autoencoders, Minimum Description Length and Helmholtz Free Energy %@Geoffrey E. Hinton,Richard S. Zemel %t1993 %cNIPS %f/NIPS/NIPS-1993-6672.pdf %*Developing Population Codes by Minimizing Description Length %@Richard S. Zemel,Geoffrey E. Hinton %t1993 %cNIPS %f/NIPS/NIPS-1993-6673.pdf %*A Unified Gradient-Descent/Clustering Architecture for Finite State Machine Induction %@Sreerupa Das,Michael C. Mozer %t1993 %cNIPS %f/NIPS/NIPS-1993-6674.pdf %*Fast Pruning Using Principal Components %@Asriel U. Levin,Todd K. Leen,John E. Moody %t1993 %cNIPS %f/NIPS/NIPS-1993-6675.pdf %*Surface Learning with Applications to Lipreading %@Christoph Bregler,Stephen M. Omohundro %t1993 %cNIPS %f/NIPS/NIPS-1993-6676.pdf %*When will a Genetic Algorithm Outperform Hill Climbing %@Melanie Mitchell,John H. Holland,Stephanie Forrest %t1993 %cNIPS %f/NIPS/NIPS-1993-6677.pdf %*Hoeffding Races: Accelerating Model Selection Search for Classification and Function Approximation %@Oded Maron,Andrew W. Moore %t1993 %cNIPS %f/NIPS/NIPS-1993-6678.pdf %*Grammatical Inference by Attentional Control of Synchronization in an Oscillating Elman Network %@Bill Baird,Todd Troyer,Frank Eeckman %t1993 %cNIPS %f/NIPS/NIPS-1993-6679.pdf %*Credit Assignment through Time: Alternatives to Backpropagation %@Yoshua Bengio,Paolo Frasconi %t1993 %cNIPS %f/NIPS/NIPS-1993-6680.pdf %*Structural and Behavioral Evolution of Recurrent Networks %@Gregory M. Saunders,Peter J. Angeline,Jordan B. Pollack %t1993 %cNIPS %f/NIPS/NIPS-1993-6681.pdf %*Clustering with a Domain-Specific Distance Measure %@Steven Gold,Eric Mjolsness,Anand Rangarajan %t1993 %cNIPS %f/NIPS/NIPS-1993-6682.pdf %*Central and Pairwise Data Clustering by Competitive Neural Networks %@Joachim Buhmann,Thomas Hofmann %t1993 %cNIPS %f/NIPS/NIPS-1993-6683.pdf %*Supervised learning from incomplete data via an EM approach %@Zoubin Ghahramani,Michael I. Jordan %t1993 %cNIPS %f/NIPS/NIPS-1993-6684.pdf %*Training Neural Networks with Deficient Data %@Volker Tresp,Subutai Ahmad,Ralph Neuneier %t1993 %cNIPS %f/NIPS/NIPS-1993-6685.pdf %*Unsupervised Parallel Feature Extraction from First Principles %@Mats Österberg,Reiner Lenz %t1993 %cNIPS %f/NIPS/NIPS-1993-6686.pdf %*Fast Non-Linear Dimension Reduction %@Nanda Kambhatla,Todd K. Leen %t1993 %cNIPS %f/NIPS/NIPS-1993-6687.pdf %*Assessing the Quality of Learned Local Models %@Stefan Schaal,Christopher G. Atkeson %t1993 %cNIPS %f/NIPS/NIPS-1993-6688.pdf %*The Power of Amnesia %@Dana Ron,Yoram Singer,Naftali Tishby %t1993 %cNIPS %f/NIPS/NIPS-1993-6689.pdf %*Locally Adaptive Nearest Neighbor Algorithms %@Dietrich Wettschereck,Thomas G. Dietterich %t1993 %cNIPS %f/NIPS/NIPS-1993-6690.pdf %*A Comparison of Dynamic Reposing and Tangent Distance for Drug Activity Prediction %@Thomas G. Dietterich,Ajay N. Jain,Richard H. Lathrop,Tomás Lozano-Pérez %t1993 %cNIPS %f/NIPS/NIPS-1993-6691.pdf %*Combined Neural Networks for Time Series Analysis %@Iris Ginzburg,David Horn %t1993 %cNIPS %f/NIPS/NIPS-1993-6692.pdf %*Backpropagation without Multiplication %@Patrice Y. Simard,Hans Peter Graf %t1993 %cNIPS %f/NIPS/NIPS-1993-6693.pdf %*A Comparative Study of a Modified Bumptree Neural Network with Radial Basis Function Networks and the Standard Multi Layer Perceptron %@Richard T. J. Bostock,Alan J. Harget %t1993 %cNIPS %f/NIPS/NIPS-1993-6694.pdf %*Adaptive knot Placement for Nonparametric Regression %@Hossein L. Najafi,Vladimir Cherkassky %t1993 %cNIPS %f/NIPS/NIPS-1993-6695.pdf %*Optimal Brain Surgeon: Extensions and performance comparisons %@Babak Hassibi,David G. Stork,Gregory Wolff %t1993 %cNIPS %f/NIPS/NIPS-1993-6696.pdf %*Constructive Learning Using Internal Representation Conflicts %@Laurens R. Leerink,Marwan A. Jabri %t1993 %cNIPS %f/NIPS/NIPS-1993-6697.pdf %*Optimal Stopping and Effective Machine Complexity in Learning %@Changfeng Wang,Santosh S. Venkatesh,J. Stephen Judd %t1993 %cNIPS %f/NIPS/NIPS-1993-6698.pdf %*How to Choose an Activation Function %@H. N. Mhaskar,C. A.. Micchelli %t1993 %cNIPS %f/NIPS/NIPS-1993-6699.pdf %*Learning Curves: Asymptotic Values and Rate of Convergence %@Corinna Cortes,L. D. Jackel,Sara A. Solla,Vladimir Vapnik,John S. Denker %t1993 %cNIPS %f/NIPS/NIPS-1993-6700.pdf %*Recovering a Feed-Forward Net From Its Output %@Charles Fefferman,Scott Markel %t1993 %cNIPS %f/NIPS/NIPS-1993-6701.pdf %*Use of Bad Training Data for Better Predictions %@Tal Grossman,Alan Lapedes %t1993 %cNIPS %f/NIPS/NIPS-1993-6702.pdf %*Hoo Optimality Criteria for LMS and Backpropagation %@Babak Hassibi,Ali H. Sayed,Thomas Kailath %t1993 %cNIPS %f/NIPS/NIPS-1993-6703.pdf %*Bounds on the complexity of recurrent neural network implementations of finite state machines %@Bill G. Horne,Don R. Hush %t1993 %cNIPS %f/NIPS/NIPS-1993-6704.pdf %*Backpropagation Convergence Via Deterministic Nonmonotone Perturbed Minimization %@O. L. Mangasarian,M. V. Solodov %t1993 %cNIPS %f/NIPS/NIPS-1993-6705.pdf %*Cross-Validation Estimates IMSE %@Mark Plutowski,Shinichi Sakata,Halbert White %t1993 %cNIPS %f/NIPS/NIPS-1993-6706.pdf %*Discontinuous Generalization in Large Committee Machines %@H. Schwarze,J. Hertz %t1993 %cNIPS %f/NIPS/NIPS-1993-6707.pdf %*Non-Linear Statistical Analysis and Self-Organizing Hebbian Networks %@Jonathan L. Shapiro,Adam Prügel-Bennett %t1993 %cNIPS %f/NIPS/NIPS-1993-6708.pdf %*Structured Machine Learning for 'Soft' Classification with Smoothing Spline ANOVA and Stacked Tuning, Testing and Evaluation %@Grace Wahba,Yuedong Wang,Chong Gu,Ronald Klein, MD,Barbara Klein, MD %t1993 %cNIPS %f/NIPS/NIPS-1993-6709.pdf %*The Statistical Mechanics of k-Satisfaction %@Scott Kirkpatrick,Géza Györgyi,Naftali Tishby,Lidror Troyansky %t1993 %cNIPS %f/NIPS/NIPS-1993-6710.pdf %*Coupled Dynamics of Fast Neurons and Slow Interactions %@A.C.C. Coolen,R. W. Penney,D. Sherrington %t1993 %cNIPS %f/NIPS/NIPS-1993-6711.pdf %*Observability of Neural Network Behavior %@Max Garzon,Fernanda Botelho %t1993 %cNIPS %f/NIPS/NIPS-1993-6712.pdf %*How to Describe Neuronal Activity: Spikes, Rates, or Assemblies? %@Wulfram Gerstner,J. Leo van Hemmen %t1993 %cNIPS %f/NIPS/NIPS-1993-6713.pdf %*Correlation Functions in a Large Stochastic Neural Network %@Iris Ginzburg,Haim Sompolinsky %t1993 %cNIPS %f/NIPS/NIPS-1993-6714.pdf %*Optimal Stochastic Search and Adaptive Momentum %@Todd K. Leen,Genevieve B. Orr %t1993 %cNIPS %f/NIPS/NIPS-1993-6715.pdf %*Optimal Signalling in Attractor Neural Networks %@Isaac Meilijson,Eytan Ruppin %t1993 %cNIPS %f/NIPS/NIPS-1993-6716.pdf %*Asynchronous Dynamics of Continuous Time Neural Networks %@Xin Wang,Qingnan Li,Edward K. Blum %t1993 %cNIPS %f/NIPS/NIPS-1993-6717.pdf %*Amplifying and Linearizing Apical Synaptic Inputs to Cortical Pyramidal Cells %@Öjvind Bernander,Christof Koch,Rodney J. Douglas %t1993 %cNIPS %f/NIPS/NIPS-1993-6718.pdf %*Odor Processing in the Bee: A Preliminary Study of the Role of Central Input to the Antennal Lobe %@Christiane Linster,David Marsan,Claudine Masson,Michel Kerszberg %t1993 %cNIPS %f/NIPS/NIPS-1993-6719.pdf %*Lower Boundaries of Motoneuron Desynchronization via Renshaw Interneurons %@Mitchell Gil Maltenfort,Robert E. Druzinsky,C. J. Heckman,W. Zev Rymer %t1993 %cNIPS %f/NIPS/NIPS-1993-6720.pdf %*Development of Orientation and Ocular Dominance Columns in Infant Macaques %@Klaus Obermayer,Lynne Kiorpes,Gary G. Blasdel %t1993 %cNIPS %f/NIPS/NIPS-1993-6721.pdf %*Statistics of Natural Images: Scaling in the Woods %@Daniel L. Ruderman,William Bialek %t1993 %cNIPS %f/NIPS/NIPS-1993-6722.pdf %*Dopaminergic Neuromodulation Brings a Dynamical Plasticity to the Retina %@Eric Boussard,Jean-François Vibert %t1993 %cNIPS %f/NIPS/NIPS-1993-6723.pdf %*A Hodgkin-Huxley Type Neuron Model That Learns Slow Non-Spike Oscillation %@Kenji Doya,Allen I. Selverston,Peter F. Rowat %t1993 %cNIPS %f/NIPS/NIPS-1993-6724.pdf %*Directional Hearing by the Mauthner System %@Audrey L. Guzik,Robert C. Eaton %t1993 %cNIPS %f/NIPS/NIPS-1993-6725.pdf %*An Analog VLSI Saccadic Eye Movement System %@Timothy K. Horiuchi,Brooks Bishofberger,Christof Koch %t1993 %cNIPS %f/NIPS/NIPS-1993-6726.pdf %*Foraging in an Uncertain Environment Using Predictive Hebbian Learning %@P. Read Montague,Peter Dayan,Terrence J. Sejnowski %t1993 %cNIPS %f/NIPS/NIPS-1993-6727.pdf %*A Connectionist Model of the Owl's Sound Localization System %@Daniel J. Rosen,David E. Rumelhart,Eric I. Knudsen %t1993 %cNIPS %f/NIPS/NIPS-1993-6728.pdf %*Synchronization, oscillations, and 1/f noise in networks of spiking neurons %@Martin Stemmler,Marius Usher,Christof Koch,Zeev Olami %t1993 %cNIPS %f/NIPS/NIPS-1993-6729.pdf %*Transition Point Dynamic Programming %@Kenneth M. Buckland,Peter D. Lawrence %t1993 %cNIPS %f/NIPS/NIPS-1993-6730.pdf %*Exploiting Chaos to Control the Future %@Gary W. Flake,Guo-Zhen Sun,Yee-Chun Lee %t1993 %cNIPS %f/NIPS/NIPS-1993-6731.pdf %*Robust Reinforcement Learning in Motion Planning %@Satinder P. Singh,Andrew G. Barto,Roderic Grupen,Christopher Connolly %t1993 %cNIPS %f/NIPS/NIPS-1993-6732.pdf %*Packet Routing in Dynamically Changing Networks: A Reinforcement Learning Approach %@Justin A. Boyan,Michael L. Littman %t1993 %cNIPS %f/NIPS/NIPS-1993-6733.pdf %*Monte Carlo Matrix Inversion and Reinforcement Learning %@Andrew Barto,Michael Duff %t1993 %cNIPS %f/NIPS/NIPS-1993-6734.pdf %*Convergence of Indirect Adaptive Asynchronous Value Iteration Algorithms %@Vijaykumar Gullapalli,Andrew G. Barto %t1993 %cNIPS %f/NIPS/NIPS-1993-6735.pdf %*Convergence of Stochastic Iterative Dynamic Programming Algorithms %@Tommi Jaakkola,Michael I. Jordan,Satinder P. Singh %t1993 %cNIPS %f/NIPS/NIPS-1993-6736.pdf %*Mixtures of Controllers for Jump Linear and Non-Linear Plants %@Timothy W. Cacciatore,Steven J. Nowlan %t1993 %cNIPS %f/NIPS/NIPS-1993-6737.pdf %*A Computational Model for Cursive Handwriting Based on the Minimization Principle %@Yasuhiro Wada,Yasuharu Koike,Eric Vatikiotis-Bateson,Mitsuo Kawato %t1993 %cNIPS %f/NIPS/NIPS-1993-6738.pdf %*Signature Verification using a "Siamese" Time Delay Neural Network %@Jane Bromley,Isabelle Guyon,Yann LeCun,Eduard Säckinger,Roopak Shah %t1993 %cNIPS %f/NIPS/NIPS-1993-6739.pdf %*Postal Address Block Location Using a Convolutional Locator Network %@Ralph Wolf,John C. Platt %t1993 %cNIPS %f/NIPS/NIPS-1993-6740.pdf %*Non-Intrusive Gaze Tracking Using Artificial Neural Networks %@Shumeet Baluja,Dean Pomerleau %t1993 %cNIPS %f/NIPS/NIPS-1993-6741.pdf %*Hidden Markov Models for Human Genes %@Pierre Baldi,Søren Brunak,Yves Chauvin,Jacob Engelbrecht,Anders Krogh %t1993 %cNIPS %f/NIPS/NIPS-1993-6742.pdf %*Illumination-Invariant Face Recognition with a Contrast Sensitive Silicon Retina %@Joachim M. Buhmann,Martin Lades,Frank Eeckman %t1993 %cNIPS %f/NIPS/NIPS-1993-6743.pdf %*Address Block Location with a Neural Net System %@Hans Peter Graf,Eric Cosatto %t1993 %cNIPS %f/NIPS/NIPS-1993-6744.pdf %*Comparison Training for a Rescheduling Problem in Neural Networks %@Didier Keymeulen,Martine de Gerlache %t1993 %cNIPS %f/NIPS/NIPS-1993-6745.pdf %*Neural Network Definitions of Highly Predictable Protein Secondary Structure Classes %@Alan Lapedes,Evan Steeg,Robert Farber %t1993 %cNIPS %f/NIPS/NIPS-1993-6746.pdf %*Temporal Difference Learning of Position Evaluation in the Game of Go %@Nicol N. Schraudolph,Peter Dayan,Terrence J. Sejnowski %t1993 %cNIPS %f/NIPS/NIPS-1993-6747.pdf %*Decoding Cursive Scripts %@Yoram Singer,Naftali Tishby %t1993 %cNIPS %f/NIPS/NIPS-1993-6748.pdf %*A Massively-Parallel SIMD Processor for Neural Network and Machine Vision Applications %@Michael A. Glover,W. Thomas Miller III %t1993 %cNIPS %f/NIPS/NIPS-1993-6749.pdf %*A Hybrid Radial Basis Function Neurocomputer and Its Applications %@Steven S. Watkins,Paul M. Chau,Raoul Tawel,Bjorn Lambrigtsen,Mark Plutowski %t1993 %cNIPS %f/NIPS/NIPS-1993-6750.pdf %*VLSI Phase Locking Architectures for Feature Linking in Multiple Target Tracking Systems %@Andreas G. Andreou,Thomas G. Edwards %t1993 %cNIPS %f/NIPS/NIPS-1993-6751.pdf %*WATTLE: A Trainable Gain Analogue VLSI Neural Network %@Richard Coggins,Marwan Jabri %t1993 %cNIPS %f/NIPS/NIPS-1993-6752.pdf %*The "Softmax" Nonlinearity: Derivation Using Statistical Mechanics and Useful Properties as a Multiterminal Analog Circuit Element %@I. M. Elfadel,J. L. Wyatt, Jr. %t1993 %cNIPS %f/NIPS/NIPS-1993-6753.pdf %*High Performance Neural Net Simulation on a Multiprocessor System with "Intelligent" Communication %@Urs A. Müller,Michael Kocheisen,Anton Gunzinger %t1993 %cNIPS %f/NIPS/NIPS-1993-6754.pdf %*Digital Boltzmann VLSI for constraint satisfaction and learning %@Michael Murray,Ming-Tak Leung,Kan Boonyanit,Kong Kritayakirana,James B. Burg,Gregory J. Wolff,Tokahiro Watanabe,Edward Schwartz,David G. Stork,Allen M. Peterson %t1993 %cNIPS %f/NIPS/NIPS-1993-6755.pdf %*Efficient Simulation of Biological Neural Networks on Massively Parallel Supercomputers with Hypercube Architecture %@Ernst Niebur,Dean Brettle %t1993 %cNIPS %f/NIPS/NIPS-1993-6756.pdf %*Learning Complex Boolean Functions: Algorithms and Applications %@Arlindo L. Oliveira,Alberto Sangiovanni-Vincentelli %t1993 %cNIPS %f/NIPS/NIPS-1993-6757.pdf %*Implementing Intelligence on Silicon Using Neuron-Like Functional MOS Transistors %@Tadashi Shibata,Koji Kotani,Takeo Yamashita,Hiroshi Ishii,Hideo Kosaka,Tadahiro Ohmi %t1993 %cNIPS %f/NIPS/NIPS-1993-6758.pdf %*Globally Trained Handwritten Word Recognizer using Spatial Representation, Convolutional Neural Networks, and Hidden Markov Models %@Yoshua Bengio,Yann LeCun,Donnie Henderson %t1993 %cNIPS %f/NIPS/NIPS-1993-6759.pdf %*Classifying Hand Gestures with a View-Based Distributed Representation %@Trevor J. Darrell,Alex P. Pentland %t1993 %cNIPS %f/NIPS/NIPS-1993-6760.pdf %*A Network Mechanism for the Determination of Shape-From-Texture %@Kô Sakai,Leif H. Finkel %t1993 %cNIPS %f/NIPS/NIPS-1993-6761.pdf %*The Role of MT Neuron Receptive Field Surrounds in Computing Object Shape from Velocity Fields %@G. T. Buracas,T. D. Albright %t1993 %cNIPS %f/NIPS/NIPS-1993-6762.pdf %*Resolving motion ambiguities %@K. I. Diamantaras,D. Geiger %t1993 %cNIPS %f/NIPS/NIPS-1993-6763.pdf %*Two-Dimensional Object Localization by Coarse-to-Fine Correlation Matching %@Chien-Ping Lu,Eric Mjolsness %t1993 %cNIPS %f/NIPS/NIPS-1993-6764.pdf %*Dual Mechanisms for Neural Binding and Segmentation %@Paul Sajda,Leif H. Finkel %t1993 %cNIPS %f/NIPS/NIPS-1993-6765.pdf %*Bayesian Self-Organization %@Alan L. Yuille,Stelios M. Smirnakis,Lei Xu %t1993 %cNIPS %f/NIPS/NIPS-1993-6766.pdf %*Analysis of Short Term Memories for Neural Networks %@Jose C. Principe,Hui-H. Hsu,Jyh-Ming Kuo %t1993 %cNIPS %f/NIPS/NIPS-1993-6767.pdf %*Figure of Merit Training for Detection and Spotting %@Eric I. Chang,Richard P. Lippmann %t1993 %cNIPS %f/NIPS/NIPS-1993-6768.pdf %*Lipreading by neural networks: Visual preprocessing, learning, and sensory integration %@Gregory J. Wolff,K. Venkatesh Prasad,David G. Stork,Marcus Hennecke %t1993 %cNIPS %f/NIPS/NIPS-1993-6769.pdf %*Speaker Recognition Using Neural Tree Networks %@Kevin R. Farrell,Richard J. Mammone %t1993 %cNIPS %f/NIPS/NIPS-1993-6770.pdf %*Inverse Dynamics of Speech Motor Control %@Makoto Hirayama,Eric Vatikiotis-Bateson,Mitsuo Kawato %t1993 %cNIPS %f/NIPS/NIPS-1993-6771.pdf %*Learning Temporal Dependencies in Connectionist Speech Recognition %@Steve Renals,Mike Hochberg,Tony Robinson %t1993 %cNIPS %f/NIPS/NIPS-1993-6772.pdf %*Segmental Neural Net Optimization for Continuous Speech Recognition %@Ying Zhao,Richard Schwartz,John Makhoul,George Zavaliagkos %t1993 %cNIPS %f/NIPS/NIPS-1993-6773.pdf %*Computational Elements of the Adaptive Controller of the Human Arm %@Reza Shadmehr,Ferdinando A. Mussa-Ivaldi %t1993 %cNIPS %f/NIPS/NIPS-1993-6774.pdf %*Tonal Music as a Componential Code: Learning Temporal Relationships Between and Within Pitch and Timing Components %@Catherine Stevens,Janet Wiles %t1993 %cNIPS %f/NIPS/NIPS-1993-6775.pdf %*Emergence of Global Structure from Local Associations %@Thea B. Ghiselli-Crippa,Paul W. Munro %t1993 %cNIPS %f/NIPS/NIPS-1993-6776.pdf %*Analyzing Cross-Connected Networks %@Thomas R. Shultz,Jeffrey L. Elman %t1993 %cNIPS %f/NIPS/NIPS-1993-6777.pdf %*Learning Mackey-Glass from 25 examples, Plus or Minus 2 %@Mark Plutowski,Garrison Cottrell,Halbert White %t1993 %cNIPS %f/NIPS/NIPS-1993-6778.pdf %*Classification of Electroencephalogram using Artificial Neural Networks %@A C Tsoi,D S C So,A Sergejew %t1993 %cNIPS %f/NIPS/NIPS-1993-6779.pdf %*Complexity Issues in Neural Computation and Learning %@V. P. Roychowdhury,K.-Y. Siu %t1993 %cNIPS %f/NIPS/NIPS-1993-6780.pdf %*Memory-Based Methods for Regression and Classification %@Thomas G. Dietterich,Dietrich Wettschereck,Chris G. Atkeson,Andrew W. Moore %t1993 %cNIPS %f/NIPS/NIPS-1993-6781.pdf %*Neurobiology, Psychophysics, and Computational Models of Visual Attention %@Ernst Niebur,Bruno A. Olshausen %t1993 %cNIPS %f/NIPS/NIPS-1993-6782.pdf %*Stability and Observability %@Max H. Garzon,Fernanda Botelho %t1993 %cNIPS %f/NIPS/NIPS-1993-6783.pdf %*Connectionist Modeling and Parallel Architectures %@Joachim Diederich,Ah Chung Tsoi %t1993 %cNIPS %f/NIPS/NIPS-1993-6784.pdf %*Processing of Visual and Auditory Space and Its Modification by Experience %@Josef P. Rauschecker,Terrence J. Sejnowski %t1993 %cNIPS %f/NIPS/NIPS-1993-6785.pdf %*Hidden Markov Model Induction by Bayesian Model Merging %@Andreas Stolcke,Stephen Omohundro %t1992 %cNIPS %f/NIPS/NIPS-1992-6786.pdf %*Computing with Almost Optimal Size Neural Networks %@Kai-Yeung Siu,Vwani Roychowdhury,Thomas Kailath %t1992 %cNIPS %f/NIPS/NIPS-1992-6787.pdf %*Intersecting regions: The Key to combinatorial structure in hidden unit space %@Janet Wiles,Mark Ollila %t1992 %cNIPS %f/NIPS/NIPS-1992-6788.pdf %*Improving Performance in Neural Networks Using a Boosting Algorithm %@Harris Drucker,Robert Schapire,Patrice Simard %t1992 %cNIPS %f/NIPS/NIPS-1992-6789.pdf %*Efficient Pattern Recognition Using a New Transformation Distance %@Patrice Simard,Yann LeCun,John S. Denker %t1992 %cNIPS %f/NIPS/NIPS-1992-6790.pdf %*Optimal Depth Neural Networks for Multiplication and Related Problems %@Kai-Yeung Siu,Vwani Roychowdhury %t1992 %cNIPS %f/NIPS/NIPS-1992-6791.pdf %*Using Prior Knowledge in a NNPDA to Learn Context-Free Languages %@Sreerupa Das,C. Lee Giles,Guo-Zheng Sun %t1992 %cNIPS %f/NIPS/NIPS-1992-6792.pdf %*Nets with Unreliable Hidden Nodes Learn Error-Correcting Codes %@Stephen Judd,Paul W. Munro %t1992 %cNIPS %f/NIPS/NIPS-1992-6793.pdf %*Combining Neural and Symbolic Learning to Revise Probabilistic Rule Bases %@J. Jeffrey Mahoney,Raymond J. Mooney %t1992 %cNIPS %f/NIPS/NIPS-1992-6794.pdf %*Metamorphosis Networks: An Alternative to Constructive Models %@Brian V. Bonnlander,Michael C. Mozer %t1992 %cNIPS %f/NIPS/NIPS-1992-6795.pdf %*A Boundary Hunting Radial Basis Function Classifier which Allocates Centers Constructively %@Eric I. Chang,Richard P. Lippmann %t1992 %cNIPS %f/NIPS/NIPS-1992-6796.pdf %*Automatic Capacity Tuning of Very Large VC-Dimension Classifiers %@I. Guyon,B. Boser,V. Vapnik %t1992 %cNIPS %f/NIPS/NIPS-1992-6797.pdf %*Automatic Learning Rate Maximization by On-Line Estimation of the Hessian's Eigenvectors %@Yann LeCun,Patrice Y. Simard,Barak Pearlmutter %t1992 %cNIPS %f/NIPS/NIPS-1992-6798.pdf %*Second order derivatives for network pruning: Optimal Brain Surgeon %@Babak Hassibi,David G. Stork %t1992 %cNIPS %f/NIPS/NIPS-1992-6799.pdf %*Directional-Unit Boltzmann Machines %@Richard S. Zemel,Christopher K. I. Williams,Michael C. Mozer %t1992 %cNIPS %f/NIPS/NIPS-1992-6800.pdf %*Time Warping Invariant Neural Networks %@Guo-Zheng Sun,Hsing-Hen Chen,Yee-Chun Lee %t1992 %cNIPS %f/NIPS/NIPS-1992-6801.pdf %*Generalization Abilities of Cascade Network Architecture %@E. Littmann,H. Ritter %t1992 %cNIPS %f/NIPS/NIPS-1992-6802.pdf %*Summed Weight Neuron Perturbation: An O(N) Improvement Over Weight Perturbation %@Barry Flower,Marwan Jabri %t1992 %cNIPS %f/NIPS/NIPS-1992-6803.pdf %*A Note on Learning Vector Quantization %@Virginia R. de Sa,Dana H. Ballard %t1992 %cNIPS %f/NIPS/NIPS-1992-6804.pdf %*Extended Regularization Methods for Nonconvergent Model Selection %@W. Finnoff,F. Hergert,H. G. Zimmermann %t1992 %cNIPS %f/NIPS/NIPS-1992-6805.pdf %*Synchronization and Grammatical Inference in an Oscillating Elman Net %@Bill Baird,Todd Troyer,Frank Eeckman %t1992 %cNIPS %f/NIPS/NIPS-1992-6806.pdf %*Global Regularization of Inverse Kinematics for Redundant Manipulators %@David DeMers,Kenneth Kreutz-Delgado %t1992 %cNIPS %f/NIPS/NIPS-1992-6807.pdf %*Memory-Based Reinforcement Learning: Efficient Computation with Prioritized Sweeping %@Andrew W. Moore,Christopher G. Atkeson %t1992 %cNIPS %f/NIPS/NIPS-1992-6808.pdf %*Feudal Reinforcement Learning %@Peter Dayan,Geoffrey E. Hinton %t1992 %cNIPS %f/NIPS/NIPS-1992-6809.pdf %*Explanation-Based Neural Network Learning for Robot Control %@Tom M. Mitchell,Sebastian B. Thrun %t1992 %cNIPS %f/NIPS/NIPS-1992-6810.pdf %*Integration of Visual and Somatosensory Information for Preshaping Hand in Grasping Movements %@Yoji Uno,Naohiro Fukumura,Ryoji Suzuki,Mitsuo Kawato %t1992 %cNIPS %f/NIPS/NIPS-1992-6811.pdf %*Learning Spatio-Temporal Planning from a Dynamic Programming Teacher: Feed-Forward Neurocontrol for Moving Obstacle Avoidance %@Gerald Fahner,Rolf Eckmiller %t1992 %cNIPS %f/NIPS/NIPS-1992-6812.pdf %*Learning Fuzzy Rule-Based Neural Networks for Control %@Charles M. Higgins,Rodney M. Goodman %t1992 %cNIPS %f/NIPS/NIPS-1992-6813.pdf %*Filter Selection Model for Generating Visual Motion Signals %@Steven J. Nowlan,Terrence J. Sejnowski %t1992 %cNIPS %f/NIPS/NIPS-1992-6814.pdf %*Stimulus Encoding by Multidimensional Receptive Fields in Single Cells and Cell Populations in V1 of Awake Monkey %@Edward Stern,Ad Aertsen,Eilon Vaadia,Shaul Hochstein %t1992 %cNIPS %f/NIPS/NIPS-1992-6815.pdf %*The Computation of Stereo Disparity for Transparent and for Opaque Surfaces %@Suthep Madarasmi,Daniel Kersten,Ting-Chuen Pong %t1992 %cNIPS %f/NIPS/NIPS-1992-6816.pdf %*Some Solutions to the Missing Feature Problem in Vision %@Subutai Ahmad,Volker Tresp %t1992 %cNIPS %f/NIPS/NIPS-1992-6817.pdf %*Improving Convergence in Hierarchical Matching Networks for Object Recognition %@Joachim Utans,Gene Gindi %t1992 %cNIPS %f/NIPS/NIPS-1992-6818.pdf %*Unsmearing Visual Motion: Development of Long-Range Horizontal Intrinsic Connections %@Kevin E. Martin,Jonathan A. Marshall %t1992 %cNIPS %f/NIPS/NIPS-1992-6819.pdf %*Remote Sensing Image Analysis via a Texture Classification Neural Network %@Hayit K. Greenspan,Rodney Goodman %t1992 %cNIPS %f/NIPS/NIPS-1992-6820.pdf %*Computation of Heading Direction from Optic Flow in Visual Cortex %@Markus Lappe,Josef P. Rauschecker %t1992 %cNIPS %f/NIPS/NIPS-1992-6821.pdf %*Learning to See Where and What: Training a Net to Make Saccades and Recognize Handwritten Characters %@Gale Martin,Mosfeq Rashid,David Chapman,James A. Pittman %t1992 %cNIPS %f/NIPS/NIPS-1992-6822.pdf %*Weight Space Probability Densities in Stochastic Learning: I. Dynamics and Equilibria %@Todd K. Leen,John E. Moody %t1992 %cNIPS %f/NIPS/NIPS-1992-6823.pdf %*Self-Organizing Rules for Robust Principal Component Analysis %@Lei Xu,Alan L. Yuille %t1992 %cNIPS %f/NIPS/NIPS-1992-6824.pdf %*Information, Prediction, and Query by Committee %@Yoav Freund,H. Sebastian Seung,Eli Shamir,Naftali Tishby %t1992 %cNIPS %f/NIPS/NIPS-1992-6825.pdf %*Synaptic Weight Noise During MLP Learning Enhances Fault-Tolerance, Generalization and Learning Trajectory %@Alan F. Murray,Peter J. Edwards %t1992 %cNIPS %f/NIPS/NIPS-1992-6826.pdf %*Unsupervised Discrimination of Clustered Data via Optimization of Binary Information Gain %@Nicol N. Schraudolph,Terrence J. Sejnowski %t1992 %cNIPS %f/NIPS/NIPS-1992-6827.pdf %*Weight Space Probability Densities in Stochastic Learning: II. Transients and Basin Hopping Times %@Genevieve B. Orr,Todd K. Leen %t1992 %cNIPS %f/NIPS/NIPS-1992-6828.pdf %*Information Theoretic Analysis of Connection Structure from Spike Trains %@Satoru Shiono,Satoshi Yamada,Michio Nakashima,Kenji Matsumoto %t1992 %cNIPS %f/NIPS/NIPS-1992-6829.pdf %*Statistical Mechanics of Learning in a Large Committee Machine %@Holm Schwarze,John A. Hertz %t1992 %cNIPS %f/NIPS/NIPS-1992-6830.pdf %*Probability Estimation from a Database Using a Gibbs Energy Model %@John W. Miller,Rodney M. Goodman %t1992 %cNIPS %f/NIPS/NIPS-1992-6831.pdf %*Destabilization and Route to Chaos in Neural Networks with Random Connectivity %@Bernard Doyon,Bruno Cessac,Mathias Quoy,Manuel Samuelides %t1992 %cNIPS %f/NIPS/NIPS-1992-6832.pdf %*Predicting Complex Behavior in Sparse Asymmetric Networks %@Ali A. Minai,William B. Levy %t1992 %cNIPS %f/NIPS/NIPS-1992-6833.pdf %*Single-Iteration Threshold Hamming Networks %@Isaac Meilijson,Eytan Ruppin,Moshe Sipper %t1992 %cNIPS %f/NIPS/NIPS-1992-6834.pdf %*History-Dependent Attractor Neural Networks %@Isaac Meilijson,Eytan Ruppin %t1992 %cNIPS %f/NIPS/NIPS-1992-6835.pdf %*Non-Linear Dimensionality Reduction %@David DeMers,Garrison W. Cottrell %t1992 %cNIPS %f/NIPS/NIPS-1992-6836.pdf %*On Learning µ-Perceptron Networks with Binary Weights %@Mostefa Golea,Mario Marchand,Thomas R. Hancock %t1992 %cNIPS %f/NIPS/NIPS-1992-6837.pdf %*Learning Curves, Model Selection and Complexity of Neural Networks %@Noboru Murata,Shuji Yoshizawa,Shun-ichi Amari %t1992 %cNIPS %f/NIPS/NIPS-1992-6838.pdf %*The Power of Approximating: a Comparison of Activation Functions %@Bhaskar DasGupta,Georg Schnitger %t1992 %cNIPS %f/NIPS/NIPS-1992-6839.pdf %*Rational Parametrizations of Neural Networks %@Uwe Helmke,Robert C. Williamson %t1992 %cNIPS %f/NIPS/NIPS-1992-6840.pdf %*Learning Cellular Automaton Dynamics with Neural Networks %@N. H. Wulff,J A. Hertz %t1992 %cNIPS %f/NIPS/NIPS-1992-6841.pdf %*Context-Dependent Multiple Distribution Phonetic Modeling with MLPs %@Michael Cohen,Horacio Franco,Nelson Morgan,David E. Rumelhart,Victor Abrash %t1992 %cNIPS %f/NIPS/NIPS-1992-6842.pdf %*Physiologically Based Speech Synthesis %@Makoto Hirayama,Eric Vatikiotis-Bateson,Kiyoshi Honda,Yasuharu Koike,Mitsuo Kawato %t1992 %cNIPS %f/NIPS/NIPS-1992-6843.pdf %*Analog Cochlear Model for Multiresolution Speech Analysis %@Weimin Liu,Andreas G. Andreou,Moise H. Goldstein Jr. %t1992 %cNIPS %f/NIPS/NIPS-1992-6844.pdf %*A Hybrid Linear/Nonlinear Approach to Channel Equalization Problems %@Wei-Tsih Lee,John Pearson %t1992 %cNIPS %f/NIPS/NIPS-1992-6845.pdf %*Modeling Consistency in a Speaker Independent Continuous Speech Recognition System %@Yochai Konig,Nelson Morgan,Chuck Wooters,Victor Abrash,Michael Cohen,Horacio Franco %t1992 %cNIPS %f/NIPS/NIPS-1992-6846.pdf %*Transient Signal Detection with Neural Networks: The Search for the Desired Signal %@José Carlos Príncipe,Abir Zahalka %t1992 %cNIPS %f/NIPS/NIPS-1992-6847.pdf %*Performance Through Consistency: MS-TDNN's for Large Vocabulary Continuous Speech Recognition %@Joe Tebelskis,Alex Waibel %t1992 %cNIPS %f/NIPS/NIPS-1992-6848.pdf %*A Hybrid Neural Net System for State-of-the-Art Continuous Speech Recognition %@G. Zavaliagkos,Y. Zhao,R. Schwartz,J. Makhoul %t1992 %cNIPS %f/NIPS/NIPS-1992-6849.pdf %*Connected Letter Recognition with a Multi-State Time Delay Neural Network %@Hermann Hild,Alex Waibel %t1992 %cNIPS %f/NIPS/NIPS-1992-6850.pdf %*Recognition-based Segmentation of On-Line Hand-printed Words %@M. Schenkel,H. Weissman,I. Guyon,C. Nohl,D. Henderson %t1992 %cNIPS %f/NIPS/NIPS-1992-6851.pdf %*Planar Hidden Markov Modeling: From Speech to Optical Character Recognition %@Esther Levin,Roberto Pieraccini %t1992 %cNIPS %f/NIPS/NIPS-1992-6852.pdf %*Forecasting Demand for Electric Power %@Jen-Lun Yuan,Terrence Fine %t1992 %cNIPS %f/NIPS/NIPS-1992-6853.pdf %*Hidden Markov Models in Molecular Biology: New Algorithms and Applications %@Pierre Baldi,Yves Chauvin,Tim Hunkapiller,Marcella A. McClure %t1992 %cNIPS %f/NIPS/NIPS-1992-6854.pdf %*A Neural Network that Learns to Interpret Myocardial Planar Thallium Scintigrams %@Charles Rosenberg,Jacob Erel,Henri Atlan %t1992 %cNIPS %f/NIPS/NIPS-1992-6855.pdf %*An Analog VLSI Chip for Radial Basis Functions %@Janeen Anderson,John C. Platt,David B. Kirk %t1992 %cNIPS %f/NIPS/NIPS-1992-6856.pdf %*Generic Analog Neural Computation - The EPSILON Chip %@Stephen Churcher,Donald J. Baxter,Alister Hamilton,Alan F. Murray,H. Martin Reekie %t1992 %cNIPS %f/NIPS/NIPS-1992-6857.pdf %*Visual Motion Computation in Analog VLSI Using Pulses %@Rahul Sarpeshkar,Wyeth Bair,Christof Koch %t1992 %cNIPS %f/NIPS/NIPS-1992-6858.pdf %*Analog VLSI Implementation of Multi-dimensional Gradient Descent %@David B. Kirk,Douglas Kerns,Kurt Fleischer,Alan H. Barr %t1992 %cNIPS %f/NIPS/NIPS-1992-6859.pdf %*An Object-Oriented Framework for the Simulation of Neural Nets %@A. Linden,Th. Sudbrak,Ch. Tietz,F. Weber %t1992 %cNIPS %f/NIPS/NIPS-1992-6860.pdf %*Attractor Neural Networks with Local Inhibition: from Statistical Physics to a Digitial Programmable Integrated Circuit %@E. Pasero,R. Zecchina %t1992 %cNIPS %f/NIPS/NIPS-1992-6861.pdf %*Hybrid Circuits of Interacting Computer Model and Biological Neurons %@Sylvie Renaud-Le Masson,Gwendal Le Masson,Eve Marder,L. F. Abbott %t1992 %cNIPS %f/NIPS/NIPS-1992-6862.pdf %*Silicon Auditory Processors as Computer Peripherals %@John Lazzaro,John Wawrzynek,M. Mahowald,Massimo Sivilotti,Dave Gillespie %t1992 %cNIPS %f/NIPS/NIPS-1992-6863.pdf %*Object-Based Analog VLSI Vision Circuits %@Christof Koch,Binnal Mathur,Shih-Chii Liu,John G. Harris,Jin Luo,Massimo Sivilotti %t1992 %cNIPS %f/NIPS/NIPS-1992-6864.pdf %*A Parallel Gradient Descent Method for Learning in Analog VLSI Neural Networks %@J. Alspector,R. Meir,B. Yuhas,A. Jayakumar,D. Lippe %t1992 %cNIPS %f/NIPS/NIPS-1992-6865.pdf %*Analogy-- Watershed or Waterloo? Structural alignment and the development of connectionist models of analogy %@Dedre Gentner,Arthur B. Markman %t1992 %cNIPS %f/NIPS/NIPS-1992-6866.pdf %*A Connectionist Symbol Manipulator That Discovers the Structure of Context-Free Languages %@Michael C. Mozer,Sreerupa Das %t1992 %cNIPS %f/NIPS/NIPS-1992-6867.pdf %*Network Structuring and Training Using Rule-based Knowledge %@Volker Tresp,Jürgen Hollatz,Subutai Ahmad %t1992 %cNIPS %f/NIPS/NIPS-1992-6868.pdf %*A dynamical model of priming and repetition blindness %@Daphne Bavelier,Michael I. Jordan %t1992 %cNIPS %f/NIPS/NIPS-1992-6869.pdf %*A Knowledge-Based Model of Geometry Learning %@Geoffrey Towell,Richard Lehrer %t1992 %cNIPS %f/NIPS/NIPS-1992-6870.pdf %*Mapping Between Neural and Physical Activities of the Lobster Gastric Mill %@Kenji Doya,Mary E. T. Boyle,Allen I. Selverston %t1992 %cNIPS %f/NIPS/NIPS-1992-6871.pdf %*Using hippocampal 'place cells' for navigation, exploiting phase coding %@Neil Burgess,John O'Keefe,Michael Recce %t1992 %cNIPS %f/NIPS/NIPS-1992-6872.pdf %*Adaptive Stimulus Representations: A Computational Theory of Hippocampal-Region Function %@Mark A. Gluck,Catherine E. Myers %t1992 %cNIPS %f/NIPS/NIPS-1992-6873.pdf %*Statistical Modeling of Cell Assemblies Activities in Associative Cortex of Behaving Monkeys %@Itay Gat,Naftali Tishby %t1992 %cNIPS %f/NIPS/NIPS-1992-6874.pdf %*Biologically Plausible Local Learning Rules for the Adaptation of the Vestibulo-Ocular Reflex %@Olivier Coenen,Terrence J. Sejnowski,Stephen G. Lisberger %t1992 %cNIPS %f/NIPS/NIPS-1992-6875.pdf %*Using Aperiodic Reinforcement for Directed Self-Organization During Development %@P. R. Montague,P. Dayan,S.J. Nowlan,A Pouget,T.J. Sejnowski %t1992 %cNIPS %f/NIPS/NIPS-1992-6876.pdf %*How Oscillatory Neuronal Responses Reflect Bistability and Switching of the Hidden Assembly Dynamics %@K. Pawelzik,H.-U. Bauer,J. Deppisch,T. Geisel %t1992 %cNIPS %f/NIPS/NIPS-1992-6877.pdf %*Statistical and Dynamical Interpretation of ISIH Data from Periodically Stimulated Sensory Neurons %@John K. Douglass,Frank Moss,André Longtin %t1992 %cNIPS %f/NIPS/NIPS-1992-6878.pdf %*Spiral Waves in Integrate-and-Fire Neural Networks %@John G. Milton,Po Hsiang Chu,Jack D. Cowan %t1992 %cNIPS %f/NIPS/NIPS-1992-6879.pdf %*Parameterising Feature Sensitive Cell Formation in Linsker Networks in the Auditory System %@Lance C. Walton,David L. Bisset %t1992 %cNIPS %f/NIPS/NIPS-1992-6880.pdf %*A Formal Model of the Insect Olfactory Macroglomerulus: Simulations and Analytic Results %@Christiane Linster,David Marsan,Claudine Masson,Michel Kerszberg,Gérard Dreyfus,Léon Personnaz %t1992 %cNIPS %f/NIPS/NIPS-1992-6881.pdf %*An Information-Theoretic Approach to Deciphering the Hippocampal Code %@William E. Skaggs,Bruce L. McNaughton,Katalin M. Gothard %t1992 %cNIPS %f/NIPS/NIPS-1992-6882.pdf %*Models Wanted: Must Fit Dimensions of Sleep and Dreaming %@J. Allan Hobson,Adam N. Mamelak,Jeffrey P. Sutton %t1991 %cNIPS %f/NIPS/NIPS-1991-6883.pdf %*Stationarity of Synaptic Coupling Strength Between Neurons with Nonstationary Discharge Properties %@Mark R. Sydorenko,Eric D. Young %t1991 %cNIPS %f/NIPS/NIPS-1991-6884.pdf %*Perturbing Hebbian Rules %@Peter Dayan,Geoffrey Goodhill %t1991 %cNIPS %f/NIPS/NIPS-1991-6885.pdf %*Statistical Reliability of a Blowfly Movement-Sensitive Neuron %@Rob de Ruyter van Steveninck,William Bialek %t1991 %cNIPS %f/NIPS/NIPS-1991-6886.pdf %*Network activity determines spatio-temporal integration in single cells %@Öjvind Bernander,Christof Koch,Rodney J. Douglas %t1991 %cNIPS %f/NIPS/NIPS-1991-6887.pdf %*Nonlinear Pattern Separation in Single Hippocampal Neurons with Active Dendritic Membrane %@Anthony M. Zador,Brenda J. Claiborne,Thomas H. Brown %t1991 %cNIPS %f/NIPS/NIPS-1991-6888.pdf %*Single Neuron Model: Response to Weak Modulation in the Presence of Noise %@A. R. Bulsara,W. Jacobs %t1991 %cNIPS %f/NIPS/NIPS-1991-6889.pdf %*A comparison between a neural network model for the formation of brain maps and experimental data %@K. Obermayer,K. Schulten,G. G. Blasdel %t1991 %cNIPS %f/NIPS/NIPS-1991-6890.pdf %*Retinogeniculate Development: The Role of Competition and Correlated Retinal Activity %@Ron Keesing,David G. Stork,Carla J. Shatz %t1991 %cNIPS %f/NIPS/NIPS-1991-6891.pdf %*Adaptive Synchronization of Neural and Physical Oscillators %@Kenji Doya,Shuji Yoshizawa %t1991 %cNIPS %f/NIPS/NIPS-1991-6892.pdf %*Burst Synchronization without Frequency Locking in a Completely Solvable Neural Network Model %@Heinz Schuster,Christof Koch %t1991 %cNIPS %f/NIPS/NIPS-1991-6893.pdf %*Oscillatory Model of Short Term Memory %@David Horn,Marius Usher %t1991 %cNIPS %f/NIPS/NIPS-1991-6894.pdf %*Multi-State Time Delay Networks for Continuous Speech Recognition %@Patrick Haffner,Alex Waibel %t1991 %cNIPS %f/NIPS/NIPS-1991-6895.pdf %*Modeling Applications with the Focused Gamma Net %@José Carlos Príncipe,Bert de Vries,Jyh-Ming Kuo,Pedro Guedes de Oliveira %t1991 %cNIPS %f/NIPS/NIPS-1991-6896.pdf %*Time-Warping Network: A Hybrid Framework for Speech Recognition %@Esther Levin,Roberto Pieraccini,Enrico Bocchieri %t1991 %cNIPS %f/NIPS/NIPS-1991-6897.pdf %*Improved Hidden Markov Model Speech Recognition Using Radial Basis Function Networks %@Elliot Singer,Richard P. Lippmann %t1991 %cNIPS %f/NIPS/NIPS-1991-6898.pdf %*Connectionist Optimisation of Tied Mixture Hidden Markov Models %@Steve Renals,Nelson Morgan,Hervé Bourlard,Horacio Franco,Michael Cohen %t1991 %cNIPS %f/NIPS/NIPS-1991-6899.pdf %*Neural Network - Gaussian Mixture Hybrid for Speech Recognition or Density Estimation %@Yoshua Bengio,Renato De Mori,Giovanni Flammia,Ralf Kompe %t1991 %cNIPS %f/NIPS/NIPS-1991-6900.pdf %*JANUS: Speech-to-Speech Translation Using Connectionist and Non-Connectionist Techniques %@Alex Waibel,Ajay N. Jain,Arthur E. McNair,Joe Tebelskis,Louise Osterholtz,Hiroaki Saito,Otto Schmidbauer,Tilo Sloboda,Monika Woszczyna %t1991 %cNIPS %f/NIPS/NIPS-1991-6901.pdf %*Forward Dynamics Modeling of Speech Motor Control Using Physiological Data %@Makoto Hirayama,Eric Vatikiotis-Bateson,Mitsuo Kawato,Michael I. Jordan %t1991 %cNIPS %f/NIPS/NIPS-1991-6902.pdf %*English Alphabet Recognition with Telephone Speech %@Mark Fanty,Ronald A. Cole,Krist Roginski %t1991 %cNIPS %f/NIPS/NIPS-1991-6903.pdf %*A Connectionist Learning Approach to Analyzing Linguistic Stress %@Prahlad Gupta,David S. Touretzky %t1991 %cNIPS %f/NIPS/NIPS-1991-6904.pdf %*Propagation Filters in PDS Networks for Sequencing and Ambiguity Resolution %@Ronald A. Sumida,Michael G. Dyer %t1991 %cNIPS %f/NIPS/NIPS-1991-6905.pdf %*A Segment-Based Automatic Language Identification System %@Yeshwant K. Muthusamy,Ronald A. Cole %t1991 %cNIPS %f/NIPS/NIPS-1991-6906.pdf %*HARMONET: A Neural Net for Harmonizing Chorales in the Style of J. S. Bach %@Hermann Hild,Johannes Feulner,Wolfram Menzel %t1991 %cNIPS %f/NIPS/NIPS-1991-6907.pdf %*Network Model of State-Dependent Sequencing %@Jeffrey P. Sutton,Adam N. Mamelak,J. Allan Hobson %t1991 %cNIPS %f/NIPS/NIPS-1991-6908.pdf %*Recurrent Networks and NARMA Modeling %@Jerome Connor,Les E. Atlas,Douglas R. Martin %t1991 %cNIPS %f/NIPS/NIPS-1991-6909.pdf %*Induction of Finite-State Automata Using Second-Order Recurrent Networks %@Raymond L. Watrous,Gary M. Kuhn %t1991 %cNIPS %f/NIPS/NIPS-1991-6910.pdf %*Extracting and Learning an Unknown Grammar with Recurrent Neural Networks %@C. L. Giles,C. B. Miller,D. Chen,G. Z. Sun,H. H. Chen,Y. C. Lee %t1991 %cNIPS %f/NIPS/NIPS-1991-6911.pdf %*Operators and curried functions: Training and analysis of simple recurrent networks %@Janet Wiles,Anthony Bloesch %t1991 %cNIPS %f/NIPS/NIPS-1991-6912.pdf %*Green's Function Method for Fast On-Line Learning Algorithm of Recurrent Neural Networks %@Guo-Zheng Sun,Hsing-Hen Chen,Yee-Chun Lee %t1991 %cNIPS %f/NIPS/NIPS-1991-6913.pdf %*Decoding of Neuronal Signals in Visual Pattern Recognition %@Emad N. Eskandar,Barry J. Richmond,John A. Hertz,Lance M. Optican,Troels W. Kjær %t1991 %cNIPS %f/NIPS/NIPS-1991-6914.pdf %*Learning How to Teach or Selecting Minimal Surface Data %@Davi Geiger,Ricardo A. Marques Pereira %t1991 %cNIPS %f/NIPS/NIPS-1991-6915.pdf %*Learning to Make Coherent Predictions in Domains with Discontinuities %@Suzanna Becker,Geoffrey E. Hinton %t1991 %cNIPS %f/NIPS/NIPS-1991-6916.pdf %*Recurrent Eye Tracking Network Using a Distributed Representation of Image Motion %@Paul A. Viola,Stephen G. Lisberger,Terrence J. Sejnowski %t1991 %cNIPS %f/NIPS/NIPS-1991-6917.pdf %*Against Edges: Function Approximation with Multiple Support Maps %@Trevor Darrell,Alex Pentland %t1991 %cNIPS %f/NIPS/NIPS-1991-6918.pdf %*Markov Random Fields Can Bridge Levels of Abstraction %@Paul R. Cooper,Peter N. Prokopowicz %t1991 %cNIPS %f/NIPS/NIPS-1991-6919.pdf %*Hierarchical Transformation of Space in the Visual System %@Alexandre Pouget,Stephen A. Fisher,Terrence J. Sejnowski %t1991 %cNIPS %f/NIPS/NIPS-1991-6920.pdf %*Learning to Segment Images Using Dynamic Feature Binding %@Michael C. Mozer,Richard S. Zemel,Marlene Behrmann %t1991 %cNIPS %f/NIPS/NIPS-1991-6921.pdf %*Combined Neural Network and Rule-Based Framework for Probabilistic Pattern Recognition and Discovery %@Hayit K. Greenspan,Rodney Goodman,Rama Chellappa %t1991 %cNIPS %f/NIPS/NIPS-1991-6922.pdf %*Linear Operator for Object Recognition %@Ronen Basri,Shimon Ullman %t1991 %cNIPS %f/NIPS/NIPS-1991-6923.pdf %*3D Object Recognition Using Unsupervised Feature Extraction %@Nathan Intrator,Joshua I. Gold,Heinrich H. Bülthoff,Shimon Edelman %t1991 %cNIPS %f/NIPS/NIPS-1991-6924.pdf %*Structural Risk Minimization for Character Recognition %@I. Guyon,V. Vapnik,B. Boser,L. Bottou,S. A. Solla %t1991 %cNIPS %f/NIPS/NIPS-1991-6925.pdf %*Image Segmentation with Networks of Variable Scales %@Hans Peter Graf,Craig R. Nohl,Jan Ben %t1991 %cNIPS %f/NIPS/NIPS-1991-6926.pdf %*Multi-Digit Recognition Using a Space Displacement Neural Network %@Ofer Matan,Christopher J. C. Burges,Yann LeCun,John S. Denker %t1991 %cNIPS %f/NIPS/NIPS-1991-6927.pdf %*A Self-Organizing Integrated Segmentation and Recognition Neural Net %@Jim Keeler,David E. Rumelhart %t1991 %cNIPS %f/NIPS/NIPS-1991-6928.pdf %*Recognizing Overlapping Hand-Printed Characters by Centered-Object Integrated Segmentation and Recognition %@Gale L. Martin,Mosfeq Rashid %t1991 %cNIPS %f/NIPS/NIPS-1991-6929.pdf %*Adaptive Elastic Models for Hand-Printed Character Recognition %@Geoffrey E. Hinton,Christopher K. I. Williams,Michael D. Revow %t1991 %cNIPS %f/NIPS/NIPS-1991-6930.pdf %*Obstacle Avoidance through Reinforcement Learning %@Tony J. Prescott,John E. W. Mayhew %t1991 %cNIPS %f/NIPS/NIPS-1991-6931.pdf %*Active Exploration in Dynamic Environments %@Sebastian B. Thrun,Knut Möller %t1991 %cNIPS %f/NIPS/NIPS-1991-6932.pdf %*Recognition of Manipulated Objects by Motor Learning %@Hiroaki Gomi,Mitsuo Kawato %t1991 %cNIPS %f/NIPS/NIPS-1991-6933.pdf %*Refining PID Controllers using Neural Networks %@Gary M. Scott,Jude W. Shavlik,W. Harmon Ray %t1991 %cNIPS %f/NIPS/NIPS-1991-6934.pdf %*Reverse TDNN: An Architecture For Trajectory Generation %@Patrice Simard,Yann Le Cun %t1991 %cNIPS %f/NIPS/NIPS-1991-6935.pdf %*Learning Global Direct Inverse Kinematics %@David DeMers,Kenneth Kreutz-Delgado %t1991 %cNIPS %f/NIPS/NIPS-1991-6936.pdf %*A Neural Net Model for Adaptive Control of Saccadic Accuracy by Primate Cerebellum and Brainstem %@Paul Dean,John E. W. Mayhew,Pat Langdon %t1991 %cNIPS %f/NIPS/NIPS-1991-6937.pdf %*A Cortico-Cerebellar Model that Learns to Generate Distributed Motor Commands to Control a Kinematic Arm %@N. E. Berthier,S. P. Singh,A. G. Barto,J. C. Houk %t1991 %cNIPS %f/NIPS/NIPS-1991-6938.pdf %*A Computational Mechanism to Account for Averaged Modified Hand Trajectories %@Ealan A. Henis,Tamar Flash %t1991 %cNIPS %f/NIPS/NIPS-1991-6939.pdf %*Simulation of Optimal Movements Using the Minimum-Muscle-Tension-Change Model %@Menashe Dornay,Yoji Uno,Mitsuo Kawato,Ryoji Suzuki %t1991 %cNIPS %f/NIPS/NIPS-1991-6940.pdf %*ANN Based Classification for Heart Defibrillators %@M. Jabri,S. Pickard,P. Leong,Z. Chi,B. Flower,Y. Xie %t1991 %cNIPS %f/NIPS/NIPS-1991-6941.pdf %*Neural Network Diagnosis of Avascular Necrosis from Magnetic Resonance Images %@Armando Manduca,Paul Christy,Richard Ehman %t1991 %cNIPS %f/NIPS/NIPS-1991-6942.pdf %*Neural Network Analysis of Event Related Potentials and Electroencephalogram Predicts Vigilance %@Rita Venturini,William W. Lytton,Terrence J. Sejnowski %t1991 %cNIPS %f/NIPS/NIPS-1991-6943.pdf %*Neural Control for Rolling Mills: Incorporating Domain Theories to Overcome Data Deficiency %@Martin Röscheisen,Reimar Hofmann,Volker Tresp %t1991 %cNIPS %f/NIPS/NIPS-1991-6944.pdf %*Fault Diagnosis of Antenna Pointing Systems using Hybrid Neural Network and Signal Processing Models %@Padhraic Smyth,Jeff Mellstrom %t1991 %cNIPS %f/NIPS/NIPS-1991-6945.pdf %*Multimodular Architecture for Remote Sensing Operations. %@Sylvie Thiria,Carlos Mejia,Fouad Badran,Michel Crépon %t1991 %cNIPS %f/NIPS/NIPS-1991-6946.pdf %*Principled Architecture Selection for Neural Networks: Application to Corporate Bond Rating Prediction %@John Moody,Joachim Utans %t1991 %cNIPS %f/NIPS/NIPS-1991-6947.pdf %*Adaptive Development of Connectionist Decoders for Complex Error-Correcting Codes %@Sheri L. Gish,Mario Blaum %t1991 %cNIPS %f/NIPS/NIPS-1991-6948.pdf %*Neural Network Routing for Random Multistage Interconnection Networks %@Mark W. Goudreau,C. Lee Giles %t1991 %cNIPS %f/NIPS/NIPS-1991-6949.pdf %*Networks for the Separation of Sources that are Superimposed and Delayed %@John C. Platt,Federico Faggin %t1991 %cNIPS %f/NIPS/NIPS-1991-6950.pdf %*CCD Neural Network Processors for Pattern Recognition %@Alice M. Chiang,Michael L. Chuang,Jeffrey R. LaFranchise %t1991 %cNIPS %f/NIPS/NIPS-1991-6951.pdf %*A Parallel Analog CCD/CMOS Signal Processor %@Charles F. Neugebauer,Amnon Yariv %t1991 %cNIPS %f/NIPS/NIPS-1991-6952.pdf %*Direction Selective Silicon Retina that uses Null Inhibition %@Ronald G. Benson,Tobi Delbrück %t1991 %cNIPS %f/NIPS/NIPS-1991-6953.pdf %*A Contrast Sensitive Silicon Retina with Reciprocal Synapses %@Kwabena A. Boahen,Andreas G. Andreou %t1991 %cNIPS %f/NIPS/NIPS-1991-6954.pdf %*A Neurocomputer Board Based on the ANNA Neural Network Chip %@Eduard Säckinger,Bernhard E. Boser,Lawrence D. Jackel %t1991 %cNIPS %f/NIPS/NIPS-1991-6955.pdf %*Software for ANN training on a Ring Array Processor %@Phil Kohn,Jeff Bilmes,Nelson Morgan,James Beck %t1991 %cNIPS %f/NIPS/NIPS-1991-6956.pdf %*Constrained Optimization Applied to the Parameter Setting Problem for Analog Circuits %@David Kirk,Kurt Fleischer,Lloyd Watts,Alan Barr %t1991 %cNIPS %f/NIPS/NIPS-1991-6957.pdf %*Analog LSI Implementation of an Auto-Adaptive Network for Real-Time Separation of Independent Signals %@Marc H. Cohen,Philippe O. Pouliquen,Andreas G. Andreou %t1991 %cNIPS %f/NIPS/NIPS-1991-6958.pdf %*Optical Implementation of a Self-Organizing Feature Extractor %@Dana Z. Anderson,Claus Benkert,Verena Hebler,Ju-Seog Jang,Don Montgomery,Mark Saffman %t1991 %cNIPS %f/NIPS/NIPS-1991-6959.pdf %*Estimating Average-Case Learning Curves Using Bayesian, Statistical Physics and VC Dimension Methods %@David Haussler,Michael Kearns,Manfred Opper,Robert Schapire %t1991 %cNIPS %f/NIPS/NIPS-1991-6960.pdf %*Experimental Evaluation of Learning in a Neural Microsystem %@Joshua Alspector,Anthony Jayakumar,Stephan Luna %t1991 %cNIPS %f/NIPS/NIPS-1991-6961.pdf %*Tangent Prop - A formalism for specifying selected invariances in an adaptive network %@Patrice Simard,Bernard Victorri,Yann LeCun,John Denker %t1991 %cNIPS %f/NIPS/NIPS-1991-6962.pdf %*Polynomial Uniform Convergence of Relative Frequencies to Probabilities %@Alberto Bertoni,Paola Campadelli,Anna Morpurgo,Sandra Panizza %t1991 %cNIPS %f/NIPS/NIPS-1991-6963.pdf %*Unsupervised learning of distributions on binary vectors using two layer networks %@Yoav Freund,David Haussler %t1991 %cNIPS %f/NIPS/NIPS-1991-6964.pdf %*Incrementally Learning Time-varying Half-planes %@Anthony Kuh,Thomas Petsche,Ronald L. Rivest %t1991 %cNIPS %f/NIPS/NIPS-1991-6965.pdf %*The VC-Dimension versus the Statistical Capacity of Multilayer Networks %@Chuanyi Ji,Demetri Psaltis %t1991 %cNIPS %f/NIPS/NIPS-1991-6966.pdf %*Some Approximation Properties of Projection Pursuit Learning Networks %@Ying Zhao,Christopher G. Atkeson %t1991 %cNIPS %f/NIPS/NIPS-1991-6967.pdf %*Neural Computing with Small Weights %@Kai-Yeung Siu,Jehoshua Bruck %t1991 %cNIPS %f/NIPS/NIPS-1991-6968.pdf %*A Simple Weight Decay Can Improve Generalization %@Anders Krogh,John A. Hertz %t1991 %cNIPS %f/NIPS/NIPS-1991-6969.pdf %*Rule Induction through Integrated Symbolic and Subsymbolic Processing %@Clayton McMillan,Michael C. Mozer,Paul Smolensky %t1991 %cNIPS %f/NIPS/NIPS-1991-6970.pdf %*Interpretation of Artificial Neural Networks: Mapping Knowledge-Based Neural Networks into Rules %@Geoffrey Towell,Jude W. Shavlik %t1991 %cNIPS %f/NIPS/NIPS-1991-6971.pdf %*Hierarchies of adaptive experts %@Michael I. Jordan,Robert A. Jacobs %t1991 %cNIPS %f/NIPS/NIPS-1991-6972.pdf %*Adaptive Soft Weight Tying using Gaussian Mixtures %@Steven J. Nowlan,Geoffrey E. Hinton %t1991 %cNIPS %f/NIPS/NIPS-1991-6973.pdf %*Towards Faster Stochastic Gradient Search %@Christian Darken,John Moody %t1991 %cNIPS %f/NIPS/NIPS-1991-6974.pdf %*Competitive Anti-Hebbian Learning of Invariants %@Nicol N. Schraudolph,Terrence J. Sejnowski %t1991 %cNIPS %f/NIPS/NIPS-1991-6975.pdf %*Kernel Regression and Backpropagation Training With Noise %@Petri Koistinen,Lasse Holmström %t1991 %cNIPS %f/NIPS/NIPS-1991-6976.pdf %*Splines, Rational Functions and Neural Networks %@Robert C. Williamson,Peter L. Bartlett %t1991 %cNIPS %f/NIPS/NIPS-1991-6977.pdf %*Networks with Learned Unit Response Functions %@John Moody,Norman Yarvin %t1991 %cNIPS %f/NIPS/NIPS-1991-6978.pdf %*Learning in Feedforward Networks with Nonsmooth Functions %@Nicholas J. Redding,T. Downs %t1991 %cNIPS %f/NIPS/NIPS-1991-6979.pdf %*Iterative Construction of Sparse Polynomial Approximations %@Terence D. Sanger,Richard S. Sutton,Christopher J. Matheus %t1991 %cNIPS %f/NIPS/NIPS-1991-6980.pdf %*Information Measure Based Skeletonisation %@Sowmya Ramachandran,Lorien Y. Pratt %t1991 %cNIPS %f/NIPS/NIPS-1991-6981.pdf %*Unsupervised Classifiers, Mutual Information and 'Phantom Targets %@John S. Bridle,Anthony J. R. Heading,David J. C. MacKay %t1991 %cNIPS %f/NIPS/NIPS-1991-6982.pdf %*Network generalization for production: Learning and producing styled letterforms %@Igor Grebert,David G. Stork,Ron Keesing,Steve Mims %t1991 %cNIPS %f/NIPS/NIPS-1991-6983.pdf %*Shooting Craps in Search of an Optimal Strategy for Training Connectionist Pattern Classifiers %@J. B. Hampshire II,B. V. K. Vijaya Kumar %t1991 %cNIPS %f/NIPS/NIPS-1991-6984.pdf %*Improving the Performance of Radial Basis Function Networks by Learning Center Locations %@Dietrich Wettschereck,Thomas Dietterich %t1991 %cNIPS %f/NIPS/NIPS-1991-6985.pdf %*A Topographic Product for the Optimization of Self-Organizing Feature Maps %@Hans-Ulrich Bauer,Klaus Pawelzik,Theo Geisel %t1991 %cNIPS %f/NIPS/NIPS-1991-6986.pdf %*Human and Machine 'Quick Modeling' %@Jakob Bernasconi,Karl Gustafson %t1991 %cNIPS %f/NIPS/NIPS-1991-6987.pdf %*A Comparison of Projection Pursuit and Neural Network Regression Modeling %@Jenq-Neng Huang,Hang Li,Martin Maechler,R. Douglas Martin,Jim Schimert %t1991 %cNIPS %f/NIPS/NIPS-1991-6988.pdf %*Further Studies of a Model for the Development and Regeneration of Eye-Brain Maps %@Jack D. Cowan,A. E. Friedman %t1990 %cNIPS %f/NIPS/NIPS-1990-6989.pdf %*Development and Spatial Structure of Cortical Feature Maps: A Model Study %@Klaus Obermayer,Helge Ritter,Klaus Schulten %t1990 %cNIPS %f/NIPS/NIPS-1990-6990.pdf %*Simple Spin Models for the Development of Ocular Dominance Columns and Iso-Orientation Patches %@J.D. Cowan,A. E. Friedman %t1990 %cNIPS %f/NIPS/NIPS-1990-6991.pdf %*Self-organization of Hebbian Synapses in Hippocampal Neurons %@Thomas H. Brown,Zachary F. Mainen,Anthony M. Zador,Brenda J. Claiborne %t1990 %cNIPS %f/NIPS/NIPS-1990-6992.pdf %*Cholinergic Modulation May Enhance Cortical Associative Memory Function %@Michael E. Hasselmo,Brooke P. Anderson,James M. Bower %t1990 %cNIPS %f/NIPS/NIPS-1990-6993.pdf %*Order Reduction for Dynamical Systems Describing the Behavior of Complex Neurons %@Thomas B. Kepler,L. F. Abbott,Eve Marder %t1990 %cNIPS %f/NIPS/NIPS-1990-6994.pdf %*A Lagrangian Approach to Fixed Points %@Eric Mjolsness,Willard L. Miranker %t1990 %cNIPS %f/NIPS/NIPS-1990-6995.pdf %*CAM Storage of Analog Patterns and Continuous Sequences with 3N2 Weights %@Bill Baird,Frank Eeckman %t1990 %cNIPS %f/NIPS/NIPS-1990-6996.pdf %*Connection Topology and Dynamics in Lateral Inhibition Networks %@C.M Marcus,F. R. Waugh,R. M. Westervelt %t1990 %cNIPS %f/NIPS/NIPS-1990-6997.pdf %*Shaping the State Space Landscape in Recurrent Networks %@Patrice Simard,Jean Pierre Raysz,Bernard Victorri %t1990 %cNIPS %f/NIPS/NIPS-1990-6998.pdf %*Adjoint-Functions and Temporal Learning Algorithms in Neural Networks %@N. Toomarian,J. Barhen %t1990 %cNIPS %f/NIPS/NIPS-1990-6999.pdf %*Phase-coupling in Two-Dimensional Networks of Interacting Oscillators %@Ernst Niebur,Daniel M. Kammen,Christof Koch,Daniel L. Ruderman,Heinz G. Schuster %t1990 %cNIPS %f/NIPS/NIPS-1990-7000.pdf %*Analog Computation at a Critical Point: A Novel Function for Neuronal Oscillations? %@Leonid Kruglyak,William Bialek %t1990 %cNIPS %f/NIPS/NIPS-1990-7001.pdf %*The Tempo 2 Algorithm: Adjusting Time-Delays By Supervised Learning %@Ulrich Bodenhausen,Alex Waibel %t1990 %cNIPS %f/NIPS/NIPS-1990-7002.pdf %*A Theory for Neural Networks with Time Delays %@Bert de Vries,José Carlos Príncipe %t1990 %cNIPS %f/NIPS/NIPS-1990-7003.pdf %*Statistical Mechanics of Temporal Association in Neural Networks %@Andreas V. M. Herz,Zhaoping Li,J. Leo van Hemmen %t1990 %cNIPS %f/NIPS/NIPS-1990-7004.pdf %*Learning Time-varying Concepts %@Anthony Kuh,Thomas Petsche,Ronald L. Rivest %t1990 %cNIPS %f/NIPS/NIPS-1990-7005.pdf %*Continuous Speech Recognition by Linked Predictive Neural Networks %@Joe Tebelskis,Alex Waibel,Bojan Petek,Otto Schmidbauer %t1990 %cNIPS %f/NIPS/NIPS-1990-7006.pdf %*A Recurrent Neural Network for Word Identification from Continuous Phoneme Strings %@Robert B. Allen,Candace A. Kamm %t1990 %cNIPS %f/NIPS/NIPS-1990-7007.pdf %*Connectionist Approaches to the Use of Markov Models for Speech Recognition %@Hervé Bourlard,Nelson Morgan,Chuck Wooters %t1990 %cNIPS %f/NIPS/NIPS-1990-7008.pdf %*Spoken Letter Recognition %@Mark Fanty,Ronald Cole %t1990 %cNIPS %f/NIPS/NIPS-1990-7009.pdf %*Speech Recognition Using Demi-Syllable Neural Prediction Model %@Ken-ichi Iso,Takao Watanabe %t1990 %cNIPS %f/NIPS/NIPS-1990-7010.pdf %*RecNorm: Simultaneous Normalisation and Classification applied to Speech Recognition %@John S. Bridle,Stephen J. Cox %t1990 %cNIPS %f/NIPS/NIPS-1990-7011.pdf %*Phonetic Classification and Recognition Using the Multi-Layer Perceptron %@Hong C. Leung,James R. Glass,Michael S. Phillips,Victor W. Zue %t1990 %cNIPS %f/NIPS/NIPS-1990-7012.pdf %*From Speech Recognition to Spoken Language Understanding: The Development of the MIT SUMMIT and VOYAGER Systems %@Victor Zue,James Glass,David Goodine,Lynette Hirschman,Hong Leung,Michael Phillips,Joseph Polifroni,Stephanie Seneff %t1990 %cNIPS %f/NIPS/NIPS-1990-7013.pdf %*Natural Dolphin Echo Recognition Using an Integrator Gateway Network %@Herbert L. Roitblat,Patrick W. B. Moore,Paul E. Nachtigall,Ralph H. Penner %t1990 %cNIPS %f/NIPS/NIPS-1990-7014.pdf %*Applications of Neural Networks in Video Signal Processing %@John C. Pearson,Clay D. Spence,Ronald Sverdlove %t1990 %cNIPS %f/NIPS/NIPS-1990-7015.pdf %*Discovering Viewpoint-Invariant Relationships That Characterize Objects %@Richard S. Zemel,Geoffrey E. Hinton %t1990 %cNIPS %f/NIPS/NIPS-1990-7016.pdf %*A Second-Order Translation, Rotation and Scale Invariant Neural Network %@Shelly D. D. Goggin,Kristina M. Johnson,Karl E. Gustafson %t1990 %cNIPS %f/NIPS/NIPS-1990-7017.pdf %*Learning to See Rotation and Dilation with a Hebb Rule %@Martin I. Sereno,Margaret E. Sereno %t1990 %cNIPS %f/NIPS/NIPS-1990-7018.pdf %*Stereopsis by a Neural Network Which Learns the Constraints %@Alireza Khotanzad,Ying-Wung Lee %t1990 %cNIPS %f/NIPS/NIPS-1990-7019.pdf %*Grouping Contours by Iterated Pairing Network %@Amnon Shashua,Shimon Ullman %t1990 %cNIPS %f/NIPS/NIPS-1990-7020.pdf %*A Multiscale Adaptive Network Model of Motion Computation in Primates %@H. Taichi Wang,Bimal Mathur,Christof Koch %t1990 %cNIPS %f/NIPS/NIPS-1990-7021.pdf %*Optimal Sampling of Natural Images: A Design Principle for the Visual System %@William Bialek,Daniel L. Ruderman,A. Zee %t1990 %cNIPS %f/NIPS/NIPS-1990-7022.pdf %*A VLSI Neural Network for Color Constancy %@Andrew W. Moore,John Allman,Geoffrey Fox,Rodney Goodman %t1990 %cNIPS %f/NIPS/NIPS-1990-7023.pdf %*Optimal Filtering in the Salamander Retina %@Fred Rieke,W. Geoffrey Owen,William Bialek %t1990 %cNIPS %f/NIPS/NIPS-1990-7024.pdf %*A four neuron circuit accounts for change sensitive inhibition in salamander retina %@Jeffrey L. Teeters,Frank H. Eeckman,Frank S. Werblin %t1990 %cNIPS %f/NIPS/NIPS-1990-7025.pdf %*An Analog VLSI Chip for Finding Edges from Zero-crossings %@Wyeth Bair,Christof Koch %t1990 %cNIPS %f/NIPS/NIPS-1990-7026.pdf %*A Delay-Line Based Motion Detection Chip %@Tim Horiuchi,John Lazzaro,Andrew Moore,Christof Koch %t1990 %cNIPS %f/NIPS/NIPS-1990-7027.pdf %*Neural Networks Structured for Control Application to Aircraft Landing %@Charles Schley,Yves Chauvin,Van Henkle,Richard Golden %t1990 %cNIPS %f/NIPS/NIPS-1990-7028.pdf %*Real-time autonomous robot navigation using VLSI neural networks %@Lionel Tarassenko,Michael Brownlow,Gillian Marshall,Jan Tombs,Alan Murray %t1990 %cNIPS %f/NIPS/NIPS-1990-7029.pdf %*Learning Trajectory and Force Control of an Artificial Muscle Arm by Parallel-hierarchical Neural Network Model %@Masazumi Katayama,Mitsuo Kawato %t1990 %cNIPS %f/NIPS/NIPS-1990-7030.pdf %*Proximity Effect Corrections in Electron Beam Lithography Using a Neural Network %@Robert C. Frye,Kevin D. Cummings,Edward A. Rietman %t1990 %cNIPS %f/NIPS/NIPS-1990-7031.pdf %*Planning with an Adaptive World Model %@Sebastian Thrun,Knut Möller,Alexander Linden %t1990 %cNIPS %f/NIPS/NIPS-1990-7032.pdf %*Adaptive Range Coding %@Bruce E. Rosen,James M. Goodwin,Jacques J. Vidal %t1990 %cNIPS %f/NIPS/NIPS-1990-7033.pdf %*Neural Network Implementation of Admission Control %@Rodolfo A. Milito,Isabelle Guyon,Sara A. Solla %t1990 %cNIPS %f/NIPS/NIPS-1990-7034.pdf %*A Model of Distributed Sensorimotor Control in the Cockroach Escape Turn %@R.D. Beer,G. J. Kacmarcik,R.E. Ritzmann,H.J. Chiel %t1990 %cNIPS %f/NIPS/NIPS-1990-7035.pdf %*Flight Control in the Dragonfly: A Neurobiological Simulation %@William E. Faller,Marvin W. Luttges %t1990 %cNIPS %f/NIPS/NIPS-1990-7036.pdf %*A Novel Approach to Prediction of the 3-Dimensional Structures of Protein Backbones by Neural Networks %@Henrik Fredholm,Henrik Bohr,Jakob Bohr,Søren Brunak,Rodney M. J. Cotterill,Benny Lautrup,Steffen B. Petersen %t1990 %cNIPS %f/NIPS/NIPS-1990-7037.pdf %*Training Knowledge-Based Neural Networks to Recognize Genes in DNA Sequences %@Michiel O. Noordewier,Geoffrey G. Towell,Jude W. Shavlik %t1990 %cNIPS %f/NIPS/NIPS-1990-7038.pdf %*Lg Depth Estimation and Ripple Fire Characterization Using Artificial Neural Networks %@John L. Perry,Douglas R. Baumgardt %t1990 %cNIPS %f/NIPS/NIPS-1990-7039.pdf %*Integrated Segmentation and Recognition of Hand-Printed Numerals %@James D. Keeler,David E. Rumelhart,Wee Kheng Leow %t1990 %cNIPS %f/NIPS/NIPS-1990-7040.pdf %*EMPATH: Face, Emotion, and Gender Recognition Using Holons %@Garrison W. Cottrell,Janet Metcalfe %t1990 %cNIPS %f/NIPS/NIPS-1990-7041.pdf %*SEXNET: A Neural Network Identifies Sex From Human Faces %@B.A. Golomb,D.T. Lawrence,T.J. Sejnowski %t1990 %cNIPS %f/NIPS/NIPS-1990-7042.pdf %*Analog Neural Networks as Decoders %@Ruth Erlanson,Yaser Abu-Mostafa %t1990 %cNIPS %f/NIPS/NIPS-1990-7043.pdf %*Distributed Recursive Structure Processing %@Geraldine Legendre,Yoshiro Miyata,Paul Smolensky %t1990 %cNIPS %f/NIPS/NIPS-1990-7044.pdf %*Translating Locative Prepositions %@Paul W. Munro,Mary Tabasko %t1990 %cNIPS %f/NIPS/NIPS-1990-7045.pdf %*A Short-Term Memory Architecture for the Learning of Morphophonemic Rules %@Michael Gasser,Chan-Do Lee %t1990 %cNIPS %f/NIPS/NIPS-1990-7046.pdf %*Exploiting Syllable Structure in a Connectionist Phonology Model %@David S. Touretzky,Deirdre W. Wheeler %t1990 %cNIPS %f/NIPS/NIPS-1990-7047.pdf %*Direct memory access using two cues: Finding the intersection of sets in a connectionist model %@Janet Wiles,Michael S. Humphreys,John D. Bain,Simon Dennis %t1990 %cNIPS %f/NIPS/NIPS-1990-7048.pdf %*An Attractor Neural Network Model of Recall and Recognition %@Eytan Ruppin,Yehezkel Yeshurun %t1990 %cNIPS %f/NIPS/NIPS-1990-7049.pdf %*Spherical Units as Dynamic Consequential Regions: Implications for Attention, Competition and Categorization %@Stephen Jose Hanson,Mark A. Gluck %t1990 %cNIPS %f/NIPS/NIPS-1990-7050.pdf %*Connectionist Implementation of a Theory of Generalization %@Roger N. Shepard,Sheila Kannappan %t1990 %cNIPS %f/NIPS/NIPS-1990-7051.pdf %*Multi-Layer Perceptrons with B-Spline Receptive Field Functions %@Stephen H. Lane,Marshall Flax,David Handelman,Jack Gelfand %t1990 %cNIPS %f/NIPS/NIPS-1990-7052.pdf %*Generalization Properties of Radial Basis Functions %@Sherif M. Botros,Christopher G. Atkeson %t1990 %cNIPS %f/NIPS/NIPS-1990-7053.pdf %*Sequential Adaptation of Radial Basis Function Neural Networks and its Application to Time-series Prediction %@V. Kadirkamanathan,M. Niranjan,F. Fallside %t1990 %cNIPS %f/NIPS/NIPS-1990-7054.pdf %*Oriented Non-Radial Basis Functions for Image Coding and Analysis %@Avijit Saha,Jim Christian,Dun-Sung Tang,Wu Chuan-Lin %t1990 %cNIPS %f/NIPS/NIPS-1990-7055.pdf %*Discrete Affine Wavelet Transforms For Anaylsis And Synthesis Of Feedfoward Neural Networks %@Y. C. Pati,P. S. Krishnaprasad %t1990 %cNIPS %f/NIPS/NIPS-1990-7056.pdf %*Extensions of a Theory of Networks for Approximation and Learning: Outliers and Negative Examples %@Federico Girosi,Tomaso Poggio,Bruno Caprile %t1990 %cNIPS %f/NIPS/NIPS-1990-7057.pdf %*How Receptive Field Parameters Affect Neural Learning %@Bartlett W. Mel,Stephen M. Omohundro %t1990 %cNIPS %f/NIPS/NIPS-1990-7058.pdf %*A competitive modular connectionist architecture %@Robert A. Jacobs,Michael I. Jordan %t1990 %cNIPS %f/NIPS/NIPS-1990-7059.pdf %*Evaluation of Adaptive Mixtures of Competing Experts %@Steven J. Nowlan,Geoffrey E. Hinton %t1990 %cNIPS %f/NIPS/NIPS-1990-7060.pdf %*A Framework for the Cooperation of Learning Algorithms %@Léon Bottou,Patrick Gallinari %t1990 %cNIPS %f/NIPS/NIPS-1990-7061.pdf %*Connectionist Music Composition Based on Melodic and Stylistic Constraints %@Michael C. Mozer,Todd Soukup %t1990 %cNIPS %f/NIPS/NIPS-1990-7062.pdf %*Using Genetic Algorithms to Improve Pattern Classification Performance %@Eric I. Chang,Richard P. Lippmann %t1990 %cNIPS %f/NIPS/NIPS-1990-7063.pdf %*Evolution and Learning in Neural Networks: The Number and Distribution of Learning Trials Affect the Rate of Evolution %@Ron Keesing,David G. Stork %t1990 %cNIPS %f/NIPS/NIPS-1990-7064.pdf %*A Method for the Efficient Design of Boltzmann Machines for Classiffication Problems %@Ajay Gupta,Wolfgang Maass %t1990 %cNIPS %f/NIPS/NIPS-1990-7065.pdf %*Note on Learning Rate Schedules for Stochastic Optimization %@Christian Darken,John E. Moody %t1990 %cNIPS %f/NIPS/NIPS-1990-7066.pdf %*Convergence of a Neural Network Classifier %@John S. Baras,Anthony LaVigna %t1990 %cNIPS %f/NIPS/NIPS-1990-7067.pdf %*Learning Theory and Experiments with Competitive Networks %@Griff L. Bilbro,David E. van den Bout %t1990 %cNIPS %f/NIPS/NIPS-1990-7068.pdf %*Transforming Neural-Net Output Levels to Probability Distributions %@John S. Denker,Yann LeCun %t1990 %cNIPS %f/NIPS/NIPS-1990-7069.pdf %*Back Propagation is Sensitive to Initial Conditions %@John F. Kolen,Jordan B. Pollack %t1990 %cNIPS %f/NIPS/NIPS-1990-7070.pdf %*Generalization by Weight-Elimination with Application to Forecasting %@Andreas S. Weigend,David E. Rumelhart,Bernardo A. Huberman %t1990 %cNIPS %f/NIPS/NIPS-1990-7071.pdf %*The Devil and the Network: What Sparsity Implies to Robustness and Memory %@Sanjay Biswas,Santosh S. Venkatesh %t1990 %cNIPS %f/NIPS/NIPS-1990-7072.pdf %*Dynamics of Generalization in Linear Perceptrons %@Anders Krogh,John A. Hertz %t1990 %cNIPS %f/NIPS/NIPS-1990-7073.pdf %*Constructing Hidden Units using Examples and Queries %@Eric B. Baum,Kevin J. Lang %t1990 %cNIPS %f/NIPS/NIPS-1990-7074.pdf %*Can neural networks do better than the Vapnik-Chervonenkis bounds? %@David Cohn,Gerald Tesauro %t1990 %cNIPS %f/NIPS/NIPS-1990-7075.pdf %*Second Order Properties of Error Surfaces: Learning Time and Generalization %@Yann LeCun,Ido Kanter,Sara A. Solla %t1990 %cNIPS %f/NIPS/NIPS-1990-7076.pdf %*Chaitin-Kolmogorov Complexity and Generalization in Neural Networks %@Barak A. Pearlmutter,Ronald Rosenfeld %t1990 %cNIPS %f/NIPS/NIPS-1990-7077.pdf %*Asymptotic slowing down of the nearest-neighbor classifier %@Robert R. Snapp,Demetri Psaltis,Santosh S. Venkatesh %t1990 %cNIPS %f/NIPS/NIPS-1990-7078.pdf %*On the Circuit Complexity of Neural Networks %@V. P. Roychowdhury,K. Y. Siu,A. Orlitsky,T. Kailath %t1990 %cNIPS %f/NIPS/NIPS-1990-7079.pdf %*Comparison of three classification techniques: CART, C4.5 and Multi-Layer Perceptrons %@A. C. Tsoi,R. A. Pearson %t1990 %cNIPS %f/NIPS/NIPS-1990-7080.pdf %*A Comparative Study of the Practical Characteristics of Neural Network and Conventional Pattern Classifiers %@Kenney Ng,Richard P. Lippmann %t1990 %cNIPS %f/NIPS/NIPS-1990-7081.pdf %*Kohonen Networks and Clustering: Comparative Performance in Color Clustering %@Wesley Snyder,Daniel Nissman,David Van den Bout,Griff Bilbro %t1990 %cNIPS %f/NIPS/NIPS-1990-7082.pdf %*Compact EEPROM-based Weight Functions %@A. Kramer,C. K. Sin,R. Chu,P. K. Ko %t1990 %cNIPS %f/NIPS/NIPS-1990-7083.pdf %*An Analog VLSI Splining Network %@Daniel B. Schwartz,Vijay K. Samalam %t1990 %cNIPS %f/NIPS/NIPS-1990-7084.pdf %*Relaxation Networks for Large Supervised Learning Problems %@Joshua Alspector,Robert B. Allen,Anthony Jayakumar,Torsten Zeppenfeld,Ronny Meir %t1990 %cNIPS %f/NIPS/NIPS-1990-7085.pdf %*Design and Implementation of a High Speed CMAC Neural Network Using Programmable CMOS Logic Cell Arrays %@W. Thomas Miller III,Brian A. Box,Erich C. Whitney,James M. Glynn %t1990 %cNIPS %f/NIPS/NIPS-1990-7086.pdf %*Reconfigurable Neural Net Chip with 32K Connections %@H. P. Graf,R. Janow,D. Henderson,R. Lee %t1990 %cNIPS %f/NIPS/NIPS-1990-7087.pdf %*Simulation of the Neocognitron on a CCD Parallel Processing Architecture %@Michael L. Chuang,Alice M. Chiang %t1990 %cNIPS %f/NIPS/NIPS-1990-7088.pdf %*VLSI Implementation of TInMANN %@Matt Melton,Tan Phan,Doug Reeves,Dave Van den Bout %t1990 %cNIPS %f/NIPS/NIPS-1990-7089.pdf %*The Computation of Sound Source Elevation in the Barn Owl %@Clay D. Spence,John C. Pearson %t1989 %cNIPS %f/NIPS/NIPS-1989-7090.pdf %*Neural Network Analysis of Distributed Representations of Dynamical Sensory-Motor Transformations in the Leech %@Shawn R. Lockery,Yan Fang,Terrence J. Sejnowski %t1989 %cNIPS %f/NIPS/NIPS-1989-7091.pdf %*Reading a Neural Code %@William Bialek,Fred Rieke,Robert R. de Ruyter van Steveninck,David Warland %t1989 %cNIPS %f/NIPS/NIPS-1989-7092.pdf %*Neural Implementation of Motivated Behavior: Feeding in an Artificial Insect %@Randall D. Beer,Hillel J. Chiel %t1989 %cNIPS %f/NIPS/NIPS-1989-7093.pdf %*Neural Network Simulation of Somatosensory Representational Plasticity %@Kamil A. Grajski,Michael Merzenich %t1989 %cNIPS %f/NIPS/NIPS-1989-7094.pdf %*Computational Efficiency: A Common Organizing Principle for Parallel Computer Maps and Brain Maps? %@Mark E. Nelson,James M. Bower %t1989 %cNIPS %f/NIPS/NIPS-1989-7095.pdf %*Collective Oscillations in the Visual Cortex %@Daniel M. Kammen,Christof Koch,Philip J. Holmes %t1989 %cNIPS %f/NIPS/NIPS-1989-7096.pdf %*Computer Simulation of Oscillatory Behavior in Cerebral Cortical Networks %@Matthew A. Wilson,James M. Bower %t1989 %cNIPS %f/NIPS/NIPS-1989-7097.pdf %*Development and Regeneration of Eye-Brain Maps: A Computational Model %@Jack D. Cowan,A. E. Friedman %t1989 %cNIPS %f/NIPS/NIPS-1989-7098.pdf %*The Effect of Catecholamines on Performance: From Unit to System Behavior %@David Servan-Schreiber,Harry Printz,Jonathan D. Cohen %t1989 %cNIPS %f/NIPS/NIPS-1989-7099.pdf %*Non-Boltzmann Dynamics in Networks of Spiking Neurons %@Michael C. Crair,William Bialek %t1989 %cNIPS %f/NIPS/NIPS-1989-7100.pdf %*A Computer Modeling Approach to Understanding the Inferior Olive and Its Relationships to the Cerebellar Cortex in Rats %@Maurice Lee,James M. Bower %t1989 %cNIPS %f/NIPS/NIPS-1989-7101.pdf %*Can Simple Cells Learn Curves? A Hebbian Model in a Structured Environment %@William R. Softky,Daniel M. Kammen %t1989 %cNIPS %f/NIPS/NIPS-1989-7102.pdf %*Note on Development of Modularity in Simple Cortical Models %@Alex Chernajvsky,John E. Moody %t1989 %cNIPS %f/NIPS/NIPS-1989-7103.pdf %*Effects of Firing Synchrony on Signal Propagation in Layered Networks %@G. T. Kenyon,Eberhard E. Fetz,R. D. Puff %t1989 %cNIPS %f/NIPS/NIPS-1989-7104.pdf %*Practical Characteristics of Neural Network and Conventional Pattern Classifiers on Artificial and Speech Problems %@Yuchun Lee,Richard P. Lippmann %t1989 %cNIPS %f/NIPS/NIPS-1989-7105.pdf %*Dimensionality Reduction and Prior Knowledge in E-Set Recognition %@Kevin J. Lang,Geoffrey E. Hinton %t1989 %cNIPS %f/NIPS/NIPS-1989-7106.pdf %*A Continuous Speech Recognition System Embedding MLP into HMM %@Hervé Bourlard,Nelson Morgan %t1989 %cNIPS %f/NIPS/NIPS-1989-7107.pdf %*HMM Speech Recognition with Neural Net Discrimination %@William Y. Huang,Richard P. Lippmann %t1989 %cNIPS %f/NIPS/NIPS-1989-7108.pdf %*Connectionist Architectures for Multi-Speaker Phoneme Recognition %@John B. Hampshire II,Alex Waibel %t1989 %cNIPS %f/NIPS/NIPS-1989-7109.pdf %*Speaker Independent Speech Recognition with Neural Networks and Speech Knowledge %@Yoshua Bengio,Renato de Mori,Régis Cardin %t1989 %cNIPS %f/NIPS/NIPS-1989-7110.pdf %*Combining Visual and Acoustic Speech Signals with a Neural Network Improves Intelligibility %@Terrence J. Sejnowski,Ben P. Yuhas,Moise H. Goldstein Jr.,Robert E. Jenkins %t1989 %cNIPS %f/NIPS/NIPS-1989-7111.pdf %*Learning Aspect Graph Representations from View Sequences %@Michael Seibert,Allen M. Waxman %t1989 %cNIPS %f/NIPS/NIPS-1989-7112.pdf %*TRAFFIC: Recognizing Objects Using Hierarchical Reference Frame Transformations %@Richard S. Zemel,Michael C. Mozer,Geoffrey E. Hinton %t1989 %cNIPS %f/NIPS/NIPS-1989-7113.pdf %*A self-organizing multiple-view representation of 3D objects %@Daphna Weinshall,Shimon Edelman,Heinrich H. Bülthoff %t1989 %cNIPS %f/NIPS/NIPS-1989-7114.pdf %*Model Based Image Compression and Adaptive Data Representation by Interacting Filter Banks %@Toshiaki Okamoto,Mitsuo Kawato,Toshio Inui,Sei Miyake %t1989 %cNIPS %f/NIPS/NIPS-1989-7115.pdf %*Neuronal Group Selection Theory: A Grounding in Robotics %@Jim Donnett,Tim Smithers %t1989 %cNIPS %f/NIPS/NIPS-1989-7116.pdf %*Learning to Control an Unstable System with Forward Modeling %@Michael I. Jordan,Robert A. Jacobs %t1989 %cNIPS %f/NIPS/NIPS-1989-7117.pdf %*Operational Fault Tolerance of CMAC Networks %@Michael J. Carter,Franklin J. Rudolph,Adam J. Nucci %t1989 %cNIPS %f/NIPS/NIPS-1989-7118.pdf %*Neural Network Weight Matrix Synthesis Using Optimal Control Techniques %@O. Farotimi,Amir Dembo,Thomas Kailath %t1989 %cNIPS %f/NIPS/NIPS-1989-7119.pdf %*Generalized Hopfield Networks and Nonlinear Optimization %@Gintaras V. Reklaitis,Athanasios G. Tsirukis,Manoel Fernando Tenorio %t1989 %cNIPS %f/NIPS/NIPS-1989-7120.pdf %*Incremental Parsing by Modular Recurrent Connectionist Networks %@Ajay N. Jain,Alex Waibel %t1989 %cNIPS %f/NIPS/NIPS-1989-7121.pdf %*A Computational Basis for Phonology %@David S. Touretzky,Deirdre W. Wheeler %t1989 %cNIPS %f/NIPS/NIPS-1989-7122.pdf %*Higher Order Recurrent Networks and Grammatical Inference %@C. Lee Giles,Guo-Zheng Sun,Hsing-Hen Chen,Yee-Chun Lee,Dong Chen %t1989 %cNIPS %f/NIPS/NIPS-1989-7123.pdf %*Bayesian Inference of Regular Grammar and Markov Source Models %@Kurt R. Smith,Michael I. Miller %t1989 %cNIPS %f/NIPS/NIPS-1989-7124.pdf %*Handwritten Digit Recognition with a Back-Propagation Network %@Yann LeCun,Bernhard E. Boser,John S. Denker,Donnie Henderson,R. E. Howard,Wayne E. Hubbard,Lawrence D. Jackel %t1989 %cNIPS %f/NIPS/NIPS-1989-7125.pdf %*Recognizing Hand-Printed Letters and Digits %@Gale Martin,James A. Pittman %t1989 %cNIPS %f/NIPS/NIPS-1989-7126.pdf %*A Large-Scale Neural Network Which Recognizes Handwritten Kanji Characters %@Yoshihiro Mori,Kazuki Joe %t1989 %cNIPS %f/NIPS/NIPS-1989-7127.pdf %*A Neural Network to Detect Homologies in Proteins %@Yoshua Bengio,Samy Bengio,Yannick Pouliot,Patrick Agin %t1989 %cNIPS %f/NIPS/NIPS-1989-7128.pdf %*Rule Representations in a Connectionist Chunker %@David S. Touretzky,Gillette Elvgreen III %t1989 %cNIPS %f/NIPS/NIPS-1989-7129.pdf %*Discovering the Structure of a Reactive Environment by Exploration %@Michael C. Mozer,Jonathan Bachrach %t1989 %cNIPS %f/NIPS/NIPS-1989-7130.pdf %*Designing Application-Specific Neural Networks Using the Genetic Algorithm %@Steven A. Harp,Tariq Samad,Aloke Guha %t1989 %cNIPS %f/NIPS/NIPS-1989-7131.pdf %*Neural Network Visualization %@Jakub Wejchert,Gerald Tesauro %t1989 %cNIPS %f/NIPS/NIPS-1989-7132.pdf %*Sigma-Pi Learning: On Radial Basis Functions and Cortical Associative Learning %@Bartlett W. Mel,Christof Koch %t1989 %cNIPS %f/NIPS/NIPS-1989-7133.pdf %*Algorithms for Better Representation and Faster Learning in Radial Basis Function Networks %@Avijit Saha,James D. Keeler %t1989 %cNIPS %f/NIPS/NIPS-1989-7134.pdf %*Adjoint Operator Algorithms for Faster Learning in Dynamical Neural Networks %@Jacob Barhen,Nikzad Benny Toomarian,Sandeep Gulati %t1989 %cNIPS %f/NIPS/NIPS-1989-7135.pdf %*Discovering High Order Features with Mean Field Modules %@Conrad C. Galland,Geoffrey E. Hinton %t1989 %cNIPS %f/NIPS/NIPS-1989-7136.pdf %*The Cascade-Correlation Learning Architecture %@Scott E. Fahlman,Christian Lebiere %t1989 %cNIPS %f/NIPS/NIPS-1989-7137.pdf %*The Cocktail Party Problem: Speech/Data Signal Separation Comparison between Backpropagation and SONN %@John Kassebaum,Manoel Fernando Tenorio,Christoph Schaefers %t1989 %cNIPS %f/NIPS/NIPS-1989-7138.pdf %*Generalization and Scaling in Reinforcement Learning %@David H. Ackley,Michael L. Littman %t1989 %cNIPS %f/NIPS/NIPS-1989-7139.pdf %*Training Connectionist Networks with Queries and Selective Sampling %@Les E. Atlas,David A. Cohn,Richard E. Ladner %t1989 %cNIPS %f/NIPS/NIPS-1989-7140.pdf %*Unsupervised Learning in Neurodynamics Using the Phase Velocity Field Approach %@Michail Zak,Nikzad Benny Toomarian %t1989 %cNIPS %f/NIPS/NIPS-1989-7141.pdf %*A Method for the Associative Storage of Analog Vectors %@Amir F. Atiya,Yaser S. Abu-Mostafa %t1989 %cNIPS %f/NIPS/NIPS-1989-7142.pdf %*Optimal Brain Damage %@Yann LeCun,John S. Denker,Sara A. Solla %t1989 %cNIPS %f/NIPS/NIPS-1989-7143.pdf %*Asymptotic Convergence of Backpropagation: Numerical Experiments %@Subutai Ahmad,Gerald Tesauro,Yu He %t1989 %cNIPS %f/NIPS/NIPS-1989-7144.pdf %*Comparing the Performance of Connectionist and Statistical Classifiers on an Image Segmentation Problem %@Sheri L. Gish,W. E. Blanz %t1989 %cNIPS %f/NIPS/NIPS-1989-7145.pdf %*Performance Comparisons Between Backpropagation Networks and Classification Trees on Three Real-World Applications %@Les E. Atlas,Ronald A. Cole,Jerome T. Connor,Mohamed A. El-Sharkawi,Robert J. Marks II,Yeshwant K. Muthusamy,Etienne Barnard %t1989 %cNIPS %f/NIPS/NIPS-1989-7146.pdf %*Generalization and Parameter Estimation in Feedforward Nets: Some Experiments %@N. Morgan,H. Bourlard %t1989 %cNIPS %f/NIPS/NIPS-1989-7147.pdf %*Synergy of Clustering Multiple Back Propagation Networks %@William P. Lincoln,Josef Skrzypek %t1989 %cNIPS %f/NIPS/NIPS-1989-7148.pdf %*Coupled Markov Random Fields and Mean Field Theory %@Davi Geiger,Federico Girosi %t1989 %cNIPS %f/NIPS/NIPS-1989-7149.pdf %*Complexity of Finite Precision Neural Network Classifier %@Amir Dembo,Kai-Yeung Siu,Thomas Kailath %t1989 %cNIPS %f/NIPS/NIPS-1989-7150.pdf %*Sequential Decision Problems and Neural Networks %@A. G. Barto,R. S. Sutton,C. J. C. H. Watkins %t1989 %cNIPS %f/NIPS/NIPS-1989-7151.pdf %*Analysis of Linsker's Simulations of Hebbian Rules %@David J. C. MacKay,Kenneth D. Miller %t1989 %cNIPS %f/NIPS/NIPS-1989-7152.pdf %*Analog Neural Networks of Limited Precision I: Computing with Multilinear Threshold Functions %@Zoran Obradovic,Ian Parberry %t1989 %cNIPS %f/NIPS/NIPS-1989-7153.pdf %*On the Distribution of the Number of Local Minima of a Random Function on a Graph %@Pierre Baldi,Yosef Rinott,Charles Stein %t1989 %cNIPS %f/NIPS/NIPS-1989-7154.pdf %*A Cost Function for Internal Representations %@Anders Krogh,C. I. Thorbergsson,John A. Hertz %t1989 %cNIPS %f/NIPS/NIPS-1989-7155.pdf %*An Analog VLSI Model of Adaptation in the Vestibulo-Ocular Reflex %@Stephen P. DeWeerth,Carver Mead %t1989 %cNIPS %f/NIPS/NIPS-1989-7156.pdf %*Real-Time Computer Vision and Robotics Using Analog VLSI Circuits %@Christof Koch,Wyeth Bair,John G. Harris,Timothy K. Horiuchi,Andrew Hsu,Jin Luo %t1989 %cNIPS %f/NIPS/NIPS-1989-7157.pdf %*A Reconfigurable Analog VLSI Neural Network Chip %@Srinagesh Satyanarayana,Yannis P. Tsividis,Hans Peter Graf %t1989 %cNIPS %f/NIPS/NIPS-1989-7158.pdf %*Digital-Analog Hybrid Synapse Chips for Electronic Neural Networks %@Alexander Moopenn,T. Duong,A. P. Thakoor %t1989 %cNIPS %f/NIPS/NIPS-1989-7159.pdf %*Pulse-Firing Neural Chips for Hundreds of Neurons %@Michael Brownlow,Lionel Tarassenko,Alan F. Murray,Alister Hamilton,Il Song Han,H. Martin Reekie %t1989 %cNIPS %f/NIPS/NIPS-1989-7160.pdf %*VLSI Implementation of a High-Capacity Neural Network Associative Memory %@Tzi-Dar Chiueh,Rodney M. Goodman %t1989 %cNIPS %f/NIPS/NIPS-1989-7161.pdf %*An Efficient Implementation of the Back-propagation Algorithm on the Connection Machine CM-2 %@Xiru Zhang,Michael McKenna,Jill P. Mesirov,David L. Waltz %t1989 %cNIPS %f/NIPS/NIPS-1989-7162.pdf %*Performance of Connectionist Learning Algorithms on 2-D SIMD Processor Arrays %@Fernando J. Nuñez,José A. B. Fortes %t1989 %cNIPS %f/NIPS/NIPS-1989-7163.pdf %*Constraints on Adaptive Networks for Modeling Human Generalization %@Mark A. Gluck,M. Pavel,Van Henkle %t1988 %cNIPS %f/NIPS/NIPS-1988-7164.pdf %*Efficient Parallel Learning Algorithms for Neural Networks %@Alan H. Kramer,Alberto Sangiovanni-Vincentelli %t1988 %cNIPS %f/NIPS/NIPS-1988-7165.pdf %*Self Organizing Neural Networks for the Identification Problem %@Manoel Fernando Tenorio,Wei-Tsih Lee %t1988 %cNIPS %f/NIPS/NIPS-1988-7166.pdf %*Learning by Choice of Internal Representations %@Tal Grossman,Ronny Meir,Eytan Domany %t1988 %cNIPS %f/NIPS/NIPS-1988-7167.pdf %*What Size Net Gives Valid Generalization? %@Eric B. Baum,David Haussler %t1988 %cNIPS %f/NIPS/NIPS-1988-7168.pdf %*Optimization by Mean Field Annealing %@Griff Bilbro,Reinhold Mann,Thomas K. Miller,Wesley E. Snyder,David E. van den Bout,Mark White %t1988 %cNIPS %f/NIPS/NIPS-1988-7169.pdf %*Skeletonization: A Technique for Trimming the Fat from a Network via Relevance Assessment %@Michael C. Mozer,Paul Smolensky %t1988 %cNIPS %f/NIPS/NIPS-1988-7170.pdf %*The Boltzmann Perceptron Network: A Multi-Layered Feed-Forward Network Equivalent to the Boltzmann Machine %@Eyal Yair,Allen Gersho %t1988 %cNIPS %f/NIPS/NIPS-1988-7171.pdf %*Adaptive Neural Net Preprocessing for Signal Detection in Non-Gaussian Noise %@Richard P. Lippmann,Paul Beckman %t1988 %cNIPS %f/NIPS/NIPS-1988-7172.pdf %*Training Multilayer Perceptrons with the Extended Kalman Algorithm %@Sharad Singhal,Lance Wu %t1988 %cNIPS %f/NIPS/NIPS-1988-7173.pdf %*GEMINI: Gradient Estimation Through Matrix Inversion After Noise Injection %@Yann Le Cun,Conrad C. Galland,Geoffrey E. Hinton %t1988 %cNIPS %f/NIPS/NIPS-1988-7174.pdf %*Fixed Point Analysis for Recurrent Networks %@Patrice Y. Simard,Mary B. Ottaway,Dana H. Ballard %t1988 %cNIPS %f/NIPS/NIPS-1988-7175.pdf %*Scaling and Generalization in Neural Networks: A Case Study %@Subutai Ahmad,Gerald Tesauro %t1988 %cNIPS %f/NIPS/NIPS-1988-7176.pdf %*Comparing Biases for Minimal Network Construction with Back-Propagation %@Stephen Jose Hanson,Lorien Y. Pratt %t1988 %cNIPS %f/NIPS/NIPS-1988-7177.pdf %*Learning with Temporal Derivatives in Pulse-Coded Neuronal Systems %@David B. Parker,Mark Gluck,Eric S. Reifsnider %t1988 %cNIPS %f/NIPS/NIPS-1988-7178.pdf %*Applications of Error Back-Propagation to Phonetic Classification %@Hong C. Leung,Victor W. Zue %t1988 %cNIPS %f/NIPS/NIPS-1988-7179.pdf %*Use of Multi-Layered Networks for Coding Speech with Phonetic Features %@Yoshua Bengio,Régis Cardin,Renato de Mori,Piero Cosi %t1988 %cNIPS %f/NIPS/NIPS-1988-7180.pdf %*Speech Production Using A Neural Network with a Cooperative Learning Mechanism %@Mitsuo Komura,Akio Tanaka %t1988 %cNIPS %f/NIPS/NIPS-1988-7181.pdf %*A Connectionist Expert System that Actually Works %@Richard Fozzard,Gary Bradshaw,Louis Ceci %t1988 %cNIPS %f/NIPS/NIPS-1988-7182.pdf %*An Information Theoretic Approach to Rule-Based Connectionist Expert Systems %@Rodney M. Goodman,John W. Miller,Padhraic Smyth %t1988 %cNIPS %f/NIPS/NIPS-1988-7183.pdf %*Neural Approach for TV Image Compression Using a Hopfield Type Network %@Martine Naillon,Jean-Bernard Theeten %t1988 %cNIPS %f/NIPS/NIPS-1988-7184.pdf %*Neural Net Receivers in Multiple Access-Communications %@Bernd-Peter Paris,Geoffrey Orsak,Mahesh Varanasi,Behnaam Aazhang %t1988 %cNIPS %f/NIPS/NIPS-1988-7185.pdf %*Performance of Synthetic Neural Network Classification of Noisy Radar Signals %@Stanley C. Ahalt,F. D. Garber,I. Jouny,Ashok K. Krishnamurthy %t1988 %cNIPS %f/NIPS/NIPS-1988-7186.pdf %*Neural Analog Diffusion-Enhancement Layer and Spatio-Temporal Grouping in Early Vision %@Allen M. Waxman,Michael Seibert,Robert K. Cunningham,Jian Wu %t1988 %cNIPS %f/NIPS/NIPS-1988-7187.pdf %*A Network for Image Segmentation Using Color %@Anya Hurlbert,Tomaso Poggio %t1988 %cNIPS %f/NIPS/NIPS-1988-7188.pdf %*Neural Network Star Pattern Recognition for Spacecraft Attitude Determination and Control %@Phillip Alvelda,A. Miguel San Martin %t1988 %cNIPS %f/NIPS/NIPS-1988-7189.pdf %*Neural Network Recognizer for Hand-Written Zip Code Digits %@John S. Denker,W. R. Gardner,Hans Peter Graf,Donnie Henderson,R. E. Howard,W. Hubbard,L. D. Jackel,Henry S. Baird,Isabelle Guyon %t1988 %cNIPS %f/NIPS/NIPS-1988-7190.pdf %*Neural Networks that Learn to Discriminate Similar Kanji Characters %@Yoshihiro Mori,Kazuhiko Yokosawa %t1988 %cNIPS %f/NIPS/NIPS-1988-7191.pdf %*Backpropagation and Its Application to Handwritten Signature Verification %@Timothy S. Wilkinson,Dorothy A. Mighell,Joseph W. Goodman %t1988 %cNIPS %f/NIPS/NIPS-1988-7192.pdf %*Using Backpropagation with Temporal Windows to Learn the Dynamics of the CMU Direct-Drive Arm II %@Kenneth Y. Goldberg,Barak A. Pearlmutter %t1988 %cNIPS %f/NIPS/NIPS-1988-7193.pdf %*Neuronal Maps for Sensory-Motor Control in the Barn Owl %@Clay D. Spence,John C. Pearson,J. J. Gelfand,R. M. Peterson,W. E. Sullivan %t1988 %cNIPS %f/NIPS/NIPS-1988-7194.pdf %*Models of Ocular Dominance Column Formation: Analytical and Computational Results %@Kenneth D. Miller,Joseph B. Keller,Michael P. Stryker %t1988 %cNIPS %f/NIPS/NIPS-1988-7195.pdf %*Modeling Small Oscillating Biological Networks in Analog VLSI %@Sylvie Ryckebusch,James M. Bower,Carver Mead %t1988 %cNIPS %f/NIPS/NIPS-1988-7196.pdf %*Storing Covariance by the Associative Long-Term Potentiation and Depression of Synaptic Strengths in the Hippocampus %@Patric K. Stanton,Terrence J. Sejnowski %t1988 %cNIPS %f/NIPS/NIPS-1988-7197.pdf %*Modeling the Olfactory Bulb - Coupled Nonlinear Oscillators %@Zhaoping Li,John J. Hopfield %t1988 %cNIPS %f/NIPS/NIPS-1988-7198.pdf %*Neural Control of Sensory Acquisition: The Vestibulo-Ocular Reflex %@Michael G. Paulin,Mark E. Nelson,James M. Bower %t1988 %cNIPS %f/NIPS/NIPS-1988-7199.pdf %*Computer Modeling of Associative Learning %@Daniel L. Alkon,Francis K. H. Quek,Thomas P. Vogl %t1988 %cNIPS %f/NIPS/NIPS-1988-7200.pdf %*Simulation and Measurement of the Electric Fields Generated by Weakly Electric Fish %@Brian Rasnow,Christopher Assad,Mark E. Nelson,James M. Bower %t1988 %cNIPS %f/NIPS/NIPS-1988-7201.pdf %*A Model for Resolution Enhancement (Hyperacuity) in Sensory Representation %@Jun Zhang,John P. Miller %t1988 %cNIPS %f/NIPS/NIPS-1988-7202.pdf %*A Computationally Robust Anatomical Model for Retinal Directional Selectivity %@Norberto M. Grzywacz,Franklin R. Amthor %t1988 %cNIPS %f/NIPS/NIPS-1988-7203.pdf %*GENESIS: A System for Simulating Neural Networks %@Matthew A. Wilson,Upinder S. Bhalla,John D. Uhley,James M. Bower %t1988 %cNIPS %f/NIPS/NIPS-1988-7204.pdf %*Training a 3-Node Neural Network is NP-Complete %@Avrim Blum,Ronald L. Rivest %t1988 %cNIPS %f/NIPS/NIPS-1988-7205.pdf %*Links Between Markov Models and Multilayer Perceptrons %@Hervé Bourlard,C. J. Wellekens %t1988 %cNIPS %f/NIPS/NIPS-1988-7206.pdf %*Convergence and Pattern-Stabilization in the Boltzmann Machine %@Moshe Kam,Roger Cheng %t1988 %cNIPS %f/NIPS/NIPS-1988-7207.pdf %*Dynamic, Non-Local Role Bindings and Inferencing in a Localist Network for Natural Language Understanding %@Trent E. Lange,Michael G. Dyer %t1988 %cNIPS %f/NIPS/NIPS-1988-7208.pdf %*A Model of Neural Oscillator for a Unified Submodule %@Alexandr B. Kirillov,G. N. Borisyuk,R. M. Borisyuk,Ye. I. Kovalenko,V. I. Makarenko,V. A. Chulaevsky,V. I. Kryukov %t1988 %cNIPS %f/NIPS/NIPS-1988-7209.pdf %*Dynamics of Analog Neural Networks with Time Delay %@Charles M. Marcus,R. M. Westervelt %t1988 %cNIPS %f/NIPS/NIPS-1988-7210.pdf %*Heterogeneous Neural Networks for Adaptive Behavior in Dynamic Environments %@Randall D. Beer,Hillel J. Chiel,Leon S. Sterling %t1988 %cNIPS %f/NIPS/NIPS-1988-7211.pdf %*Range Image Restoration Using Mean Field Annealing %@Griff L. Bilbro,Wesley E. Snyder %t1988 %cNIPS %f/NIPS/NIPS-1988-7212.pdf %*Neural Networks for Model Matching and Perceptual Organization %@Eric Mjolsness,Gene Gindi,P. Anandan %t1988 %cNIPS %f/NIPS/NIPS-1988-7213.pdf %*On the K-Winners-Take-All Network %@E. Majani,Ruth Erlanson,Yaser S. Abu-Mostafa %t1988 %cNIPS %f/NIPS/NIPS-1988-7214.pdf %*Learning Sequential Structure in Simple Recurrent Networks %@David Servan-Schreiber,Axel Cleeremans,James L. McClelland %t1988 %cNIPS %f/NIPS/NIPS-1988-7215.pdf %*A Passive Shared Element Analog Electrical Cochlea %@David Feld,Joe Eisenberg,Edwin Lewis %t1988 %cNIPS %f/NIPS/NIPS-1988-7216.pdf %*Programmable Analog Pulse-Firing Neural Networks %@Alister Hamilton,Alan F. Murray,Lionel Tarassenko %t1988 %cNIPS %f/NIPS/NIPS-1988-7217.pdf %*A Low-Power CMOS Circuit Which Emulates Temporal Electrical Properties of Neurons %@Jack L. Meador,Clint S. Cole %t1988 %cNIPS %f/NIPS/NIPS-1988-7218.pdf %*Analog Implementation of Shunting Neural Networks %@Bahram Nabet,Robert B. Darling,Robert B. Pinter %t1988 %cNIPS %f/NIPS/NIPS-1988-7219.pdf %*Winner-Take-All Networks of O(N) Complexity %@J. Lazzaro,S. Ryckebusch,M.A. Mahowald,C. A. Mead %t1988 %cNIPS %f/NIPS/NIPS-1988-7220.pdf %*A Programmable Analog Neural Computer and Simulator %@Paul Mueller,Jan Van der Spiegel,David Blackman,Timothy Chiu,Thomas Clare,Joseph Dao,Christopher Donham,Tzu-pu Hsieh,Marc Loinaz %t1988 %cNIPS %f/NIPS/NIPS-1988-7221.pdf %*An Electronic Photoreceptor Sensitive to Small Changes in Intensity %@Tobi Delbrück,C. A. Mead %t1988 %cNIPS %f/NIPS/NIPS-1988-7222.pdf %*Digital Realisation of Self-Organising Maps %@Nigel M. Allinson,Martin J. Johnson,Kevin J. Moon %t1988 %cNIPS %f/NIPS/NIPS-1988-7223.pdf %*An Analog Self-Organizing Neural Network Chip %@James R. Mann,Sheldon Gilbert %t1988 %cNIPS %f/NIPS/NIPS-1988-7224.pdf %*Performance of a Stochastic Learning Microchip %@Joshua Alspector,Bhusan Gupta,Robert B. Allen %t1988 %cNIPS %f/NIPS/NIPS-1988-7225.pdf %*Adaptive Neural Networks Using MOS Charge Storage %@Daniel B. Schwartz,R. E. Howard,Wayne E. Hubbard %t1988 %cNIPS %f/NIPS/NIPS-1988-7226.pdf %*A Self-Learning Neural Network %@Allan Hartstein,R. H. Koch %t1988 %cNIPS %f/NIPS/NIPS-1988-7227.pdf %*Training a Limited-Interconnect, Synthetic Neural IC %@M. R. Walker,S. Haghighi,A. Afghan,Larry A. Akers %t1988 %cNIPS %f/NIPS/NIPS-1988-7228.pdf %*Stochastic Learning Networks and their Electronic Implementation %@Joshua Alspector,Robert B. Allen,Victor Hu,Srinagesh Satyanarayana %t1987 %cNIPS %f/NIPS/NIPS-1987-7229.pdf %*An Artificial Neural Network for Spatio-Temporal Bipolar Patterns: Application to Phoneme Classification %@Les E. Atlas,Toshiteru Homma,Robert J. Marks II %t1987 %cNIPS %f/NIPS/NIPS-1987-7230.pdf %*On Properties of Networks of Neuron-Like Elements %@Pierre Baldi,Santosh S. Venkatesh %t1987 %cNIPS %f/NIPS/NIPS-1987-7231.pdf %*Supervised Learning of Probability Distributions by Neural Networks %@Eric B. Baum,Frank Wilczek %t1987 %cNIPS %f/NIPS/NIPS-1987-7232.pdf %*Centric Models of the Orientation Map in Primary Visual Cortex %@William Baxter,Bruce Dow %t1987 %cNIPS %f/NIPS/NIPS-1987-7233.pdf %*Optimal Neural Spike Classification %@James M. Bower,Amir F. Atiya %t1987 %cNIPS %f/NIPS/NIPS-1987-7234.pdf %*Neural Networks for Template Matching: Application to Real-Time Classification of the Action Potentials of Real Neurons %@James M. Bower,Yiu-Fai Wong,Jashojiban Banik %t1987 %cNIPS %f/NIPS/NIPS-1987-7235.pdf %*A Computer Simulation of Olfactory Cortex with Functional Implications for Storage and Retrieval of Olfactory Information %@James M. Bower,Matthew A. Wilson %t1987 %cNIPS %f/NIPS/NIPS-1987-7236.pdf %*On the Power of Neural Networks for Solving Hard Problems %@Jehoshua Bruck,Joseph W. Goodman %t1987 %cNIPS %f/NIPS/NIPS-1987-7237.pdf %*Mathematical Analysis of Learning Behavior of Neuronal Models %@John Y. Cheung,Massoud Omidvar %t1987 %cNIPS %f/NIPS/NIPS-1987-7238.pdf %*A NEURAL NETWORK CLASSIFIER BASED ON CODING THEORY %@Tzi-Dar Chiueh,Rodney Goodman %t1987 %cNIPS %f/NIPS/NIPS-1987-7239.pdf %*New Hardware for Massive Neural Networks %@Darryl D. Coon,A. G. Unil Perera %t1987 %cNIPS %f/NIPS/NIPS-1987-7240.pdf %*HIGH DENSITY ASSOCIATIVE MEMORIES %@Amir Dembo,Ofer Zeitouni %t1987 %cNIPS %f/NIPS/NIPS-1987-7241.pdf %*Network Generality, Training Required, and Precision Required %@John S. Denker,Ben S. Wittner %t1987 %cNIPS %f/NIPS/NIPS-1987-7242.pdf %*Ensemble' Boltzmann Units have Collective Computational Properties like those of Hopfield and Tank Neurons %@Mark Derthick,Joe Tebelskis %t1987 %cNIPS %f/NIPS/NIPS-1987-7243.pdf %*High Order Neural Networks for Efficient Associative Memory Design %@Gérard Dreyfus,Isabelle Guyon,Jean-Pierre Nadal,Léon Personnaz %t1987 %cNIPS %f/NIPS/NIPS-1987-7244.pdf %*Hierarchical Learning Control - An Approach with Neuron-Like Associative Memories %@Enis Ersü,Henning Tolle %t1987 %cNIPS %f/NIPS/NIPS-1987-7245.pdf %*Encoding Geometric Invariances in Higher-Order Neural Networks %@C. Lee Giles,R. D. Griffin,T. Maxwell %t1987 %cNIPS %f/NIPS/NIPS-1987-7246.pdf %*PARTITIONING OF SENSORY DATA BY A CORTICAL NETWORK %@Richard Granger,Jose Ambros-Ingerson,Howard Henry,Gary Lynch %t1987 %cNIPS %f/NIPS/NIPS-1987-7247.pdf %*Minkowski-r Back-Propagation: Learning in Connectionist Models with Non-Euclidian Error Signals %@Stephen Jose Hanson,David J. Burr %t1987 %cNIPS %f/NIPS/NIPS-1987-7248.pdf %*Learning Representations by Recirculation %@Geoffrey E. Hinton,James L. McClelland %t1987 %cNIPS %f/NIPS/NIPS-1987-7249.pdf %*Experimental Demonstrations of Optical Neural Computers %@Ken Hsu,David Brady,Demetri Psaltis %t1987 %cNIPS %f/NIPS/NIPS-1987-7250.pdf %*Neural Net and Traditional Classifiers %@William Y. Huang,Richard P. Lippmann %t1987 %cNIPS %f/NIPS/NIPS-1987-7251.pdf %*An Optimization Network for Matrix Inversion %@Ju-Seog Jang,Soo-Young Lee,Sang-Yung Shin %t1987 %cNIPS %f/NIPS/NIPS-1987-7252.pdf %*Computing Motion Using Resistive Networks %@Christof Koch,Jin Luo,Carver Mead,James Hutchinson %t1987 %cNIPS %f/NIPS/NIPS-1987-7253.pdf %*How Neural Nets Work %@Alan S. Lapedes,Robert M. Farber %t1987 %cNIPS %f/NIPS/NIPS-1987-7254.pdf %*Distributed Neural Information Processing in the Vestibulo-Ocular System %@Clifford Lau,Vicente Honrubia %t1987 %cNIPS %f/NIPS/NIPS-1987-7255.pdf %*SPONTANEOUS AND INFORMATION-TRIGGERED SEGMENTS OF SERIES OF HUMAN BRAIN ELECTRIC FIELD MAPS %@D. Lehmann,D. Brandeis,A. Horst,H. Ozaki,I. Pal %t1987 %cNIPS %f/NIPS/NIPS-1987-7256.pdf %*Microelectronic Implementations of Connectionist Neural Networks %@Stuart Mackie,Hans Peter Graf,Daniel B. Schwartz,John S. Denker %t1987 %cNIPS %f/NIPS/NIPS-1987-7257.pdf %*Basins of Attraction for Electronic Neural Networks %@Charles M. Marcus,R. M. Westervelt %t1987 %cNIPS %f/NIPS/NIPS-1987-7258.pdf %*The Performance of Convex Set Projection Based Neural Networks %@Robert J. Marks II,Les E. Atlas,Seho Oh,James A. Ritcey %t1987 %cNIPS %f/NIPS/NIPS-1987-7259.pdf %*Stability Results for Neural Networks %@Anthony N. Michel,Jay A. Farrell,Wolfgang Porod %t1987 %cNIPS %f/NIPS/NIPS-1987-7260.pdf %*Programmable Synaptic Chip for Electronic Neural Networks %@Alexander Moopenn,H. Langenbacher,A. P. Thakoor,S. K. Khanna %t1987 %cNIPS %f/NIPS/NIPS-1987-7261.pdf %*Bit-Serial Neural Networks %@Alan F. Murray,Anthony V. W. Smith,Zoe F. Butler %t1987 %cNIPS %f/NIPS/NIPS-1987-7262.pdf %*A Trellis-Structured Neural Network %@Thomas Petsche,Bradley W. Dickinson %t1987 %cNIPS %f/NIPS/NIPS-1987-7263.pdf %*Constrained Differential Optimization %@John C. Platt,Alan H. Barr %t1987 %cNIPS %f/NIPS/NIPS-1987-7264.pdf %*Learning a Color Algorithm from Examples %@Tomaso A. Poggio,Anya C. Hurlbert %t1987 %cNIPS %f/NIPS/NIPS-1987-7265.pdf %*Static and Dynamic Error Propagation Networks with Application to Speech Coding %@A. J. Robinson,F. Fallside %t1987 %cNIPS %f/NIPS/NIPS-1987-7266.pdf %*LEARNING BY STATE RECURRENCE DETECTION %@Bruce E. Rosen,James M. Goodwin,Jacques J. Vidal %t1987 %cNIPS %f/NIPS/NIPS-1987-7267.pdf %*Scaling Properties of Coarse-Coded Symbol Memories %@Ronald Rosenfeld,David S. Touretzky %t1987 %cNIPS %f/NIPS/NIPS-1987-7268.pdf %*An Adaptive and Heterodyne Filtering Procedure for the Imaging of Moving Objects %@F. H. Schuling,H. A. K. Mastebroek,W. H. Zaagman %t1987 %cNIPS %f/NIPS/NIPS-1987-7269.pdf %*PATTERN CLASS DEGENERACY IN AN UNRESTRICTED STORAGE DENSITY MEMORY %@Christopher L. Scofield,Douglas L. Reilly,Charles Elbaum,Leon N. Cooper %t1987 %cNIPS %f/NIPS/NIPS-1987-7270.pdf %*Teaching Artificial Neural Systems to Drive: Manual Training Techniques for Autonomous Systems %@J. F. Shepanski,S. A. Macy %t1987 %cNIPS %f/NIPS/NIPS-1987-7271.pdf %*Time-Sequential Self-Organization of Hierarchical Neural Networks %@Ronald H. Silverman,Andrew S. Noetzel %t1987 %cNIPS %f/NIPS/NIPS-1987-7272.pdf %*A Computer Simulation of Cerebral Neocortex: Computational Capabilities of Nonlinear Neural Networks %@Alexander Singer,John P. Donoghue %t1987 %cNIPS %f/NIPS/NIPS-1987-7273.pdf %*Spatial Organization of Neural Networks: A Probabilistic Modeling Approach %@Andreas Stafylopatis,Marios D. Dikaiakos,D. Kontoravdis %t1987 %cNIPS %f/NIPS/NIPS-1987-7274.pdf %*A Dynamical Approach to Temporal Pattern Processing %@W. Scott Stornetta,Tad Hogg,Bernardo A. Huberman %t1987 %cNIPS %f/NIPS/NIPS-1987-7275.pdf %*A Novel Net that Learns Sequential Decision Process %@Guo-Zheng Sun,Yee-Chun Lee,Hsing-Hen Chen %t1987 %cNIPS %f/NIPS/NIPS-1987-7276.pdf %*Self-Organization of Associative Database and Its Applications %@Hisashi Suzuki,Suguru Arimoto %t1987 %cNIPS %f/NIPS/NIPS-1987-7277.pdf %*A Neural-Network Solution to the Concentrator Assignment Problem %@Gene A. Tagliarini,Edward W. Page %t1987 %cNIPS %f/NIPS/NIPS-1987-7278.pdf %*A 'Neural' Network that Learns to Play Backgammon %@Gerald Tesauro,Terrence J. Sejnowski %t1987 %cNIPS %f/NIPS/NIPS-1987-7279.pdf %*Neuromorphic Networks Based on Sparse Optical Orthogonal Codes %@Mario P. Vecchi,Jawad A. Salehi %t1987 %cNIPS %f/NIPS/NIPS-1987-7280.pdf %*Synchronization in Neural Nets %@Jacques J. Vidal,John Haggerty %t1987 %cNIPS %f/NIPS/NIPS-1987-7281.pdf %*Invariant Object Recognition Using a Distributed Associative Memory %@Harry Wechsler,George Lee Zimmerman %t1987 %cNIPS %f/NIPS/NIPS-1987-7282.pdf %*Strategies for Teaching Layered Networks Classification Tasks %@Ben S. Wittner,John S. Denker %t1987 %cNIPS %f/NIPS/NIPS-1987-7283.pdf %*A Method for the Design of Stable Lateral Inhibition Networks that is Robust in the Presence of Circuit Parasitics %@John L. Wyatt Jr.,D. L. Standley %t1987 %cNIPS %f/NIPS/NIPS-1987-7284.pdf %*Towards a Framework for Semantic Exploration of Frequent Patterns %@Behrooz Omidvar Tehrani , Sihem Amer-Yahia , Alexandre Termier , Aurélie Bertaux , Eric Gaussier , Marie-Christine Rousset %t2013 %cVLDB %f/VLDB/VLDB-2013-7285.pdf %*A Method for Activity Recognition Partially Resilient on Mobile Device Orientation %@Nikola Jajac, Bratislav Predic, Dragan Stojanovic %t2013 %cVLDB %f/VLDB/VLDB-2013-7286.pdf %*Vectorizing Database Column Scans with Complex Predicates %@Thomas Willhalm , Ismail Oukid , Ingo Muller and Franz Faerber %t2013 %cVLDB %f/VLDB/VLDB-2013-7287.pdf %*High-Performance XML Twing Filtering using GPUs %@Ildar Absalyamov , Roger Moussalli , Vassilis Tsotras and Walid Najjar %t2013 %cVLDB %f/VLDB/VLDB-2013-7288.pdf %*Skew Handling in Aggregate Streaming Queries on GPUs %@Georgios Koutsoumpakis, Iakovos Koutsoumpakis and Anastasios Gounaris %t2013 %cVLDB %f/VLDB/VLDB-2013-7289.pdf %*Crowdsourcing Feedback for Pay­As­You­Go Data Integration. %@Fernando Osorno­Gutierrez, Norman Paton and Alvaro A. A. Fernandes %t2013 %cVLDB %f/VLDB/VLDB-2013-7290.pdf %*The Palm­tree Index: Indexing with the crowd. %@Ahmed Mahmood, Walid Aref, Eduard Dragut and Saleh Basalamah %t2013 %cVLDB %f/VLDB/VLDB-2013-7291.pdf %*Crowdsourcing to Mobile Users: A Study of the Role of Platforms and Tasks. %@Vincenzo Della Mea, Eddy Maddalena and Stefano Mizzaro %t2013 %cVLDB %f/VLDB/VLDB-2013-7292.pdf %*Extending Augmented Reality Mobile Application with Structured Knowledge from the LOD Cloud %@Betül Aydin , Jerome Gensel , Philippe Genoud , Sylvie Calabretto , Bruno Tellez %t2013 %cVLDB %f/VLDB/VLDB-2013-7293.pdf %*Cache Conscious Star-Join in MapReduce Environments %@Guoliang Zhou, Yongli Zhu and Guilan Wang %t2013 %cVLDB %f/VLDB/VLDB-2013-7294.pdf %*Toward Intersection Filter-Based Optimization for Joins in MapReduce %@Thuong-Cang Phan, Laurent d'Orazio and Philippe Rigaux %t2013 %cVLDB %f/VLDB/VLDB-2013-7295.pdf %*i2MapReduce: Incremental Iterative MapReduce %@Yanfeng Zhang and Shimin Chen %t2013 %cVLDB %f/VLDB/VLDB-2013-7296.pdf %*Massively Parallel NUMA-aware Hash Joins %@Harald Lang, Viktor Leis, Martina-Cezara Albutiu, Thomas Neumann, Alfons Kemper (Technische Universität München) %t2013 %cVLDB %f/VLDB/VLDB-2013-7297.pdf %*Fast Column Scans: Paged Indices for In-Memory Column Stores %@Martin Faust, David Schwalb, Jens Krueger %t2013 %cVLDB %f/VLDB/VLDB-2013-7298.pdf %*Compiled Plans for In-Memory Path-Counting Queries %@Brandon Myers, Jeremy Hyrkas, Daniel Halperin, Bill Howe %t2013 %cVLDB %f/VLDB/VLDB-2013-7299.pdf %*Task Scheduling for Highly Concurrent Analytical and Transactional Main-Memory Workloads %@Iraklis Psaroudakis , Tobias Scheuer , Norman May and Anastasia Ailamaki %t2013 %cVLDB %f/VLDB/VLDB-2013-7300.pdf %*Modularizing B+-trees: Three-Level B+-trees Work Fine %@Shigero Sasaki and Takuya Araki %t2013 %cVLDB %f/VLDB/VLDB-2013-7301.pdf %*FBARC: I/O Asymmetry Aware Buffer Replacement Strategy %@Paul Dubs , Ilia Petrov , Robert Gottstein and Alejandro Buchmann %t2013 %cVLDB %f/VLDB/VLDB-2013-7302.pdf %*Wrapper Generation Supervised by a Noisy Crowd. %@Valter Crescenzi, Paolo Merialdo and Disheng Qiu %t2013 %cVLDB %f/VLDB/VLDB-2013-7303.pdf %*Condition­Task­Store: A Declarative Abstraction for Microtask­based Complex Crowdsourcing. %@Kenji Gonnokami, Atsuyuki Morishima and Hiroyuki Kitagawa %t2013 %cVLDB %f/VLDB/VLDB-2013-7304.pdf %*Vanet-X: A Videogame to Evaluate Information Management in Vehicular Networks %@Sergio Ilarri, Eduardo Mena, Víctor Rújula %t2013 %cVLDB %f/VLDB/VLDB-2013-7305.pdf %*Mobile objects and sensors within a video surveillance system: Spatio-temporal model and queries %@Dana Codreanu, Ana-Maria Manzat, Florence Sedes (Université de Toulouse, France) %t2013 %cVLDB %f/VLDB/VLDB-2013-7306.pdf %*MappingSets for Spatial Observation Data Warehouses %@José R.R. Viqueira, David Martínez, Sebastián Villarroya, José A. Taboada %t2013 %cVLDB %f/VLDB/VLDB-2013-7307.pdf %*To trust, or not to trust: Highlighting the need for data provenance in mobile apps for smart cities %@Mikel Emaldi , Oscar Peña , Jon Lázaro , Diego López-de-Ipiña , Sacha Vanhecke , Erik Mannens %t2013 %cVLDB %f/VLDB/VLDB-2013-7308.pdf %*Bloofi: A Hierarchical Bloom Filter Index with Applications to Distributed Data Provenance %@Adina Crainiceanu %t2013 %cVLDB %f/VLDB/VLDB-2013-7309.pdf %*Cloud Intelligence - Challenges for Research and Industry (Roundtable/Panel discussion) %@Jerome Darmont and Torben Bach Pedersen %t2013 %cVLDB %f/VLDB/VLDB-2013-7310.pdf %*Bringing Linear Algebra Objects to Life in a Column-Oriented In-Memory Database %@David Kernert , Frank Köhler , Wolfgang Lehner %t2013 %cVLDB %f/VLDB/VLDB-2013-7311.pdf %*Dynamic Query Prioritization for In-Memory Databases %@Johannes Wust , Martin Grund , Hasso Plattner %t2013 %cVLDB %f/VLDB/VLDB-2013-7312.pdf %*Data In Context: Aiding News Consumers while Taming Dataspaces. %@Eugene Wu, Adam Marcus , Sam Madden %t2013 %cVLDB %f/VLDB/VLDB-2013-7313.pdf %*Cost and Quality Trade­Offs in Crowdsourcing. %@Anja Gruenheid, Donald Kossmann %t2013 %cVLDB %f/VLDB/VLDB-2013-7314.pdf %*Crowds, not Drones: Modeling Human Factors in Interactive Crowdsourcing %@Senjuti Basu Roy, Ioanna Lykourentzou, Saravanan Thirumuruganathan, Sihem Amer­Yahia and Gautam Das %t2013 %cVLDB %f/VLDB/VLDB-2013-7315.pdf %*HealthNet: A System for Mobile and Wearable Health Information Management %@Christoph Quix, Johannes Barnickel, Sandra Geisler, Marwan Hassani, Saim Kim, Xiang Li, Andreas Lorenz, Till Quadflieg, Thomas Gries, Matthias Jarke, Steffen Leonhardt, Ulrike Meyer, Thomas Seidl %t2013 %cVLDB %f/VLDB/VLDB-2013-7316.pdf %*A clinical quality feedback loop supported by mobile point of care (POC) data collection %@Christopher A. Bain , Tracey Bucknall , Janet Weir-Phyland %t2013 %cVLDB %f/VLDB/VLDB-2013-7317.pdf %*Aggregates Caching in Columnar In-Memory Databases %@Stephan Müller, Hasso Plattner %t2013 %cVLDB %f/VLDB/VLDB-2013-7318.pdf %*An Evaluation of Strict Timestamp Ordering Concurrency Control for Main-Memory Database Systems %@Henrik Mühe, Stephan Wolf, Alfons Kemper, Thomas Neumann %t2013 %cVLDB %f/VLDB/VLDB-2013-7319.pdf %*Revisiting Co-Processing for Hash Joins on the Coupled CPU-GPU Architecture %@Jiong HE , Mian Lu , Bingsheng He %t2013 %cVLDB %f/VLDB/VLDB-2013-7320.pdf %*Hardware-Oblivious Parallelism for In-Memory Column-Stores %@Max Heimel (Technische Universität Berlin), Michael Saecker , Holger Pirk , Stefan Manegold , Volker Markl (Technische Universität Berlin) %t2013 %cVLDB %f/VLDB/VLDB-2013-7321.pdf %*Improving Flash Write Performance by Using Update Frequency %@Radu Stoica , Anastasia Ailamaki %t2013 %cVLDB %f/VLDB/VLDB-2013-7322.pdf %*Hybrid Storage Management for Database Systems %@Xin Liu , Kenneth Salem %t2013 %cVLDB %f/VLDB/VLDB-2013-7323.pdf %*The Yin and Yang of Processing Data Warehousing Queries on GPU Devices %@Yuan Yuan , Rubao Lee , Xiaodong Zhang %t2013 %cVLDB %f/VLDB/VLDB-2013-7324.pdf %*Big Data Integration Bio: Bio: %@Xin Luna Dong and Divesh Srivastava %t2013 %cVLDB %f/VLDB/VLDB-2013-7325.pdf %*A Performance Study of Three Disk-based Structures for Indexing and Querying Frequent Itemsets %@Guimei Liu , Andre Suchitra , Limsoon Wong %t2013 %cVLDB %f/VLDB/VLDB-2013-7326.pdf %*Computing Immutable Regions for Subspace Top-k Queries %@Kyriakos Mouratidis , HweeHwa Pang %t2013 %cVLDB %f/VLDB/VLDB-2013-7327.pdf %*A Data-adaptive and Dynamic Segmentation Index for Whole Matching on Time Series %@Yang Wang , Peng Wang , Jian Pei , Wei Wang ,Sheng Huang %t2013 %cVLDB %f/VLDB/VLDB-2013-7328.pdf %*Efficient Indexing for Diverse Query Results %@Lu Li , Chee-Yong Chan %t2013 %cVLDB %f/VLDB/VLDB-2013-7329.pdf %*LLAMA: A Cache/Storage Subsystem for Modern Hardware %@Justin Levandoski , David Lomet , Sudipta Sengupta %t2013 %cVLDB %f/VLDB/VLDB-2013-7330.pdf %*MillWheel: Fault-Tolerant Stream Processing at Internet Scale %@Tyler Akidau , Alex Balikov , Kaya Bekiroglu , Slava Chernyak , Josh Haberman , Reuven Lax , Sam McVeety , Daniel Mills , Paul Nordstrom , Sam Whittle %t2013 %cVLDB %f/VLDB/VLDB-2013-7331.pdf %*F1: A Distributed SQL Database That Scales %@Jeff Shute , Radek Vingralek , Bart Samwel , Ben Handy , Chad Whipkey , Eric Rollins , Mircea Oancea , Kyle Littlefield , David Menestrina , Stephan Ellner , John Cieslewicz , Ian Rae , Traian Stancescu , Himani Apte %t2013 %cVLDB %f/VLDB/VLDB-2013-7332.pdf %*DB2 with BLU Acceleration: So Much More than Just a Column Store %@Vijayshankar Raman , Gopi Attaluri , Ronald Barber , Naresh Chainani , David Kalmuk , Vincent Kulandai Samy , Jens Leenstra , Sam Lightstone , Shaorong Liu , Guy M. Lohman , Tim Malkemus , Rene Mueller , Ippokratis Pandis , Berni Schiefer , David Sharpe , Richard Sidle , Adam Storm , Liping Zhang %t2013 %cVLDB %f/VLDB/VLDB-2013-7333.pdf %*The Quantcast File System %@Michael Ovsiannikov , Silvius Rus , Damian Reeves , Paul Sutter , Sriram Rao , Jim Kelly , Chris Zimmerman , Dan Adkins , Thilee Subramaniam , Jeremy Fishman %t2013 %cVLDB %f/VLDB/VLDB-2013-7334.pdf %*Overview of Turn Data Management Platform for Digital Advertising %@Hazem Elmeleegy , Yinan Li , Yan Qi , Peter Wilmot , Mingxi Wu , Santanu Kolay , Ali Dasdan , Songting Chen %t2013 %cVLDB %f/VLDB/VLDB-2013-7335.pdf %*A Demonstration of SpatialHadoop: An Efficient MapReduce Framework for Spatial Data %@Ahmed Eldawy , Mohamed Mokbel %t2013 %cVLDB %f/VLDB/VLDB-2013-7336.pdf %*Aggregate Profile Clustering for Telco Analytics %@Mehmet Ali Abbasoğlu (Ä°hsan Doğramacı Bilkent Üniversitesi), Buğra Gedik , Hakan Ferhatosmanoglu %t2013 %cVLDB %f/VLDB/VLDB-2013-7337.pdf %*Parallel Graph Processing on Graphics Processors Made Easy %@Jianlong Zhong , Bingsheng He %t2013 %cVLDB %f/VLDB/VLDB-2013-7338.pdf %*Mosquito: Another One Bites the Data Upload STream %@Stefan Richter , Jens Dittrich %t2013 %cVLDB %f/VLDB/VLDB-2013-7339.pdf %*NoFTL: Database Systems on FTL-less Flash Storage %@Sergey Hardock , Ilia Petrov , Robert Gottstein , Alejandro Buchmann %t2013 %cVLDB %f/VLDB/VLDB-2013-7340.pdf %*EagleTree: Exploring the Design Space of SSD-Based Algorithms %@Niv Dayan , Martin Kjær Svendsen , Matias Bjørling , Philippe Bonnet , Luc Bouganim %t2013 %cVLDB %f/VLDB/VLDB-2013-7341.pdf %*Flexible Query Processor on FPGAs %@mohammadreza Najafi , Mohammad Sadoghi , Hans-Arno Jacobsen %t2013 %cVLDB %f/VLDB/VLDB-2013-7342.pdf %*A Demonstration of Iterative Parallel Array Processing in Support of Telescope Image Analysis %@Matthew Moyers , Emad Soroush , Spencer Wallace , Simon Krughoff , Jake Vanderplas , Magdalena Balazinska , Andrew Connolly %t2013 %cVLDB %f/VLDB/VLDB-2013-7343.pdf %*Hone: "Scaling Down" Hadoop on Shared-Memory Systems %@K.Ashwin Kumar , Jonathan Gluck , Amol Deshpande , Jimmy Lin %t2013 %cVLDB %f/VLDB/VLDB-2013-7344.pdf %*REEF: Retainable Evaluator Execution Framework %@Byung-Gon Chun , Tyson Condie , Carlo Curino , Raghu Ramakrishnan , Russell Sears , Markus Weimer %t2013 %cVLDB %f/VLDB/VLDB-2013-7345.pdf %*OmniDB: Towards Portable and Efficient Query Processing on Parallel CPU/GPU Architectures %@Shuhao Zhang , Jiong HE , Bingsheng He , Mian Lu %t2013 %cVLDB %f/VLDB/VLDB-2013-7346.pdf %*DiAl: Distributed Streaming Analytics Anywhere, Anytime %@Ivo Santos , Marcel Tilly , Badrish Chandramouli , Jonathan Goldstein %t2013 %cVLDB %f/VLDB/VLDB-2013-7347.pdf %*DAX: A Widely Distributed Multi-tenant Storage Service for DBMS Hosting %@Rui Liu , Ashraf Aboulnaga , Kenneth Salem %t2013 %cVLDB %f/VLDB/VLDB-2013-7348.pdf %*Low-latency multi-datacenter databases using replicated commit %@Hatem Mahmoud , Faisal Nawab , Alexander Pucher , Divyakant Agrawal , Amr El Abbadi %t2013 %cVLDB %f/VLDB/VLDB-2013-7349.pdf %*RACE: A Scalable and Elastic Parallel System for Discovering Repeats in Very Long Sequences %@Essam Mansour , Ahmed El-Roby , Panos Kalnis , Aron Ahmadia , Ashraf Aboulnaga %t2013 %cVLDB %f/VLDB/VLDB-2013-7350.pdf %*XORing Elephants: Novel Erasure Codes for Big Data %@Maheswaran Sathiamoorthy , Megasthenis Asteris , Dimitris Papailiopoulos , Alexandros Dimakis , Ramkumar Vadali,Dropbox), Scott Chen , Dhruba Borthakur %t2013 %cVLDB %f/VLDB/VLDB-2013-7351.pdf %*Distribution-Based Query Scheduling %@Yun Chi , Hakan Hacigumus , Wang-Pin Hsiung , Jeffrey Naughton %t2013 %cVLDB %f/VLDB/VLDB-2013-7352.pdf %*Big Data Integration Bio: Bio: %@Xin Luna Dong and Divesh Srivastava %t2013 %cVLDB %f/VLDB/VLDB-2013-7353.pdf %*IS-LABEL: an Independent-Set based Labeling Scheme for Point-to-Point Distance Querying %@Ada Wai-Chee Fu , Huanhuan Wu , James Cheng , Raymond Chi-Wing Wong %t2013 %cVLDB %f/VLDB/VLDB-2013-7354.pdf %*Mining and Indexing Graphs For Supergraph Search %@Dayu Yuan , Prasenjit Mitra , C. Lee Giles %t2013 %cVLDB %f/VLDB/VLDB-2013-7355.pdf %*NeMa: Fast Graph Search with Label Similarity %@Arijit Khan , Yinghui Wu , Charu Aggarwal , Xifeng Yan %t2013 %cVLDB %f/VLDB/VLDB-2013-7356.pdf %*A Distributed Graph Engine for Web Scale RDF Data %@Kai Zeng , Jiacheng Yang , Haixun Wang , Bin Shao , Zhongyuan Wang %t2013 %cVLDB %f/VLDB/VLDB-2013-7357.pdf %*Top-K Nearest Keyword Search on Large Graphs %@Miao Qiao , Lu Qin, Hong Cheng , Jeffrey Yu %t2013 %cVLDB %f/VLDB/VLDB-2013-7358.pdf %*Online, Asynchronous Schema Change in F1 %@Ian Rae , Eric Rollins , Jeff Shute , Sukhdeep Sodhi , Radek Vingralek %t2013 %cVLDB %f/VLDB/VLDB-2013-7359.pdf %*WOO: A Scalable and Multi-tenant Platform for Continuous Knowledge Base Synthesis %@Kedar Bellare , Carlo Curino , Ashwin Machanavajjhala , Peter Mika , Mandar Rahurkar , Aamod Sane %t2013 %cVLDB %f/VLDB/VLDB-2013-7360.pdf %*Entity Extraction, Linking, Classification, and Tagging for Social Media: a Wikipedia-Based Approach %@Abhishek Gattani , Digvijay S. Lamba , Nikesh Garera , Mitul Tiwari , Xiaoyong Chai , Sanjib Das , Sri Subramaniam , Anand Rajaraman , Venky Harinarayan , AnHai Doan %t2013 %cVLDB %f/VLDB/VLDB-2013-7361.pdf %*Unicorn: A System for Searching the Social Graph %@Michael Curtiss , Iain Becker , Tudor Bosman , Sergey Doroshenko , Lucian Grijincu , Tom Jackson , Sandhya Kunnatur , Soren Lassen , Philip Pronin , Sriram Sankar , Guanghao Shen , Gintaras Woss , Chao Yang , Ning Zhang %t2013 %cVLDB %f/VLDB/VLDB-2013-7362.pdf %*DesTeller: A System for Destination Prediction Based on Trajectories with Privacy Protection %@Andy Yuan Xue , Rui Zhang , Yu Zheng , Xing Xie , Jianhui Yu , Yong Tang %t2013 %cVLDB %f/VLDB/VLDB-2013-7363.pdf %*GroupFinder: A New Approach to Top-K Point-of-Interest Group Retrieval %@Kenneth Bøgh , Anders Skovsgaard , Christian S. Jensen %t2013 %cVLDB %f/VLDB/VLDB-2013-7364.pdf %*CrowdMiner: Mining association rules from the crowd %@Yael Amsterdamer , Yael Grossman , Tova Milo , Pierre Senellart (Télécom ParisTech) %t2013 %cVLDB %f/VLDB/VLDB-2013-7365.pdf %*TeRec: A Temporal Recommender System Over Tweet Stream %@Chen Chen , Hongzhi Yin , Junjie Yao , Bin Cui %t2013 %cVLDB %f/VLDB/VLDB-2013-7366.pdf %*iRoad: A Framework For Scalable Predictive Query Processing On Road Networks %@Abdeltawab Hendawi , Jie Bao , Mohamed Mokbel %t2013 %cVLDB %f/VLDB/VLDB-2013-7367.pdf %*SmartMonitor: Using Smart Devices to Perform Structural Health Monitoring %@Dimitrios Kotsakos , Panos Sakkos , Vana Kalogeraki , Dimitrios Gunopulos %t2013 %cVLDB %f/VLDB/VLDB-2013-7368.pdf %*EnviroMeter: A Platform for Querying Community-Sensed Data %@Saket Sathe , Arthur Oviedo , Dipanjan Chakraborty , Karl Aberer %t2013 %cVLDB %f/VLDB/VLDB-2013-7369.pdf %*EvenTweet: Online Localized Event Detection from Twitter %@Hamed Abdelhaq , Christian Sengstock , Michael Gertz %t2013 %cVLDB %f/VLDB/VLDB-2013-7370.pdf %*PhotoStand: A Map Query Interface for a Database of News Photos %@Hanan Samet , Marco D. Adelfio , Brendan C. Fruin , Michael D. Lieberman , Jagan Sankaranarayanan %t2013 %cVLDB %f/VLDB/VLDB-2013-7371.pdf %*Ringtail: A Generalized Nowcasting System %@Dolan Antenucci , Erdong Li , Shaobo Liu , Bochun Zhang , Mike Cafarella , Christopher Re %t2013 %cVLDB %f/VLDB/VLDB-2013-7372.pdf %*IPS: An Interactive Package Configuration System for Trip Planning %@Min Xie , Laks V. S. Lakshmanan , Peter Wood %t2013 %cVLDB %f/VLDB/VLDB-2013-7373.pdf %*R2-D2: a System to Support Probabilistic Path Prediction in Dynamic Environments %@Jingbo Zhou , Anthony K.H. Tung , Wei Wu , Wee Siong Ng %t2013 %cVLDB %f/VLDB/VLDB-2013-7374.pdf %*Piggybacking on social networks %@Aristides Gionis , Flavio Junqueira (Microsoft Research Cambridge , Vincent Leroy (University of Grenoble - CNRS , Marco Serafini , Ingmar Weber %t2013 %cVLDB %f/VLDB/VLDB-2013-7375.pdf %*Answering Planning Queries with the Crowd %@Haim Kaplan , Ilia Lotosh , Tova Milo , Slava Novgorodov %t2013 %cVLDB %f/VLDB/VLDB-2013-7376.pdf %*Query Optimization over Crowdsourced Data %@Hyunjung Park , Jennifer Widom %t2013 %cVLDB %f/VLDB/VLDB-2013-7377.pdf %*Counting with the Crowd %@Adam Marcus (Locu/MIT CSAIL), David Karger , Sam Madden , Robert Miller , Sewoong Oh %t2013 %cVLDB %f/VLDB/VLDB-2013-7378.pdf %*Question Selection for Crowd Entity Resolution %@Steven Whang , Peter Lofgren , Hector Garcia-Molina %t2013 %cVLDB %f/VLDB/VLDB-2013-7379.pdf %*Towards Database Virtualization for Database as a Service Bio: Bio: Bio: Bio: %@Aaron J. Elmore , Carlo Curino , Divyakant Agrawal , Amr El Abbadi %t2013 %cVLDB %f/VLDB/VLDB-2013-7380.pdf %*DisC Diversity: Result Diversification based on Dissimilarity and Coverage %@Marina Drosou , Evaggelia Pitoura %t2013 %cVLDB %f/VLDB/VLDB-2013-7381.pdf %*Ratio Threshold Queries over Distributed Data Sources %@Rajeev Gupta , Krithi Ramamritham , Mukesh Mohania %t2013 %cVLDB %f/VLDB/VLDB-2013-7382.pdf %*Distributed Time-aware Provenance %@Wenchao Zhou , Suyog Mapara , Yiqing Ren , Yang Li , Andreas Haeberlen , Zachary Ives , Boon Thau Loo , Micah Sherr %t2013 %cVLDB %f/VLDB/VLDB-2013-7383.pdf %*TripleBit: a Fast and Compact System for Large Scale RDF Data %@Pingpeng Yuan , Pu Liu , Buwen Wu , Ling Liu , Hai Jin , Wenya Zhang %t2013 %cVLDB %f/VLDB/VLDB-2013-7384.pdf %*Extraction and Integration of Partially Overlapping Web Sources %@Mirko Bronzi (Università Roma Tre), Valter Crescenzi (Università Roma Tre), Paolo Merialdo (Università Roma Tre), Paolo Papotti %t2013 %cVLDB %f/VLDB/VLDB-2013-7385.pdf %*Hadoop-GIS: A High Performance Spatial Data Warehousing System over MapReduce %@Ablimit Aji , Fusheng Wang , Hoang Vo , Rubao Lee , Qiaoling Liu , Xiaodong Zhang , Joel Saltz %t2013 %cVLDB %f/VLDB/VLDB-2013-7386.pdf %*Statistics Collection in Oracle Spatial and Graph: Fast Histogram Construction for Complex Geometry Objects %@Bhuvan Bamba , Siva Ravada , Ying Hu , Richard Anderson %t2013 %cVLDB %f/VLDB/VLDB-2013-7387.pdf %*Scuba: Diving into Data at Facebook %@Lior Abraham , John Allen , Oleksandr Barykin , Vinayak Borkar , Bhuwan Chopra , Ciprian Gerea , Daniel Merl , Josh Metzler , David Reiss , Subbu Subramanian , Janet L. Wiener , Okay Zed %t2013 %cVLDB %f/VLDB/VLDB-2013-7388.pdf %*Adaptive and Big Data Scale Parallel Execution in Oracle %@Srikanth Bellamkonda , Huagang Li , Unmesh Jagtap , Yali Zhu , Thierry Cruanes , Vince Liang %t2013 %cVLDB %f/VLDB/VLDB-2013-7389.pdf %*NADEEF: A Generalized Data Cleaning System %@Amr Ebaid , Ahmed Elmagarmid , Ihab Ilyas , Mourad Ouzzani , Jorge-Arnulfo Quiane-Ruiz , Nan Tang , Si Yin %t2013 %cVLDB %f/VLDB/VLDB-2013-7390.pdf %*RecDB in Action: Recommendation Made Easy in Relational Databases %@Mohamed Sarwat , James Avery , Mohamed Mokbel %t2013 %cVLDB %f/VLDB/VLDB-2013-7391.pdf %*Graph Queries in a Next-Generation Datalog System %@Alexander Shkapsky , Kai Zeng , Carlo Zaniolo %t2013 %cVLDB %f/VLDB/VLDB-2013-7392.pdf %*Lazy ETL in Action: ETL Technology Dates Scientific Data %@Yağız Kargın , Milena Ivanova , Stefan Manegold , Martin Kersten , Ying Zhang %t2013 %cVLDB %f/VLDB/VLDB-2013-7393.pdf %*Scolopax: Exploratory Analysis of Scientific Data %@Alper Okcan , Mirek Riedewald, Biswanath Panda, Daniel Fink %t2013 %cVLDB %f/VLDB/VLDB-2013-7394.pdf %*PROPOLIS: Provisioned Analysis of Data-Centric Processes %@Daniel Deutch , Yuval Moskovitch , Val Tannen %t2013 %cVLDB %f/VLDB/VLDB-2013-7395.pdf %*Feature Selection in Enterprise Analytics: A Demonstration using an R-based Data Analytics System %@Pradap Konda , Arun Kumar , Christopher Re , Vaishnavi Sashikanth %t2013 %cVLDB %f/VLDB/VLDB-2013-7396.pdf %*PLASMA-HD: Probing the LAttice Structure and MAkeup of High-dimensional Data %@David Fuhry , Yang Zhang , Venu Satuluri , Arnab Nandi , Srinivasan Parthasarathy %t2013 %cVLDB %f/VLDB/VLDB-2013-7397.pdf %*IBminer: A Text Mining Tool for Constructing and Populating InfoBox Databases and Knowledge Bases %@Hamid Mousavi , Shi Gao , Carlo Zaniolo %t2013 %cVLDB %f/VLDB/VLDB-2013-7398.pdf %*Mining and Linking Patterns across Live Data Streams and Stream Archives %@Di Yang , Kaiyu Zhao , Maryam Hasan , Hanyuan Lu , Elke Rundensteiner , Matthew Ward %t2013 %cVLDB %f/VLDB/VLDB-2013-7399.pdf %*User Analytics with UbeOne: Insights into Web Printing %@Georgia Koutrika , Qian Lin , Jerry Liu %t2013 %cVLDB %f/VLDB/VLDB-2013-7400.pdf %*Big and Useful: What's in the Data for Me? Bio: Bio: Bio: Bio: Bio: Bio: Bio: %@Rada Chirkova , Minos Garofalakis , Joseph M. Hellerstein , Yannis Ioannidis , Zachary Ives , H. V. Jagadish , Jun Yang %t2013 %cVLDB %f/VLDB/VLDB-2013-7401.pdf %*Towards Database Virtualization for Database as a Service Bio: Bio: Bio: Bio: %@Aaron J. Elmore , Carlo Curino , Divyakant Agrawal , Amr El Abbadi %t2013 %cVLDB %f/VLDB/VLDB-2013-7402.pdf %*Efficient Querying of Inconsistent Databases with Binary Integer Programming %@Phokion Kolaitis , Enela Pema , Wang-Chiew Tan %t2013 %cVLDB %f/VLDB/VLDB-2013-7403.pdf %*Streaming Quotient Filter: A Near Optimal Approximate Duplicate Detection Approach for Data Streams %@Sourav Dutta , Ankur Narang , Suman K. Bera %t2013 %cVLDB %f/VLDB/VLDB-2013-7404.pdf %*On Repairing Structural Problems In Semi-structured Data %@Flip Korn , Barna Saha , Divesh Srivastava , Shanshan Ying %t2013 %cVLDB %f/VLDB/VLDB-2013-7405.pdf %*The Llunatic Data Cleaning Framework %@Floris Geerts , Giansalvatore Mecca (Università della Basilicata), Paolo Papotti , Donatello Santoro (Università della Basilicata) %t2013 %cVLDB %f/VLDB/VLDB-2013-7406.pdf %*Truth Finding on the Deep Web: Is the Problem Solved? %@Xian Li , Xin Luna Dong , Kenneth Lyons , Weiyi Meng , Divesh Srivastava %t2013 %cVLDB %f/VLDB/VLDB-2013-7407.pdf %*Practical Differential Privacy via Grouping and Smoothing %@Georgios Kellaris , Stavros Papadopoulos %t2013 %cVLDB %f/VLDB/VLDB-2013-7408.pdf %*On Differentially Private Frequent Itemset Mining %@Chen Zeng , Jeffrey Naughton , Jin-yi Cai %t2013 %cVLDB %f/VLDB/VLDB-2013-7409.pdf %*Processing Analytical Queries over Encrypted Data %@Stephen Tu , Frans Kaashoek , Sam Madden , Nickolai Zeldovich %t2013 %cVLDB %f/VLDB/VLDB-2013-7410.pdf %*CorrectDB: SQL Engine with Practical Query Authentication %@Sumeet Bajaj , Radu Sion %t2013 %cVLDB %f/VLDB/VLDB-2013-7411.pdf %*Lightweight Privacy-Preserving Peer-to-Peer Data Integration %@Ye Zhang , Wai-Kit Wong , Siu Ming Yiu , Nikos Mamoulis , David W. Cheung %t2013 %cVLDB %f/VLDB/VLDB-2013-7412.pdf %*Senbazuru: A Prototype Spreadsheet Database Management System %@Shirley Zhe Chen , Mike Cafarella , Jun Chen , Daniel Prevo, Junfeng Zhuang %t2013 %cVLDB %f/VLDB/VLDB-2013-7413.pdf %*ReqFlex: Fuzzy Queries for Everyone %@Grégory SMITS , Olivier PIVERT , Thomas GIRAULT %t2013 %cVLDB %f/VLDB/VLDB-2013-7414.pdf %*Comprehensive and Interactive Temporal Query Processing with SAP HANA %@Martin Kaufmann (ETH Zürich), Panagiotis Vagenas , Peter Fischer (Albert-Ludwigs-Universität Freiburg, Germany), Donald Kossmann , Franz Färber %t2013 %cVLDB %f/VLDB/VLDB-2013-7415.pdf %*Functions Are Data Too (Defunctionalization for PL/SQL) %@Torsten Grust (Universität Tübingen, Germany), Nils Schweinsberg (Universität Tübingen, Germany), Alexander Ulrich (Universität Tübingen, Germany) %t2013 %cVLDB %f/VLDB/VLDB-2013-7416.pdf %*QUEST: A Keyword Search System for Relational Data based on Semantic and Machine Learning Techniques %@Sonia Bergamaschi, Francesco Guerra, and Matteo Interlandi (Università di Modena e Reggio Emilia), Raquel Trillo-Lado , Yannis Velegrakis (Università di Trento) %t2013 %cVLDB %f/VLDB/VLDB-2013-7417.pdf %*ROSeAnn: Reconciling Opinions of Semantic Annotators %@Luying Chen , Stefano Ortona , Giorgio Orsi , Michael Benedikt %t2013 %cVLDB %f/VLDB/VLDB-2013-7418.pdf %*SkySuite: A Framework of Skyline-Join Operators for Static and Stream Environments %@Mithila Nagendra , K. Selcuk Candan %t2013 %cVLDB %f/VLDB/VLDB-2013-7419.pdf %*MASTRO STUDIO: Managing Ontology-Based Data Access applications %@Cristina Civili , Marco Console , Giuseppe De Giacomo (Sapienza Università di Roma), Domenico Lembo , Maurizio Lenzerini (Sapienza Università di Roma), Lorenzo Lepore , Riccardo Mancini , Antonella Poggi , Riccardo Rosati , Marco Ruzzi , Valerio Santarelli , Domenico Fabio Savo %t2013 %cVLDB %f/VLDB/VLDB-2013-7420.pdf %*PAQO: A Preference-Aware Query Optimizer for PostgreSQL %@Nicholas L. Farnan , Adam J. Lee , Panos K. Chrysanthis , Ting Yu %t2013 %cVLDB %f/VLDB/VLDB-2013-7421.pdf %*eSkyline: Processing Skyline Queries over Encrypted Data %@Suvarna Bothe , Panagiotis Karras , Akrivi Vlachou %t2013 %cVLDB %f/VLDB/VLDB-2013-7422.pdf %*GestureQuery: A Multitouch Database Query Interface %@Lilong Jiang , Michael Mandel , Arnab Nandi %t2013 %cVLDB %f/VLDB/VLDB-2013-7423.pdf %*Complete Approximations of Incomplete Queries %@Ognjen Savkovic , Paramita Mirza , Alex Tomasi , Werner Nutt %t2013 %cVLDB %f/VLDB/VLDB-2013-7424.pdf %*POIKILO: A Tool for Evaluating the Results of Diversification Models and Algorithms %@Marina Drosou , Evaggelia Pitoura %t2013 %cVLDB %f/VLDB/VLDB-2013-7425.pdf %*Efficient SimRank-based Similarity Join Over Large Graphs %@Weiguo Zheng , Lei Zou , Yansong Feng, Lei Chen , Dongyan Zhao %t2013 %cVLDB %f/VLDB/VLDB-2013-7426.pdf %*Incremental and Accuracy-Aware Personalized PageRank through Scheduled Approximation %@Fanwei Zhu , Yuan Fang, Kevin Chang , Jing Ying %t2013 %cVLDB %f/VLDB/VLDB-2013-7427.pdf %*Memory Efficient Minimum Substring Partitioning %@Yang Li , Pegah Kamousi , Fangqiu Han , Shengqi Yang , Xifeng Yan , Subhash Suri %t2013 %cVLDB %f/VLDB/VLDB-2013-7428.pdf %*An In-depth Comparison of Subgraph Isomorphism Algorithms in Graph Databases %@Jinsoo Lee , Wook-Shin Han , Romans Kasperovics , Jeong-Hoon Lee %t2013 %cVLDB %f/VLDB/VLDB-2013-7429.pdf %*Large Scale Cohesive Subgraphs Discovery for Social Network Visual Analysis %@Feng Zhao , Anthony Tung %t2013 %cVLDB %f/VLDB/VLDB-2013-7430.pdf %*Toward Scalable Transaction Processing - Evolution of Shore - MT Bio: Bio: Bio: Bio: %@Anastasia Ailamaki , Ryan Johnson , Ippokratis Pandis , Pinar Tözün %t2013 %cVLDB %f/VLDB/VLDB-2013-7431.pdf %*Scaling Factorization Machines to Relational Data %@Steffen Rendle, University of Konstanz %t2013 %cVLDB %f/VLDB/VLDB-2013-7432.pdf %*Scorpion: Explaining Away Outliers in Aggregate Queries %@Eugene Wu , Sam Madden %t2013 %cVLDB %f/VLDB/VLDB-2013-7433.pdf %*PARAS: A Parameter Space Framework for Online Association Mining %@Xika Lin , Abhishek Mukherji , Elke Rundensteiner , Carolina Ruiz , Matthew Ward %t2013 %cVLDB %f/VLDB/VLDB-2013-7434.pdf %*Schema Extraction for Tabular Data on the Web %@Marco D. Adelfio , Hanan Samet %t2013 %cVLDB %f/VLDB/VLDB-2013-7435.pdf %*Partitioning and Ranking Tagged Data Sources %@Milad Eftekhar , Nick Koudas %t2013 %cVLDB %f/VLDB/VLDB-2013-7436.pdf %*Next Generation Data Analytics at IBM Research %@Oktie Hassanzadeh , Anastasips Kementsietsidis , Benny Kimelfeld , Rajasekar Krishnamurthy , Fatma Özcan , Ippokratis Pandis %t2013 %cVLDB %f/VLDB/VLDB-2013-7437.pdf %*Learning and Intelligent Optimization: one ring to rule them all %@Mauro Brunato , Roberto Battiti %t2013 %cVLDB %f/VLDB/VLDB-2013-7438.pdf %*SAP HANA: The Evolution from a Modern Main-Memory Data Platform to an Enterprise Application Platform %@Vishal Sikka , Franz Färber , Anil Goel , Wolfgang Lehner %t2013 %cVLDB %f/VLDB/VLDB-2013-7439.pdf %*Athilab presentation %@Sergio Ramazzina , Chiara L. Ballari %t2013 %cVLDB %f/VLDB/VLDB-2013-7440.pdf %*Context-Aware Computing: Opportunities and Open Issues %@Edward Y. Chang %t2013 %cVLDB %f/VLDB/VLDB-2013-7441.pdf %*How to maximize the value of big data with the open source SpagoBI suite through a comprehensive approach %@Monica Franceschini %t2013 %cVLDB %f/VLDB/VLDB-2013-7442.pdf %*Odyssey: A MultiStore System for Evolutionary Analytics %@Hakan Hacıgumus , Jagan Sankaranarayanan , Junichi Tatemura , Jeff LeFevre, Neoklis Polyzotis %t2013 %cVLDB %f/VLDB/VLDB-2013-7444.pdf %*TPC: A Look Back and a Look Ahead %@Raghunath Nambiar , Meikel Poess %t2013 %cVLDB %f/VLDB/VLDB-2013-7445.pdf %*Designing Query Optimizers for Big Data problems of the future %@Nga Tran %t2013 %cVLDB %f/VLDB/VLDB-2013-7447.pdf %*Microsoft SQL Server’s Integrated Database Approach for Modern Applications and Hardware %@David Lomet %t2013 %cVLDB %f/VLDB/VLDB-2013-7448.pdf %*A global Entity Name System (ENS) for data ecosystems. %@Paolo Bouquet , Andrea Molinari %t2013 %cVLDB %f/VLDB/VLDB-2013-7449.pdf %*A Demonstration of SpatialHadoop: An Efficient MapReduce Framework for Spatial Data %@Ahmed Eldawy , Mohamed Mokbel %t2013 %cVLDB %f/VLDB/VLDB-2013-7450.pdf %*Aggregate Profile Clustering for Telco Analytics %@Mehmet Ali Abbasoğlu (Ä°hsan Doğramacı Bilkent Üniversitesi), Buğra Gedik , Hakan Ferhatosmanoglu %t2013 %cVLDB %f/VLDB/VLDB-2013-7451.pdf %*Parallel Graph Processing on Graphics Processors Made Easy %@Jianlong Zhong , Bingsheng He %t2013 %cVLDB %f/VLDB/VLDB-2013-7452.pdf %*Mosquito: Another One Bites the Data Upload STream %@Stefan Richter , Jens Dittrich %t2013 %cVLDB %f/VLDB/VLDB-2013-7453.pdf %*NoFTL: Database Systems on FTL-less Flash Storage %@Sergey Hardock , Ilia Petrov , Robert Gottstein , Alejandro Buchmann %t2013 %cVLDB %f/VLDB/VLDB-2013-7454.pdf %*EagleTree: Exploring the Design Space of SSD-Based Algorithms %@Niv Dayan , Martin Kjær Svendsen , Matias Bjørling , Philippe Bonnet , Luc Bouganim %t2013 %cVLDB %f/VLDB/VLDB-2013-7455.pdf %*Flexible Query Processor on FPGAs %@mohammadreza Najafi , Mohammad Sadoghi , Hans-Arno Jacobsen %t2013 %cVLDB %f/VLDB/VLDB-2013-7456.pdf %*A Demonstration of Iterative Parallel Array Processing in Support of Telescope Image Analysis %@Matthew Moyers , Emad Soroush , Spencer Wallace , Simon Krughoff , Jake Vanderplas , Magdalena Balazinska , Andrew Connolly %t2013 %cVLDB %f/VLDB/VLDB-2013-7457.pdf %*Hone: "Scaling Down" Hadoop on Shared-Memory Systems %@K.Ashwin Kumar , Jonathan Gluck , Amol Deshpande , Jimmy Lin %t2013 %cVLDB %f/VLDB/VLDB-2013-7458.pdf %*REEF: Retainable Evaluator Execution Framework %@Byung-Gon Chun , Tyson Condie , Carlo Curino , Raghu Ramakrishnan , Russell Sears , Markus Weimer %t2013 %cVLDB %f/VLDB/VLDB-2013-7459.pdf %*OmniDB: Towards Portable and Efficient Query Processing on Parallel CPU/GPU Architectures %@Shuhao Zhang , Jiong HE , Bingsheng He , Mian Lu %t2013 %cVLDB %f/VLDB/VLDB-2013-7460.pdf %*DiAl: Distributed Streaming Analytics Anywhere, Anytime %@Ivo Santos , Marcel Tilly , Badrish Chandramouli , Jonathan Goldstein %t2013 %cVLDB %f/VLDB/VLDB-2013-7461.pdf %*ClouDiA: A Deployment Advisor for Public Clouds %@Tao Zou , Ronan Le Bras , Marcos Vaz Salles , Alan Demers , Johannes Gehrke %t2013 %cVLDB %f/VLDB/VLDB-2013-7463.pdf %*Upper and Lower Bounds on the Cost of a Map-Reduce Computation %@Foto Afrati , Anish Das Sarma , Semih Salihoglu , Jeffrey Ullman %t2013 %cVLDB %f/VLDB/VLDB-2013-7464.pdf %*A Distributed Algorithm for Large-Scale Generalized Matching %@Faraz Makari Manshadi , Baruch Awerbuch , Rainer Gemulla , Rohit Khandekar , Julián Mestre , Mauro Sozio %t2013 %cVLDB %f/VLDB/VLDB-2013-7465.pdf %*Making Queries Tractable on Big Data with Preprocessing %@Wenfei Fan , Floris Geerts , Frank Neven %t2013 %cVLDB %f/VLDB/VLDB-2013-7466.pdf %*Hadoop's Adolescence: An analysis of Hadoop usage in scientific workloads %@Kai Ren , YongChul Kwon , Magdalena Balazinska , Bill Howe %t2013 %cVLDB %f/VLDB/VLDB-2013-7467.pdf %*A General Framework for Geo-Social Query Processing %@Nikos Armenatzoglou , Stavros Papadopoulos , Dimitris Papadias %t2013 %cVLDB %f/VLDB/VLDB-2013-7468.pdf %*Spatio-Textual Similarity Joins %@Panagiotis Bouros , Shen Ge , Nikos Mamoulis %t2013 %cVLDB %f/VLDB/VLDB-2013-7469.pdf %*Direction-Preserving Trajectory Simplification %@Cheng Long , Raymond Chi-Wing Wong , H. V. Jagadish %t2013 %cVLDB %f/VLDB/VLDB-2013-7470.pdf %*Efficient Error-tolerant Query Autocompletion %@Chuan Xiao , Jianbin Qin , Wei Wang , Yoshiharu Ishikawa , Koji Tsuda , Kunihiko Sadakane %t2013 %cVLDB %f/VLDB/VLDB-2013-7471.pdf %*Spatial Keyword Query Processing: An Experimental Evaluation %@Lisi Chen , Gao Cong , Christian S. Jensen , Dingming Wu %t2013 %cVLDB %f/VLDB/VLDB-2013-7472.pdf %*Continuous Cloud-Scale Query Optimization and Processing %@Nico Bruno , Sapna Jain , Jingren Zhou %t2013 %cVLDB %f/VLDB/VLDB-2013-7473.pdf %*Optimization Strategies for A/B Testing on HADOOP %@Andrii Cherniak , Huma Zaidi , Vladimir Zadorozhny %t2013 %cVLDB %f/VLDB/VLDB-2013-7474.pdf %*Piranha: Optimizing Short Jobs in Hadoop %@Khaled Elmeleegy, Turn Inc %t2013 %cVLDB %f/VLDB/VLDB-2013-7475.pdf %*Making Updates Disk-I/O Friendly Using SSDs %@Mohammad Sadoghi , Kenneth Ross , Mustafa Canim , Bishwaranjan Bhattacharjee %t2013 %cVLDB %f/VLDB/VLDB-2013-7476.pdf %*DesTeller: A System for Destination Prediction Based on Trajectories with Privacy Protection %@Andy Yuan Xue , Rui Zhang , Yu Zheng , Xing Xie , Jianhui Yu , Yong Tang %t2013 %cVLDB %f/VLDB/VLDB-2013-7477.pdf %*GroupFinder: A New Approach to Top-K Point-of-Interest Group Retrieval %@Kenneth Bøgh , Anders Skovsgaard , Christian S. Jensen %t2013 %cVLDB %f/VLDB/VLDB-2013-7478.pdf %*CrowdMiner: Mining association rules from the crowd %@Yael Amsterdamer , Yael Grossman , Tova Milo , Pierre Senellart (Télécom ParisTech) %t2013 %cVLDB %f/VLDB/VLDB-2013-7479.pdf %*TeRec: A Temporal Recommender System Over Tweet Stream %@Chen Chen , Hongzhi Yin , Junjie Yao , Bin Cui %t2013 %cVLDB %f/VLDB/VLDB-2013-7480.pdf %*iRoad: A Framework For Scalable Predictive Query Processing On Road Networks %@Abdeltawab Hendawi , Jie Bao , Mohamed Mokbel %t2013 %cVLDB %f/VLDB/VLDB-2013-7481.pdf %*SmartMonitor: Using Smart Devices to Perform Structural Health Monitoring %@Dimitrios Kotsakos , Panos Sakkos , Vana Kalogeraki , Dimitrios Gunopulos %t2013 %cVLDB %f/VLDB/VLDB-2013-7482.pdf %*EnviroMeter: A Platform for Querying Community-Sensed Data %@Saket Sathe , Arthur Oviedo , Dipanjan Chakraborty , Karl Aberer %t2013 %cVLDB %f/VLDB/VLDB-2013-7483.pdf %*EvenTweet: Online Localized Event Detection from Twitter %@Hamed Abdelhaq , Christian Sengstock , Michael Gertz %t2013 %cVLDB %f/VLDB/VLDB-2013-7484.pdf %*PhotoStand: A Map Query Interface for a Database of News Photos %@Hanan Samet , Marco D. Adelfio , Brendan C. Fruin , Michael D. Lieberman , Jagan Sankaranarayanan %t2013 %cVLDB %f/VLDB/VLDB-2013-7485.pdf %*Ringtail: A Generalized Nowcasting System %@Dolan Antenucci , Erdong Li , Shaobo Liu , Bochun Zhang , Mike Cafarella , Christopher Re %t2013 %cVLDB %f/VLDB/VLDB-2013-7486.pdf %*IPS: An Interactive Package Configuration System for Trip Planning %@Min Xie , Laks V. S. Lakshmanan , Peter Wood %t2013 %cVLDB %f/VLDB/VLDB-2013-7487.pdf %*R2-D2: a System to Support Probabilistic Path Prediction in Dynamic Environments %@Jingbo Zhou , Anthony K.H. Tung , Wei Wu , Wee Siong Ng %t2013 %cVLDB %f/VLDB/VLDB-2013-7488.pdf %*Just-in-time compilation for SQL query processing Bio: %@Stratis D. Viglas %t2013 %cVLDB %f/VLDB/VLDB-2013-7489.pdf %*Streaming Algorithms for k-core Decomposition %@Erdem Sarıyüce , Buğra Gedik , Gabriela Jacques-Silva , Kun-Lung Wu , Ümit Çatalyürek %t2013 %cVLDB %f/VLDB/VLDB-2013-7490.pdf %*Travel Cost Inference from Sparse, Spatio- Temporally Correlated Time Series Using Markov Models %@Bin Yang , Chenjuan Guo , Christian S. Jensen %t2013 %cVLDB %f/VLDB/VLDB-2013-7491.pdf %*Top-k Publish-Subscribe for Social Annotation of News %@Alexander Shraer , Maxim Gurevich , Marcus Fontoura , Vanja Josifovski %t2013 %cVLDB %f/VLDB/VLDB-2013-7492.pdf %*Sketch-based Geometric Monitoring of Distributed Stream Queries %@Minos Garofalakis (Technical University of Crete , Daniel Keren , Vasilis Samoladas %t2013 %cVLDB %f/VLDB/VLDB-2013-7493.pdf %*Efficient Recovery of Missing Events %@Jianmin Wang , Shaoxu Song , Xiaochen Zhu , Xuemin Lin %t2013 %cVLDB %f/VLDB/VLDB-2013-7494.pdf %*Skyline Operator on Anti-correlated Distributions %@Haichuan Shang , Masaru Kitsuregawa %t2013 %cVLDB %f/VLDB/VLDB-2013-7495.pdf %*Permuting Data on Random-Access Block Storage %@Risi Thonangi , Jun Yang %t2013 %cVLDB %f/VLDB/VLDB-2013-7496.pdf %*A Comparison of Knives for Bread Slicing %@Alekh Jindal , Endre Palatinus , Vladimir Pavlov , Jens Dittrich %t2013 %cVLDB %f/VLDB/VLDB-2013-7497.pdf %*Sharing Data and Work Across Concurrent Analytical Queries %@Iraklis Psaroudakis , Manos Athanassoulis , Anastasia Ailamaki %t2013 %cVLDB %f/VLDB/VLDB-2013-7498.pdf %*Efficient Implementation of Generalized Quantification in Relational Query Languages %@Antonio Badia , Bin Cao %t2013 %cVLDB %f/VLDB/VLDB-2013-7499.pdf %*NADEEF: A Generalized Data Cleaning System %@Amr Ebaid , Ahmed Elmagarmid , Ihab Ilyas , Mourad Ouzzani , Jorge-Arnulfo Quiane-Ruiz , Nan Tang , Si Yin %t2013 %cVLDB %f/VLDB/VLDB-2013-7500.pdf %*RecDB in Action: Recommendation Made Easy in Relational Databases %@Mohamed Sarwat , James Avery , Mohamed Mokbel %t2013 %cVLDB %f/VLDB/VLDB-2013-7501.pdf %*Graph Queries in a Next-Generation Datalog System %@Alexander Shkapsky , Kai Zeng , Carlo Zaniolo %t2013 %cVLDB %f/VLDB/VLDB-2013-7502.pdf %*Lazy ETL in Action: ETL Technology Dates Scientific Data %@Yağız Kargın , Milena Ivanova , Stefan Manegold , Martin Kersten , Ying Zhang %t2013 %cVLDB %f/VLDB/VLDB-2013-7503.pdf %*Scolopax: Exploratory Analysis of Scientific Data %@Alper Okcan , Mirek Riedewald, Biswanath Panda, Daniel Fink %t2013 %cVLDB %f/VLDB/VLDB-2013-7504.pdf %*PROPOLIS: Provisioned Analysis of Data-Centric Processes %@Daniel Deutch , Yuval Moskovitch , Val Tannen %t2013 %cVLDB %f/VLDB/VLDB-2013-7505.pdf %*Feature Selection in Enterprise Analytics: A Demonstration using an R-based Data Analytics System %@Pradap Konda , Arun Kumar , Christopher Re , Vaishnavi Sashikanth %t2013 %cVLDB %f/VLDB/VLDB-2013-7506.pdf %*PLASMA-HD: Probing the LAttice Structure and MAkeup of High-dimensional Data %@David Fuhry , Yang Zhang , Venu Satuluri , Arnab Nandi , Srinivasan Parthasarathy %t2013 %cVLDB %f/VLDB/VLDB-2013-7507.pdf %*IBminer: A Text Mining Tool for Constructing and Populating InfoBox Databases and Knowledge Bases %@Hamid Mousavi , Shi Gao , Carlo Zaniolo %t2013 %cVLDB %f/VLDB/VLDB-2013-7508.pdf %*Mining and Linking Patterns across Live Data Streams and Stream Archives %@Di Yang , Kaiyu Zhao , Maryam Hasan , Hanyuan Lu , Elke Rundensteiner , Matthew Ward %t2013 %cVLDB %f/VLDB/VLDB-2013-7509.pdf %*User Analytics with UbeOne: Insights into Web Printing %@Georgia Koutrika , Qian Lin , Jerry Liu %t2013 %cVLDB %f/VLDB/VLDB-2013-7510.pdf %*Actively Soliciting Feedback for Query Answers in Keyword Search-Based Data Integration %@Zhepeng Yan , Nan Zheng , Zachary Ives , Partha Talukdar , Cong Yu %t2013 %cVLDB %f/VLDB/VLDB-2013-7511.pdf %*Query Processing under GLAV Mappings for Relational and Graph Databases %@Diego Calvanese , Giuseppe De Giacomo (Sapienza Università di Roma), Maurizio Lenzerini (Sapienza Università di Roma), Moshe Vardi %t2013 %cVLDB %f/VLDB/VLDB-2013-7512.pdf %*Discovering Linkage Points over Web Data %@Oktie Hassanzadeh , Ken Pu , Soheil Hassas Yeganeh , Renee Miller , Lucian Popa , Mauricio Hernandez , Howard Ho %t2013 %cVLDB %f/VLDB/VLDB-2013-7513.pdf %*Reducing Uncertainty of Schema Matching via Crowdsourcing %@Chen Zhang , Lei Chen , Hosagrahar Jagadish , Chen Cao %t2013 %cVLDB %f/VLDB/VLDB-2013-7514.pdf %*Less is More: Selecting Sources Wisely for Integration %@Xin Luna Dong , Barna Saha , Divesh Srivastava %t2013 %cVLDB %f/VLDB/VLDB-2013-7515.pdf %*Mobility and Social Networking: A Data Management Perspective Bio: Bio: %@Mohamed F. Mokbel , Mohamed Sarwat %t2013 %cVLDB %f/VLDB/VLDB-2013-7516.pdf %*Towards Predicting Query Execution Time for Concurrent and Dynamic Database Workloads %@Wentao Wu , Yun Chi , Hakan Hacigumus , Jeffrey Naughton %t2013 %cVLDB %f/VLDB/VLDB-2013-7517.pdf %*Lightweight Locking For Main Memory Database Systems %@Kun Ren , Alexander Thomson , Daniel Abadi %t2013 %cVLDB %f/VLDB/VLDB-2013-7518.pdf %*Supporting User-Defined Functions on Uncertain Data %@Thanh Tran (UMass , Yanlei Diao , Charles Sutton , Anna Liu (UMass %t2013 %cVLDB %f/VLDB/VLDB-2013-7519.pdf %*On Scaling Up Sensitive Data Auditing %@Yupeng Fu (University of California , Raghav Kaushik , Ravi Ramamurthy %t2013 %cVLDB %f/VLDB/VLDB-2013-7520.pdf %*On the Complexity of Query Result Diversification %@Ting Deng , Wenfei Fan %t2013 %cVLDB %f/VLDB/VLDB-2013-7521.pdf %*Senbazuru: A Prototype Spreadsheet Database Management System %@Shirley Zhe Chen , Mike Cafarella , Jun Chen , Daniel Prevo, Junfeng Zhuang %t2013 %cVLDB %f/VLDB/VLDB-2013-7522.pdf %*ReqFlex: Fuzzy Queries for Everyone %@Grégory SMITS , Olivier PIVERT , Thomas GIRAULT %t2013 %cVLDB %f/VLDB/VLDB-2013-7523.pdf %*Comprehensive and Interactive Temporal Query Processing with SAP HANA %@Martin Kaufmann (ETH Zürich), Panagiotis Vagenas , Peter Fischer (Albert-Ludwigs-Universität Freiburg, Germany), Donald Kossmann , Franz Färber %t2013 %cVLDB %f/VLDB/VLDB-2013-7524.pdf %*Functions Are Data Too (Defunctionalization for PL/SQL) %@Torsten Grust (Universität Tübingen, Germany), Nils Schweinsberg (Universität Tübingen, Germany), Alexander Ulrich (Universität Tübingen, Germany) %t2013 %cVLDB %f/VLDB/VLDB-2013-7525.pdf %*QUEST: A Keyword Search System for Relational Data based on Semantic and Machine Learning Techniques %@Sonia Bergamaschi, Francesco Guerra, and Matteo Interlandi (Università di Modena e Reggio Emilia), Raquel Trillo-Lado , Yannis Velegrakis (Università di Trento) %t2013 %cVLDB %f/VLDB/VLDB-2013-7526.pdf %*ROSeAnn: Reconciling Opinions of Semantic Annotators %@Luying Chen , Stefano Ortona , Giorgio Orsi , Michael Benedikt %t2013 %cVLDB %f/VLDB/VLDB-2013-7527.pdf %*SkySuite: A Framework of Skyline-Join Operators for Static and Stream Environments %@Mithila Nagendra , K. Selcuk Candan %t2013 %cVLDB %f/VLDB/VLDB-2013-7528.pdf %*MASTRO STUDIO: Managing Ontology-Based Data Access applications %@Cristina Civili , Marco Console , Giuseppe De Giacomo (Sapienza Università di Roma), Domenico Lembo , Maurizio Lenzerini (Sapienza Università di Roma), Lorenzo Lepore , Riccardo Mancini , Antonella Poggi , Riccardo Rosati , Marco Ruzzi , Valerio Santarelli , Domenico Fabio Savo %t2013 %cVLDB %f/VLDB/VLDB-2013-7529.pdf %*PAQO: A Preference-Aware Query Optimizer for PostgreSQL %@Nicholas L. Farnan , Adam J. Lee , Panos K. Chrysanthis , Ting Yu %t2013 %cVLDB %f/VLDB/VLDB-2013-7530.pdf %*eSkyline: Processing Skyline Queries over Encrypted Data %@Suvarna Bothe , Panagiotis Karras , Akrivi Vlachou %t2013 %cVLDB %f/VLDB/VLDB-2013-7531.pdf %*GestureQuery: A Multitouch Database Query Interface %@Lilong Jiang , Michael Mandel , Arnab Nandi %t2013 %cVLDB %f/VLDB/VLDB-2013-7532.pdf %*Complete Approximations of Incomplete Queries %@Ognjen Savkovic , Paramita Mirza , Alex Tomasi , Werner Nutt %t2013 %cVLDB %f/VLDB/VLDB-2013-7533.pdf %*POIKILO: A Tool for Evaluating the Results of Diversification Models and Algorithms %@Marina Drosou , Evaggelia Pitoura %t2013 %cVLDB %f/VLDB/VLDB-2013-7534.pdf %*Why it is time for a HyPE: A Hybrid Query Processing Engine for Efficient GPU Coprocessing in DBMS %@Sebastian Breß, University of Magdeburg %t2013 %cVLDB %f/VLDB/VLDB-2013-7535.pdf %*Storing and Processing Temporal Data in a Main Memory Column Store %@Martin Kaufmann, ETH Zurich %t2013 %cVLDB %f/VLDB/VLDB-2013-7536.pdf %*Database Support for Unstructured Meshes %@Alireza Rezaei Mahdiraji, Jacobs University %t2013 %cVLDB %f/VLDB/VLDB-2013-7537.pdf %*(Invited Talk) Introducing Access Control in Webdamlog %@Serge Abiteboul %t2013 %cVLDB %f/VLDB/VLDB-2013-7538.pdf %*First-Class Functions for First-Order Database Engines %@Torsten Grust (Universität Tübingen) and Alexander Ulrich (Universität Tübingen) %t2013 %cVLDB %f/VLDB/VLDB-2013-7539.pdf %*A Thin Monitoring Layer for Top-k Aggregation Queries over a Database %@Foteini Alvanaki & Sebastian Michel %t2013 %cVLDB %f/VLDB/VLDB-2013-7540.pdf %*Progressive Ranking Based on a Dominance List %@Sadoun Isma, Yann Loyer & Karine Zeitouni %t2013 %cVLDB %f/VLDB/VLDB-2013-7541.pdf %*Wearable Queries: Adapting Common Retrieval Needs to Data and Users %@Barbara Catania, Giovanna Guerrini, Alberto Belussi, Federica Mandreoli, Riccardo Martoglia & Wilma Penzo %t2013 %cVLDB %f/VLDB/VLDB-2013-7542.pdf %*Keyword Search and Evaluation over Relational Databases: an Outlook to the Future %@Sonia Bergamaschi, Nicola Ferro, Francesco Guerra, Gianmaria Silvello %t2013 %cVLDB %f/VLDB/VLDB-2013-7543.pdf %*Scalable Transactions across Heterogeneous NoSQL Key-Value Data Stores %@Akon Dey, University of Sydney %t2013 %cVLDB %f/VLDB/VLDB-2013-7544.pdf %*Safe-Zones for Monitoring Distributed Streams %@Daniel Keren , Guy Sagy , Amir Abboud , Izchak Sharfman , Assaf Schuster , David Ben-David %t2013 %cVLDB %f/VLDB/VLDB-2013-7545.pdf %*Communication-Efficient Distributed Online Prediction using Dynamic Model Synchronizations %@Mario Boley , Izchak Sharfman , Daniel Keren , Michael Kamp , Assaf Schuster %t2013 %cVLDB %f/VLDB/VLDB-2013-7546.pdf %*Communication-efficient Outlier Detection for Scale-out Systems %@Moshe Gabel , Daniel Keren , Assaf Schuster %t2013 %cVLDB %f/VLDB/VLDB-2013-7547.pdf %*Managing Schema Evolution in NoSQL Data Stores %@Stefanie Scherzinger , Meike Klettke , and Uta Störl %t2013 %cVLDB %f/VLDB/VLDB-2013-7548.pdf %*Peckalytics: Analyzing Experts and Interests on Twitter %@Alex Cheng, Nilesh Bansal, Nick Koudas %t2013 %cVLDB %f/VLDB/VLDB-2013-7549.pdf %*Recommendation by Examples %@Rubi Boim, Tova Milo %t2013 %cVLDB %f/VLDB/VLDB-2013-7550.pdf %*On the Modelling of Ranking Algorithms in Probabilistic Datalog %@Thomas Roelleke & Marco Bonzanini %t2013 %cVLDB %f/VLDB/VLDB-2013-7551.pdf %*Ranking and New Database Architectures %@Justin Levandoski %t2013 %cVLDB %f/VLDB/VLDB-2013-7552.pdf %*Universal Indexing of Arbitrary Similarity Models %@Tomas Bartos, Charles University in Prague %t2013 %cVLDB %f/VLDB/VLDB-2013-7553.pdf %*Realtime Analysis of Information Diffusion in Social Media %@Io Taxidou, University of Freiburg %t2013 %cVLDB %f/VLDB/VLDB-2013-7554.pdf %*Mining Frequent Patterns with Differential Privacy %@Luca Bonomi, Emory University %t2013 %cVLDB %f/VLDB/VLDB-2013-7555.pdf %*Efficiency and Security in Similarity Cloud Services %@Stepan Kozak, Masaryk University %t2013 %cVLDB %f/VLDB/VLDB-2013-7556.pdf %*Elastic Complex Event Processing under Varying Query Load %@Thomas Heinze , Yuanzhen Ji , Yinying Pan , Franz Josef Grüneberger , Zbigniew Jerzak , Christof Fetzer %t2013 %cVLDB %f/VLDB/VLDB-2013-7557.pdf %*Adaptive Selective Replication for Complex Event Processing Systems %@Franz Josef Grüneberger , Thomas Heinze , Pascal Felber %t2013 %cVLDB %f/VLDB/VLDB-2013-7558.pdf %*Dynamic Partitioning of Big Hierarchical Graphs %@Vasilis Spyropoulos , Yannis Kotidis %t2013 %cVLDB %f/VLDB/VLDB-2013-7559.pdf %*Scalable and Robust Management of Dynamic Graph Data %@Alan Labouseur , Paul Olsen , Jeong-Hyon Hwang %t2013 %cVLDB %f/VLDB/VLDB-2013-7560.pdf %*Declarative Ajax Web Applications through SQL++ on a Unified Application State %@Yupeng Fu , Kian Win Ong , and Yannis Papakonstantinou %t2013 %cVLDB %f/VLDB/VLDB-2013-7561.pdf %*Social Search Queries in Time %@Georgia Koloniari, Kostas Stefanidis %t2013 %cVLDB %f/VLDB/VLDB-2013-7562.pdf %*Coping with the Persistent Coldstart Problem %@Siarhei Bykau, Georgia Koutrika and Yannis Velegrakis %t2013 %cVLDB %f/VLDB/VLDB-2013-7563.pdf %*Automatic ontology based User Profile Learning from heterogeneous Web Resources in a Big Data Context %@Anett Hoppe, Universite de Bourgogne %t2013 %cVLDB %f/VLDB/VLDB-2013-7564.pdf %*Domain Specific Multistage Query Language for Medical Document Repositories %@Aastha Madaan, University of Aizu %t2013 %cVLDB %f/VLDB/VLDB-2013-7565.pdf %*Getting Unique Solution in Data Exchange %@Nhung Ngo, Free University of Bolzano %t2013 %cVLDB %f/VLDB/VLDB-2013-7566.pdf %*Fast Cartography for Data Explorers %@Thibault Sellam, CWI %t2013 %cVLDB %f/VLDB/VLDB-2013-7567.pdf %*Towards Elastic Stream Processing: Patterns and Infrastructure %@Kai-Uwe Sattler , Felix Beier %t2013 %cVLDB %f/VLDB/VLDB-2013-7568.pdf %*Task Graphs of Stream Mining Algorithms %@Sayaka Akioka %t2013 %cVLDB %f/VLDB/VLDB-2013-7569.pdf %*Large-scale Online Mobility Monitoring with Exponential Histograms %@Christine Kopp , Michael Mock , Odysseas Papapetrou , Michael May %t2013 %cVLDB %f/VLDB/VLDB-2013-7570.pdf %*Multi-Stage Malicious Click Detection on Large Scale Web Advertising Data %@Leyi Song , Xueqing Gong , Xiaofeng He , Rong Zhang , Aoying Zhou %t2013 %cVLDB %f/VLDB/VLDB-2013-7571.pdf %*Learning Schemas for Unordered XML %@Radu Ciucanu and Slawek Staworko %t2013 %cVLDB %f/VLDB/VLDB-2013-7572.pdf %*Static Enforceability of XPath-Based Access Control Policies %@James Cheney %t2013 %cVLDB %f/VLDB/VLDB-2013-7573.pdf %*XPath Satisfiability with Parent Axes or Qualifiers Is Tractable under Many of Real-World DTDs %@Yasunori Ishihara , Nobutaka Suzuki , Kenji Hashimoto , Shogo Shimizu (Gakushuin Women’s College), and Toru Fujiwara %t2013 %cVLDB %f/VLDB/VLDB-2013-7574.pdf %*Front Matter %@H. V. Jagadish and Aoying Zhou %t2014 %cVLDB %f/VLDB/VLDB-2014-7575.pdf %*Efficient and Effective KNN Sequence Search with Approximate n-grams %@Xiaoli Wang, Xiaofeng Ding, Anthony Tung, Zhenjie Zhang %t2014 %cVLDB %f/VLDB/VLDB-2014-7576.pdf %*More is Simpler: Effectively and Efficiently Assessing Node-Pair Similarities Based on Hyperlinks %@Weiren Yu, Xuemin Lin, Wenjie Zhang, Lijun Chang, Jian Pei %t2014 %cVLDB %f/VLDB/VLDB-2014-7577.pdf %*An Approach towards the Study of Symmetric Queries %@Marc Gyssens, Jan Paredaens, Dirk Van Gucht, Jef Wijsen, Yuqing Wu %t2014 %cVLDB %f/VLDB/VLDB-2014-7578.pdf %*CPU Sharing Techniques for Performance Isolation in Multitenant Relational Database-as-a-Service %@Sudipto Das, Vivek Narasayya, Feng Li, Manoj Syamala %t2014 %cVLDB %f/VLDB/VLDB-2014-7579.pdf %*Authenticating Top-k Queries in Location-based Services with Confidentiality %@Qian Chen, Haibo Hu, Jianling Xu %t2014 %cVLDB %f/VLDB/VLDB-2014-7580.pdf %*Toward a Distance Oracle for Billion-Node Graphs %@Zichao Qi, Yanghua Xiao, Bin Shao, Haixun Wang %t2014 %cVLDB %f/VLDB/VLDB-2014-7581.pdf %*Finding Shortest Paths on Terrains by Killing Two Birds with One Stone %@Manohar Kaul, Raymond Chi-Wing Wong, Bin Yang, Christian Jensen %t2014 %cVLDB %f/VLDB/VLDB-2014-7582.pdf %*Multi-Core, Main-Memory Joins: Sort vs. Hash Revisited %@Cagri Balkesen, Gustavo Alonso, Jens Teubner, Tamer Ozsu %t2014 %cVLDB %f/VLDB/VLDB-2014-7583.pdf %*Front Matter %@Gao Cong and Jens Dittrich %t2014 %cVLDB %f/VLDB/VLDB-2014-7584.pdf %*The Uncracked Pieces in Database Cracking %@Felix Martin Schuhknecht, Alekh Jindal, Jens Dittrich %t2014 %cVLDB %f/VLDB/VLDB-2014-7585.pdf %*Diversity based Relevance Feedback for Time Series Search %@Bahaeddin Eravci, Hakan Ferhatosmanoglu %t2014 %cVLDB %f/VLDB/VLDB-2014-7586.pdf %*Storage Management in the NVRAM Era %@Steven Pelley, Thomas F. Wenisch, Brian T. Gold, Bill Bridge %t2014 %cVLDB %f/VLDB/VLDB-2014-7587.pdf %*Front Matter %@Zachary Ives %t2014 %cVLDB %f/VLDB/VLDB-2014-7588.pdf %*Online Ordering of Overlapping Data Sources %@Mariam Salloum, Xin Luna Dong, Divesh Srivastava, Vassilis J. Tsotras %t2014 %cVLDB %f/VLDB/VLDB-2014-7589.pdf %*Multi-Query Optimization in MapReduce Framework %@Guoping Wang, Chee-Yong Chan %t2014 %cVLDB %f/VLDB/VLDB-2014-7590.pdf %*Attraction and Avoidance Detection from Movements %@Zhenhui Li, Bolin Ding, Fei Wu, Tobias Kin Hou Lei, Roland Kays, Margaret C. Crofoot %t2014 %cVLDB %f/VLDB/VLDB-2014-7591.pdf %*A Partition-Based Approach to Structure Similarity Search %@Xiang Zhao, Chuan Xiao, Xuemin Lin, Qing Liu, Wenjie Zhang %t2014 %cVLDB %f/VLDB/VLDB-2014-7592.pdf %*Highly Available Transactions: Virtues and Limitations %@Peter Bailis, Aaron Davidson, Alan Fekete, Ali Ghodsi, Joseph M. Hellerstein, Ion Stoica %t2014 %cVLDB %f/VLDB/VLDB-2014-7593.pdf %*From "Think Like a Vertex" to "Think Like a Graph" %@Yuanyuan Tian, Andrey Balmin, Severin Andreas Corsten, Shirish Tatikonda, John McPherson %t2014 %cVLDB %f/VLDB/VLDB-2014-7594.pdf %*Probabilistic Nearest Neighbor Queries on Uncertain Moving Object Trajectories %@Johannes Niedermayer, Andreas Zufle, Tobias Emrich, Matthias Renz, Nikos Mamoulis, Lei Chen, Hans-P eter Kriegel %t2014 %cVLDB %f/VLDB/VLDB-2014-7595.pdf %*Front Matter %@Martin Kersten %t2014 %cVLDB %f/VLDB/VLDB-2014-7596.pdf %*Delta: Scalable Data Dissemination under Capacity Constraints %@Konstantinos Karanasos, Asterios Katsifodimos, Ioana Manolescu %t2014 %cVLDB %f/VLDB/VLDB-2014-7597.pdf %*GeoScope: Online Detection of Geo-Correlated Information Trends in Social Networks %@Ceren Budak, Theodore Georgiou, Divyakant Agrawal, Amr El Abbadi %t2014 %cVLDB %f/VLDB/VLDB-2014-7598.pdf %*Optimization for iterative queries on MapReduce %@Makoto Onizuka, Hiroyuki Kato, Soichiro Hidaka, Keisuke Nakano, Zhenjiang Hu %t2014 %cVLDB %f/VLDB/VLDB-2014-7599.pdf %*Willingness Optimization for Social Group Activity %@Hong-Han Shuai, De-Nian Yang, Philip S. Yu, Ming-Syan Chen %t2014 %cVLDB %f/VLDB/VLDB-2014-7600.pdf %*High Performance Stream Query Processing With Correlation-Aware Partitioning %@Lei Cao, Elke A. Rundensteiner %t2014 %cVLDB %f/VLDB/VLDB-2014-7601.pdf %*OLTP-Bench: An Extensible Testbed for Benchmarking Relational Databases %@Djellel Eddine Difallah, Andrew Pavlo, Carlo Curino, Philippe Cudre-Mauroux %t2014 %cVLDB %f/VLDB/VLDB-2014-7602.pdf %*Gestural Query Specification %@Arnab Nandi, Lilong Jiang, Michael Mandel %t2014 %cVLDB %f/VLDB/VLDB-2014-7603.pdf %*Scalable Discovery of Unique Column Combinations %@Arvid Heise, Jorge-Arnulfo, Quiane-Ruiz, Ziawasch Abedjan, Anja Jentzsch, Felix Naumann %t2014 %cVLDB %f/VLDB/VLDB-2014-7604.pdf %*Earth Mover's Distance based Similarity Search at Scale %@Yu Tang, Leong Hou U, Yilun Cai, Nikos Mamoulis, Reynold Cheng %t2014 %cVLDB %f/VLDB/VLDB-2014-7605.pdf %*SeeDB: Visualizing Database Queries Efficiently %@null %t2014 %cVLDB %f/VLDB/VLDB-2014-7606.pdf %*Front Matter %@Michael Carey %t2014 %cVLDB %f/VLDB/VLDB-2014-7607.pdf %*MaaT: Effective and scalable coordination of distributed transactions in the cloud %@Hatem A. Mahmoud, Vaibhav Arora, Faisal Nawab, Divyakant Agrawal, Amr El Abbadi %t2014 %cVLDB %f/VLDB/VLDB-2014-7608.pdf %*A Data- and Workload-Aware Query Answering Algorithm for Range Queries Under Differential Privacy %@Chao Li, Michael Hay, Gerome Miklau, Yue Wang %t2014 %cVLDB %f/VLDB/VLDB-2014-7609.pdf %*Certain Query Answering in Partially Consistent Databases %@Sergio Greco, Fabian Pijcke, Jef Wijsen %t2014 %cVLDB %f/VLDB/VLDB-2014-7610.pdf %*Exemplar Queries: Give me an Example of What You Need %@Davide Mottin, Matteo Lissandrini, Yannis Velegrakis, Themis Palpanas %t2014 %cVLDB %f/VLDB/VLDB-2014-7611.pdf %*An efficient reconciliation algorithm for social networks %@Nitish Korula, Silvio Lattanzi %t2014 %cVLDB %f/VLDB/VLDB-2014-7612.pdf %*Computing k-Regret Minimizing Sets %@Sean Chester, Alex Thomo, S. Venkatesh, Sue Whitesides %t2014 %cVLDB %f/VLDB/VLDB-2014-7613.pdf %*Reverse Top-k Search using Random Walk with Restart %@Adams Wei Yu, Nikos Mamoulis, Hao Su %t2014 %cVLDB %f/VLDB/VLDB-2014-7614.pdf %*Write-limited sorts and joins for persistent memory %@Stratis D. Viglas %t2014 %cVLDB %f/VLDB/VLDB-2014-7615.pdf %*Folk-IS: Opportunistic Data Services in Least Developed Countries %@N. Anciaux, L. Bouganim, T. Delot, S. Ilarri, L. Kloul, N. Mitton, P. Pucheral %t2014 %cVLDB %f/VLDB/VLDB-2014-7616.pdf %*Front Matter %@Graham Cormode %t2014 %cVLDB %f/VLDB/VLDB-2014-7617.pdf %*Shared Workload Optimization %@Georgios Giannikis, Darko Makreshanski, Gustavo Alonso, Donald Kossmann %t2014 %cVLDB %f/VLDB/VLDB-2014-7618.pdf %*Scalable and Adaptive Online Joins %@Mohammed Elseidy, Abdallah Elguindy, Aleksandar Vitorovic, Christoph Koch %t2014 %cVLDB %f/VLDB/VLDB-2014-7619.pdf %*Support the Data Enthusiast: Challenges for Next-Generation Data-Analysis Systems %@Kristi Morton, Magdalena Balazinska, Dan Grossman, Jock Mackinlay %t2014 %cVLDB %f/VLDB/VLDB-2014-7620.pdf %*A Provenance Framework for Data-Dependent Process Analysis %@Daniel Deutch, Yuval Moskovitch, Val Tannen %t2014 %cVLDB %f/VLDB/VLDB-2014-7621.pdf %*Tracking Entities in the Dynamic World: A Fast Algorithm for Matching Temporal Records %@Yueh-Hsuan Chiang, AnHai Doan, Jeffrey F. Naughton %t2014 %cVLDB %f/VLDB/VLDB-2014-7622.pdf %*Edelweiss: Automatic Storage Reclamation for Distributed Programming %@Neil Conway, Peter Alvaro, Emily Andrews, Joseph M. Hellerstein %t2014 %cVLDB %f/VLDB/VLDB-2014-7623.pdf %*Front Matter %@Chen Li and Volker Markl %t2014 %cVLDB %f/VLDB/VLDB-2014-7624.pdf %*Rank Join Queries in NoSQL Databases %@Nikos Ntarmos, Ioannis Patlakas, Peter Triantafillou %t2014 %cVLDB %f/VLDB/VLDB-2014-7625.pdf %*Biperpedia: An Ontology for Search Applications %@Rahul Gupta, Alon Halevy, Xuezhi Wang, Steven Euijong Whang, Fei Wu %t2014 %cVLDB %f/VLDB/VLDB-2014-7626.pdf %*GRAMI: Frequent Subgraph and Pattern Mining in a Single Large Graph %@Mohammed Elseidy, Ehab Abdelhamid, Spiros Skiadopoulos, Panos Kalnis %t2014 %cVLDB %f/VLDB/VLDB-2014-7627.pdf %*Lightweight Indexing of Observational Data in Log-Structured Storage %@Sheng Wang, David Maier, Beng Chin Ooi %t2014 %cVLDB %f/VLDB/VLDB-2014-7628.pdf %*epiC: an Extensible and Scalable System for Processing Big Data %@Dawei Jiang, Gang Chen, Beng Chin Ooi, Kian-Lee Tan, Sai Wu %t2014 %cVLDB %f/VLDB/VLDB-2014-7629.pdf %*Hybrid Parallelization Strategies for Large-Scale Machine Learning in SystemML %@Matthias Boehm, Shirish Tatikonda, Berthold Reinwald, Prithviraj Sen, Yuanyuan Tian, Douglas R. Burdick, Shivakumar Vaithyanathan %t2014 %cVLDB %f/VLDB/VLDB-2014-7630.pdf %*Schemaless and Structureless Graph Querying %@Shengqi Yang, Yinghui Wu, Huan Sun, Xifeng Yan %t2014 %cVLDB %f/VLDB/VLDB-2014-7631.pdf %*Optimizing Graph Algorithms on Pregel-like Systems %@Semih Salihoglu, Jennifer Widom %t2014 %cVLDB %f/VLDB/VLDB-2014-7632.pdf %*Toward Computational Fact-Checking %@You Wu, Pankaj K. Agarwal, Chengkai Li, Jun Yang, Cong Yu %t2014 %cVLDB %f/VLDB/VLDB-2014-7633.pdf %*Front Matter %@Divesh Srivastava %t2014 %cVLDB %f/VLDB/VLDB-2014-7634.pdf %*A Principled Approach to Bridging the Gap between Graph Data and their Schemas %@Marcelo Arenas, Gonzalo Diaz, Achille Fokoue, Anastasios Kementsietsidis, Kavitha Srinivas %t2014 %cVLDB %f/VLDB/VLDB-2014-7635.pdf %*An Efficient Publish/Subscribe Index for ECommerce Databases %@Dongxiang Zhang, Chee-Yong Chan, Kian-Lee Tan %t2014 %cVLDB %f/VLDB/VLDB-2014-7636.pdf %*String Similarity Joins: An Experimental Evaluation %@Yu Jiang, Guoliang Li, Jianhua Feng, Wen-Syan Li %t2014 %cVLDB %f/VLDB/VLDB-2014-7637.pdf %*Calibrating Data to Sensitivity in Private Data Analysis %@Davide Proserpio, Sharon Goldberg, Frank McSherry %t2014 %cVLDB %f/VLDB/VLDB-2014-7638.pdf %*Effective Multi-Modal Retrieval based on Stacked Auto-Encoders %@Wei Wang, Beng Chin Ooi, Xiaoyan Yang, Dongxiang Zhang, Yueting Zhuang %t2014 %cVLDB %f/VLDB/VLDB-2014-7639.pdf %*Front Matter %@H. V. Jagadish %t2014 %cVLDB %f/VLDB/VLDB-2014-7640.pdf %*PRESS: A Novel Framework of Trajectory Compression in Road Networks %@Renchu Song, Weiwei Sun, Baihua Zheng, Yu Zheng %t2014 %cVLDB %f/VLDB/VLDB-2014-7641.pdf %*Finding the Cost-Optimal Path with Time Constraint over Time-Dependent Graphs %@Yajun Yang, Hong Gao, Jeffrey Xu Yu, Jianzhong Li %t2014 %cVLDB %f/VLDB/VLDB-2014-7642.pdf %*Optimal Crowd-Powered Rating and Filtering Algorithms %@Aditya Parameswaran, Stephen Boyd, Hector Garcia-Molina, Ashish Gupta, Neoklis Polyzotis, Jennifer Widom %t2014 %cVLDB %f/VLDB/VLDB-2014-7643.pdf %*Incremental Record Linkage %@Anja Gruenheid, Xin Luna Dong, Divesh Srivastava %t2014 %cVLDB %f/VLDB/VLDB-2014-7644.pdf %*Low-Latency Handshake Join %@Pratanu Roy, Jens Teubner, Rainer Gemulla %t2014 %cVLDB %f/VLDB/VLDB-2014-7645.pdf %*Path Problems in Temporal Graphs %@Huanhuan Wu, James Cheng, Silu Huang, Yiping Ke, Yi Lu, Yanyan Xu %t2014 %cVLDB %f/VLDB/VLDB-2014-7646.pdf %*Retrieving Regions of Interest for User Exploration %@Xin Cao, Gao Cong, Christian S. Jensen, Man Lung Yiu %t2014 %cVLDB %f/VLDB/VLDB-2014-7647.pdf %*SK-LSH: An Efficient Index Structure for Approximate Nearest Neighbor Search %@Yingfan Liu, Jiangtao Cui, Zi Huang, Hui Li, Heng Tao Shen %t2014 %cVLDB %f/VLDB/VLDB-2014-7648.pdf %*On Arbitrage-free Pricing for General Data Queries %@Bing-Rong Lin, Daniel Kifer %t2014 %cVLDB %f/VLDB/VLDB-2014-7649.pdf %*Splitter: Mining Fine-Grained Sequential Patterns in Semantic Trajectories %@Chao Zhang, Jiawei Han, Lidan Shou, Jiajun Lu, Thomas La Porta %t2014 %cVLDB %f/VLDB/VLDB-2014-7650.pdf %*Towards Building Wind Tunnels for Data Center Design %@Avrilia Floratou, Frank Bertsch, Jignesh M. Patel, Georgios Laskaris %t2014 %cVLDB %f/VLDB/VLDB-2014-7651.pdf %*Front Matter %@Sharad Mehrotra %t2014 %cVLDB %f/VLDB/VLDB-2014-7652.pdf %*Reverse k-Ranks Query %@Zhao Zhang, Cheqing Jin, Qiangqiang Kang %t2014 %cVLDB %f/VLDB/VLDB-2014-7653.pdf %*M4: A Visualization-Oriented Time Series Data Aggregation %@Uwe Jugel, Zbigniew Jerzak, Volker Markl %t2014 %cVLDB %f/VLDB/VLDB-2014-7654.pdf %*Continuous Matrix Approximation on Distributed Data %@Mina Ghashami, Jeff M. Phillips, Feifei Li %t2014 %cVLDB %f/VLDB/VLDB-2014-7655.pdf %*An Evaluation of the Advantages and Disadvantages of Deterministic Database Systems %@Kun Ren, Alexander Thomson, Daniel J. Abadi %t2014 %cVLDB %f/VLDB/VLDB-2014-7656.pdf %*Efficient In-memory Data Management: An Analysis %@Hao Zhang, Bogdan Marius Tudor, Gang Chen, Beng Chin Ooi %t2014 %cVLDB %f/VLDB/VLDB-2014-7657.pdf %*Workload Matters: Why RDF Databases Need a New Design %@Gunes Aluc, M. Tamer Ozsu, Khuzaima Daudjee %t2014 %cVLDB %f/VLDB/VLDB-2014-7658.pdf %*Storage Management in AsterixDB %@Sattam Alsubaiee, Alexander Behm, Vinayak Borkar, Zachary Heilbron, Young-Seok Kim, Michael J. Carey, Markus Dreseler, Chen Li %t2014 %cVLDB %f/VLDB/VLDB-2014-7659.pdf %*Building Efficient Query Engines in a High-Level Language %@Yannis Klonatos, Christoph Koch, Tiark Rompf, Hassan Chafi %t2014 %cVLDB %f/VLDB/VLDB-2014-7660.pdf %*Scalable Logging through Emerging Non-Volatile Memory %@Tianzheng Wang, Ryan Johnson %t2014 %cVLDB %f/VLDB/VLDB-2014-7661.pdf %*When Data Management Systems Meet Approximate Hardware: Challenges and Opportunities %@Bingsheng He %t2014 %cVLDB %f/VLDB/VLDB-2014-7662.pdf %*From Data Fusion to Knowledge Fusion %@Xin Luna Dong, Evgeniy Gabrilovich, Geremy Heitz, Wilko Horn, Kevin Murphy, Shaohua Sun, Wei Zhang %t2014 %cVLDB %f/VLDB/VLDB-2014-7663.pdf %*On k-Path Covers and their Applications %@Stefan Funke, Andre Nusser, Sabine Storandt %t2014 %cVLDB %f/VLDB/VLDB-2014-7664.pdf %*The Case for Data Visualization Management Systems %@Eugene Wu, Leilani Battle, Samuel R. Madden %t2014 %cVLDB %f/VLDB/VLDB-2014-7665.pdf %*WideTable: An Accelerator for Analytical Data Processing %@Yinan Li, Jignesh M. Patel %t2014 %cVLDB %f/VLDB/VLDB-2014-7666.pdf %*A Framework for Protecting Worker Location Privacy in Spatial Crowdsourcing %@Hien To, Gabriel Ghinita, Cyrus Shahabi %t2014 %cVLDB %f/VLDB/VLDB-2014-7667.pdf %*Front Matter %@Lidan Shou %t2014 %cVLDB %f/VLDB/VLDB-2014-7668.pdf %*Trekking Through Siberia: Managing Cold Data in a Memory-Optimized Database %@Ahmed Eldawy, Justin Levandoski, Per-Åke Larson %t2014 %cVLDB %f/VLDB/VLDB-2014-7669.pdf %*The Case for Personal Data-Driven Decision Making %@Jennie Duggan %t2014 %cVLDB %f/VLDB/VLDB-2014-7670.pdf %*ConfluxDB: Multi-Master Replication for Partitioned Snapshot Isolation Databases %@Prima Chairunnanda, Khuzaima Daudjee, M. Tamer Özsu %t2014 %cVLDB %f/VLDB/VLDB-2014-7671.pdf %*Υ-DB: Managing scientific hypotheses as uncertain data %@Bernardo Goncalves, Fabio Porto %t2014 %cVLDB %f/VLDB/VLDB-2014-7672.pdf %*Ibex - An Intelligent Storage Engine with Support for Advanced SQL Off-loading %@Louis Woods, Zsolt Istvan, Gustavo Alonso %t2014 %cVLDB %f/VLDB/VLDB-2014-7673.pdf %*NOMAD: Nonlocking, stOchastic Multi-machine algorithm for Asynchronous and Decentralized matrix completion %@Hyokun Yun, Hsiang-Fu Yu, Cho-Jui Hsieh, S V N Vishwanathan, Inderjit Dhillon %t2014 %cVLDB %f/VLDB/VLDB-2014-7674.pdf %*Repairing Vertex Labels under Neighborhood Constraints %@Shaoxu Song, Hong Cheng, Jeffrey Xu Yu, Lei Chen %t2014 %cVLDB %f/VLDB/VLDB-2014-7675.pdf %*Progressive Approach to Relational Entity Resolution %@Yasser Altowim, Dmitri V. Kalashnikov, Sharad Mehrotra %t2014 %cVLDB %f/VLDB/VLDB-2014-7676.pdf %*Concurrent Analytical Query Processing with GPUs %@Kaibo Wang, Kai Zhang, Yuan Yuan, Siyuan Ma, Rubao Lee, Xiaoning Ding, Xiaodong Zhang %t2014 %cVLDB %f/VLDB/VLDB-2014-7677.pdf %*Front Matter %@H. V. Jagadish %t2014 %cVLDB %f/VLDB/VLDB-2014-7678.pdf %*Computing Personalized PageRank Quickly by Exploiting Graph Structures %@Takanori Maehara, Takuya Akiba, Yoichi Iwata, Ken-ichi Kawarabayashi %t2014 %cVLDB %f/VLDB/VLDB-2014-7679.pdf %*Accordion: Elastic Scalability for Database Systems Supporting Distributed Transactions %@Marco Serafini, Essam Mansour, Ashraf Aboulnaga, Kenneth Salem, Taha Rafiq, Umar Farooq Minhas %t2014 %cVLDB %f/VLDB/VLDB-2014-7680.pdf %*An Experimental Comparison of Pregel-like Graph Processing Systems %@Minyang Han, Khuzaima Daudjee, Khaled Ammar, M. Tamer Özsu, Xingfang Wang, Tianqi Jin %t2014 %cVLDB %f/VLDB/VLDB-2014-7681.pdf %*ClusterJoin: A Similarity Joins Framework using Map-Reduce %@Akash Das Sarma, Yeye He, Surajit Chaudhuri %t2014 %cVLDB %f/VLDB/VLDB-2014-7682.pdf %*Crowdsourcing Algorithms for Entity Resolution %@Norases Vesdapunt, Kedar Bellare, Nilesh Dalvi %t2014 %cVLDB %f/VLDB/VLDB-2014-7683.pdf %*Distributed Graph Simulation: Impossibility and Possibility %@Wenfei Fan, Xin Wang, Yinghui Wu, Dong Deng %t2014 %cVLDB %f/VLDB/VLDB-2014-7684.pdf %*Code Generation for Efficient Query Processing in Managed Runtimes %@Fabian Nagel, Gavin Bierman, Stratis D. Viglas %t2014 %cVLDB %f/VLDB/VLDB-2014-7685.pdf %*Aggregate Estimation Over Dynamic Hidden Web Databases %@Weimo Liu, Saravanan Thirumuruganathan, Nan Zhang, Gautam Das %t2014 %cVLDB %f/VLDB/VLDB-2014-7686.pdf %*Adaptive Query Processing on RAW Data %@Manos Karpathiotakis, Miguel Branco, Ioannis Alagiannis, Anastasia Ailamaki %t2014 %cVLDB %f/VLDB/VLDB-2014-7687.pdf %*Storing and Querying Tree-Structured Records in Dremel %@Foto N. Afrati, Dan Delorey, Mosha Pasumansky, Jeffrey D. Ullman %t2014 %cVLDB %f/VLDB/VLDB-2014-7688.pdf %*Similarity Search for Scientific Workflows %@Johannes Starlinger, Bryan Brancotte, Sarah Cohen-Boulakia, Ulf Leser %t2014 %cVLDB %f/VLDB/VLDB-2014-7689.pdf %*Differentially Private Event Sequences over Infinite Streams %@Georgios Kellaris, Stavros Papadopoulos, Xiaokui Xiao, Dimitris Papadias %t2014 %cVLDB %f/VLDB/VLDB-2014-7690.pdf %*Matching Titles with Cross Title Web-Search Enrichment and Community Detection %@Nikhil Londhe, Vishrawas Gopalakrishnan, Aidong Zhang, Hung Q. Ngo, Rohini Srihari %t2014 %cVLDB %f/VLDB/VLDB-2014-7691.pdf %*On Concise Set of Relative Candidate Keys %@Shaoxu Song, Lei Chen, Hong Cheng %t2014 %cVLDB %f/VLDB/VLDB-2014-7692.pdf %*Reachability Querying: An Independent Permutation Labeling Approach %@Hao Wei, Jeffrey Xu Yu, Can Lu, Ruoming Jin %t2014 %cVLDB %f/VLDB/VLDB-2014-7693.pdf %*Hop Doubling Label Indexing for Point-to-Point Distance Querying on Scale-Free Networks %@Minhao Jiang, Ada Wai-Chee Fu, Raymond Chi-Wing Wong, Yanyan Xu %t2014 %cVLDB %f/VLDB/VLDB-2014-7694.pdf %*Semantic Culturomics (vision paper) %@Fabian M. Suchanek, Nicoleta Preda %t2014 %cVLDB %f/VLDB/VLDB-2014-7695.pdf %*Benchmarking Scalability and Elasticity of Distributed Database Systems %@Jörn Kuhlenkamp, Markus Klems, Oliver Röss %t2014 %cVLDB %f/VLDB/VLDB-2014-7696.pdf %*Bounded Conjunctive Queries %@Yang Cao, Wenfei Fan, Tianyu Wo, Wenyuan Yu %t2014 %cVLDB %f/VLDB/VLDB-2014-7697.pdf %*Optimizing Join Enumeration in Transformation-based Query Optimizers %@Anil Shanbhag, S. Sudarshan %t2014 %cVLDB %f/VLDB/VLDB-2014-7698.pdf %*A System for Management and Analysis of Preference Data %@Marie Jacob, Benny Kimelfeld, Julia Stoyanovich %t2014 %cVLDB %f/VLDB/VLDB-2014-7699.pdf %*Mesa: Geo-Replicated, Near Real-Time, Scalable Data Warehousing %@Ashish Gupta, Fan Yang, Jason Govig, Adam Kirsch, Kelvin Chan, Kevin Lai, Shuo Wu, Sandeep Govind Dhoot, Abhilash Rajesh Kumar, Ankur Agiwal, Sanjay Bhansali, Mingsheng Hong, Jamie Cameron, Masood Siddiqi, David Jones, Jeff Shute, Andrey Gubarev, Shivakumar Venkataraman, Divyakant Agrawal %t2014 %cVLDB %f/VLDB/VLDB-2014-7700.pdf %*An Effective Encoding Scheme for Spatial RDF Data %@John Liagouris, Nikos Mamoulis, Panagiotis Bouros, Manolis Terrovitis %t2014 %cVLDB %f/VLDB/VLDB-2014-7701.pdf %*DimmWitted: A Study of Main-Memory Statistical Analytics %@Ce Zhang, Christopher Re %t2014 %cVLDB %f/VLDB/VLDB-2014-7702.pdf %*SQL-on-Hadoop: Full Circle Back to Shared-Nothing Database Architectures %@Avrilia Floratou, Umar Farooq Minhas, Fatma Özcan %t2014 %cVLDB %f/VLDB/VLDB-2014-7703.pdf %*Optimal Security-Aware Query Processing %@Marco Guarnieri, David Basin %t2014 %cVLDB %f/VLDB/VLDB-2014-7704.pdf %*Front Matter %@H. V. Jagadish %t2014 %cVLDB %f/VLDB/VLDB-2014-7705.pdf %*MRTuner: A Toolkit to Enable Holistic Optimization for MapReduce Jobs %@Juwei Shi, Jia Zou, Jiaheng Lu, Zhao Cao, Shiqiang Li, and Chen Wang %t2014 %cVLDB %f/VLDB/VLDB-2014-7706.pdf %*Reducing Database Locking Contention Through Multi-version Concurrency %@Mohammad Sadoghi, Mustafa Canim, Bishwaranjan Bhattacharjee, Fabian Nagel, Kenneth A. Ross %t2014 %cVLDB %f/VLDB/VLDB-2014-7707.pdf %*Changing Engines in Midstream: A Java Stream Computational Model for Big Data Processing %@Xueyuan Su, Garret Swart, Brian Goetz, Brian Oliver, Paul Sandoz %t2014 %cVLDB %f/VLDB/VLDB-2014-7708.pdf %*Joins on Encoded and Partitioned Data %@Jae-Gil Lee, Gopi Attaluri, Ronald Barber, Naresh Chainani, Oliver Draese, Frederick Ho, Stratos Idreos, Min-Soo Kim, Sam Lightstone, Guy Lohman, Konstantinos Morfonios, Keshava Murthy, Ippokratis Pandis, Lin Qiao, Vijayshankar Raman, Vincent Kulandai Samy, Richard Sidle, Knut Stolz, Liping Zhang %t2014 %cVLDB %f/VLDB/VLDB-2014-7709.pdf %*TPC-DI: The First Industry Benchmark for Data Integration %@Meikel Poess, Tilmann Rabl, Brian Caufield %t2014 %cVLDB %f/VLDB/VLDB-2014-7710.pdf %*Real-Time Twitter Recommendation: Online Motif Detection in Large Dynamic Graphs %@Pankaj Gupta, Venu Satuluri, Ajeet Grewal, Siva Gurumurthy, Volodymyr Zhabiuk, Quannan Li, and Jimmy Lin %t2014 %cVLDB %f/VLDB/VLDB-2014-7711.pdf %*Interval Disaggregate: A New Operator for Business Planning %@Sang K. Cha, Kunsoo Park, Changbin Song, Kihong Kim, Cheol Ryu, Sunho Lee %t2014 %cVLDB %f/VLDB/VLDB-2014-7712.pdf %*Fuxi: a Fault-Tolerant Resource Management and Job Scheduling System at Internet Scale %@Zhuo Zhang, Chao Li, Yangyu Tao, Renyu Yangy, Hong Tang, Jie Xu %t2014 %cVLDB %f/VLDB/VLDB-2014-7713.pdf %*Large-Scale Graph Analytics in Aster 6: Bringing Context to Big Data Discovery %@David Simmen, Karl Schnaitter, Jeff Davis, Yingjie He, Sangeet Lohariwala, Ajay Mysore, Vinayak Shenoi, Mingfeng Tan, Yu Xiao %t2014 %cVLDB %f/VLDB/VLDB-2014-7714.pdf %*Fast Foreign-Key Detection in Microsoft SQL Server PowerPivot for Excel %@Zhimin Chen, Vivek Narasayya, Surajit Chaudhuri %t2014 %cVLDB %f/VLDB/VLDB-2014-7715.pdf %*Big Data Small Footprint: The Design of A Low-Power Classifier for Detecting Transportation Modes %@Meng-Chieh Yu, Tong Yu, Shao-Chen Wang, Chih-Jen Lin, Edward Y. Chang %t2014 %cVLDB %f/VLDB/VLDB-2014-7716.pdf %*Summingbird: A Framework for Integrating Batch and Online MapReduce Computations %@Oscar Boykin, Sam Ritchie, Ian O'Connell, Jimmy Lin %t2014 %cVLDB %f/VLDB/VLDB-2014-7717.pdf %*Of Snowstorms and Bushy Trees %@Rafi Ahmed, Rajkumar Sen, Meikel Poess, Sunil Chakkappen %t2014 %cVLDB %f/VLDB/VLDB-2014-7718.pdf %*Execution Primitives for Scalable Joins and Aggregations in Map Reduce %@Srinivas Vemuri, Maneesh Varshney, Krishna Puttaswamy, Rui Liu %t2014 %cVLDB %f/VLDB/VLDB-2014-7719.pdf %*CAP Limits in Telecom Subscriber Database Design %@Javier Arauz %t2014 %cVLDB %f/VLDB/VLDB-2014-7720.pdf %*Advanced Join Strategies for Large-Scale Distributed Computation %@Nicolas Bruno, YongChul Kwon, Ming-Chuan Wu %t2014 %cVLDB %f/VLDB/VLDB-2014-7721.pdf %*DGFIndex for Smart Grid: Enhancing Hive with a Cost-Effective Multidimensional Range Index %@Yue Liu, Songlin Hu, Tilmann Rabl, Wantao Liu, Hans-Arno Jacobsen, Kaifeng Wu, Jian Chen, Jintao Li %t2014 %cVLDB %f/VLDB/VLDB-2014-7722.pdf %*Error-bounded Sampling for Analytics on Big Sparse Data %@Ying Yan, Liang Jeff Chen, Zheng Zhang %t2014 %cVLDB %f/VLDB/VLDB-2014-7723.pdf %*Indexing HDFS Data in PDW: Splitting the data from the index %@Vinitha Reddy Gankidi, Nikhil Teletia, Jignesh M. Patel, Alan Halverson, David J. DeWitt %t2014 %cVLDB %f/VLDB/VLDB-2014-7724.pdf %*Chimera: Large-Scale Classification using Machine Learning, Rules, and Crowdsourcing %@Chong Sun, Narasimhan Rampalli, Frank Yang, AnHai Doan %t2014 %cVLDB %f/VLDB/VLDB-2014-7725.pdf %*Interactive Join Query Inference with JIM %@Angela Bonifati, Radu Ciucanu, Slawek Staworko %t2014 %cVLDB %f/VLDB/VLDB-2014-7726.pdf %*MESA: A Map Service to Support Fuzzy Type-ahead Search over Geo-Textual Data %@Yuxin Zheng, Zhifeng Bao, Lidan Shou, Anthony K. H. Tung %t2014 %cVLDB %f/VLDB/VLDB-2014-7727.pdf %*R3: A Real-Time Route Recommendation System %@Henan Wang, Guoliang Li, Huiqi Hu, Shuo Chen, Bingwen Shen, Hao Wu, Wen-Syan Li, Kian-Lee Tan %t2014 %cVLDB %f/VLDB/VLDB-2014-7728.pdf %*PDQ: Proof-driven Query Answering over Web-based Data %@Michael Benedikt, Julien Leblay, Efthymia Tsamoura %t2014 %cVLDB %f/VLDB/VLDB-2014-7729.pdf %*Data In, Fact Out: Automated Monitoring of Facts by FactWatcher %@Naeemul Hassan, Afroza Sultana, You Wu, Gensheng Zhang, Chengkai Li, Jun Yang, Cong Yu %t2014 %cVLDB %f/VLDB/VLDB-2014-7730.pdf %*OceanST: A Distributed Analytic System for Large-Scale Spatiotemporal Mobile Broadband Data %@Mingxuan Yuan, Ke Deng, Jia Zeng, Yanhua Li, Bing Ni, Xiuqiang He, Fei Wang, Wenyuan Dai, Qiang Yang %t2014 %cVLDB %f/VLDB/VLDB-2014-7731.pdf %*That's All Folks! LLUNATIC Goes Open Source %@Floris Geerts, Giansalvatore Mecca, Paolo Papotti, Donatello Santoro %t2014 %cVLDB %f/VLDB/VLDB-2014-7732.pdf %*HDBTracker: Monitoring the Aggregates On Dynamic Hidden Web Databases %@Weimo Liu, Saad Bin Suhaim, Saravanan Thirumuruganathan, Nan Zhang, Gautam Das, Ali Jaoua %t2014 %cVLDB %f/VLDB/VLDB-2014-7733.pdf %*BSMA: A Benchmark for Analytical Queries over Social Media Data %@Fan Xia, Ye Li, Chengcheng Yu, Haixin Ma, Weining Qian %t2014 %cVLDB %f/VLDB/VLDB-2014-7734.pdf %*Graph-based Data Integration and Business Intelligence with BIIIG %@Andre Petermann, Martin Junghanns, Robert Muller, Erhard Rahm %t2014 %cVLDB %f/VLDB/VLDB-2014-7735.pdf %*SEEDB: Automatically Generating Query Visualizations %@Manasi Vartak, Samuel Madden, Aditya Parameswaran, Neoklis Polyzotis %t2014 %cVLDB %f/VLDB/VLDB-2014-7736.pdf %*QUEST: An Exploratory Approach to Robust Query Processing %@Anshuman Dutt, Sumit Neelam, Jayant R. Haritsa %t2014 %cVLDB %f/VLDB/VLDB-2014-7737.pdf %*Redoop Infrastructure for Recurring Big Data Queries %@Chuan Lei, Zhongfang Zhuang, Elke A. Rundensteiner, Mohamed Y. Eltabakh %t2014 %cVLDB %f/VLDB/VLDB-2014-7738.pdf %*PackageBuilder: From Tuples to Packages %@Matteo Brucato, Rahul Ramakrishna, Azza Abouzied, Alexandra Meliou %t2014 %cVLDB %f/VLDB/VLDB-2014-7739.pdf %*Ontology Assisted Crowd Mining %@Yael Amsterdamer, Susan B. Davidson, Tova Milo, Slava Novgorodov, Amit Somech %t2014 %cVLDB %f/VLDB/VLDB-2014-7740.pdf %*SOPS: A System for Efficient Processing of Spatial-Keyword Publish/Subscribe %@Lisi Chen, Yan Cui, Gao Cong, Xin Cao %t2014 %cVLDB %f/VLDB/VLDB-2014-7741.pdf %*MLJ: Language-Independent Real-Time Search of Tweets Reported by Media Outlets and Journalists %@Masumi Shirakawa, Takahiro Hara, Shojiro Nishio %t2014 %cVLDB %f/VLDB/VLDB-2014-7742.pdf %*Ocelot/HyPE: Optimized Data Processing on Heterogeneous Hardware %@Sebastian Bress, Max Heimel, Michael Saecker, Bastian Kocher, Volker Markl, Gunter Saake %t2014 %cVLDB %f/VLDB/VLDB-2014-7743.pdf %*MoveMine 2.0: Mining Object Relationships from Movement Data %@Fei Wu, Tobias Kin Hou Lei, Zhenhui Li, Jiawei Han %t2014 %cVLDB %f/VLDB/VLDB-2014-7744.pdf %*A Partitioning Framework for Aggressive Data Skipping %@Liwen Sun, Sanjay Krishnan, Reynold S. Xin, Michael J. Franklin %t2014 %cVLDB %f/VLDB/VLDB-2014-7745.pdf %*Interactive Outlier Exploration in Big Data Streams %@Lei Cao, Qingyang Wang, Elke A. Rundensteiner %t2014 %cVLDB %f/VLDB/VLDB-2014-7746.pdf %*SQL/AA: Executing SQL on an Asymmetric Architecture %@Quoc-Cuong To, Benjamin Nguyen, Philippe Pucheral %t2014 %cVLDB %f/VLDB/VLDB-2014-7747.pdf %*gMission: A General Spatial Crowdsourcing Platform %@Zhao Chen, Rui Fu, Ziyuan Zhao, Zheng Liu, Leihao Xia, Lei Chen, Peng Cheng, Caleb Chen Cao, Yongxin Tong, Chen Jason Zhang %t2014 %cVLDB %f/VLDB/VLDB-2014-7748.pdf %*S-Store: A Streaming NewSQL System for Big Velocity Applications %@Ugur Cetintemel, Jiang Du, Tim Kraska, Samuel Madden, David Maier, John Meehan, Andrew Pavlo, Michael Stonebraker, Erik Sutherland, Nesime Tatbul, Kristin Tufte, Hao Wang, Stanley Zdonik %t2014 %cVLDB %f/VLDB/VLDB-2014-7749.pdf %*CLEar: A Real-time Online Observatory for Bursty and Viral Events %@Runquan Xie, Feida Zhu, Hui Ma, Wei Xie, Chen Lin %t2014 %cVLDB %f/VLDB/VLDB-2014-7750.pdf %*AZDBLab: A Laboratory Information System for Large-Scale Empirical DBMS Studies %@Young-Kyoon Suh, Richard T. Snodgrass, Rui Zhang %t2014 %cVLDB %f/VLDB/VLDB-2014-7751.pdf %*Terrain-Toolkit: A Multi-Functional Tool for Terrain Data %@Qi Wang, Manohar Kaul, Cheng Long, Raymond Chi-Wing Wong %t2014 %cVLDB %f/VLDB/VLDB-2014-7752.pdf %*FORWARD: Data-Centric UIs using Declarative Templates that Efficiently Wrap Third-Party JavaScript Components %@Yupeng Fu, Kian Win Ong, Yannis Papakonstantinou, Erick Zamora %t2014 %cVLDB %f/VLDB/VLDB-2014-7753.pdf %*SPIRE: Supporting Parameter-Driven Interactive Rule Mining and Exploration %@Xika Lin, Abhishek Mukherji, Elke A. Rundensteiner, Matthew O. Ward %t2014 %cVLDB %f/VLDB/VLDB-2014-7754.pdf %*An Integrated Development Environment for Faster Feature Engineering %@Michael R. Anderson, Michael Cafarella, Yixing Jiang, Guan Wang, Bochun Zhang %t2014 %cVLDB %f/VLDB/VLDB-2014-7755.pdf %*Pronto: A Software-Defined Networking based System for Performance Management of Analytical Queries on Distributed Data Stores %@Pengcheng Xiong, Hakan Hacigumus %t2014 %cVLDB %f/VLDB/VLDB-2014-7756.pdf %*Getting Your Big Data Priorities Straight: A Demonstration of Priority-based QoS using Social-network-driven Stock Recommendation %@Rui Zhang, Reshu Jain, Prasenjit Sarkar, Lukas Rupprecht %t2014 %cVLDB %f/VLDB/VLDB-2014-7757.pdf %*VERTEXICA: Your Relational Friend for Graph Analytics! %@Alekh Jindal, Praynaa Rawlani, Eugene Wu, Samuel Madden, Amol Deshpande, Mike Stonebraker %t2014 %cVLDB %f/VLDB/VLDB-2014-7758.pdf %*NScale: Neighborhood-centric Analytics on Large Graphs %@Abdul Quamar, Amol Deshpande, Jimmy Lin %t2014 %cVLDB %f/VLDB/VLDB-2014-7759.pdf %*DPSynthesizer: Differentially Private Data Synthesizer for Privacy Preserving Data Sharing %@Haoran Li, Li Xiong, Lifan Zhang, Xiaoqian Jiang %t2014 %cVLDB %f/VLDB/VLDB-2014-7760.pdf %*SPOT: Locating Social Media Users Based on Social Network Context %@Longbo Kong, Zhi Liu, Yan Huang %t2014 %cVLDB %f/VLDB/VLDB-2014-7761.pdf %*RASP-QS: Efficient and Confidential Query Services in the Cloud %@Zohreh Alavi, Lu Zhou, James Powers, Keke Chen %t2014 %cVLDB %f/VLDB/VLDB-2014-7762.pdf %*Thoth: Towards Managing a Multi-System Cluster %@Mayuresh Kunjir, Prajakta Kalmegh, Shivnath Babu %t2014 %cVLDB %f/VLDB/VLDB-2014-7763.pdf %*X-LiSA: Cross-lingual Semantic Annotation %@Lei Zhang, Achim Rettinger %t2014 %cVLDB %f/VLDB/VLDB-2014-7764.pdf %*Combining User Interaction, Speculative Query Execution and Sampling in the DICE System %@Prasanth Jayachandran, Karthik Tunga, Niranjan Kamat, Arnab Nandi %t2014 %cVLDB %f/VLDB/VLDB-2014-7765.pdf %*STMaker - A System to Make Sense of Trajectory Data %@Han Su, Kai Zheng, Kai Zeng, Jiamin Huang, Xiaofang Zhou %t2014 %cVLDB %f/VLDB/VLDB-2014-7766.pdf %*Faster Visual Analytics through Pixel-Perfect Aggregation %@Uwe Jugel, Zbigniew Jerzak, Gregor Hackenbroich, Volker Markl %t2014 %cVLDB %f/VLDB/VLDB-2014-7767.pdf %*Systems for Big-Graphs %@Arijit Khan, Sameh Elnikety %t2014 %cVLDB %f/VLDB/VLDB-2014-7768.pdf %*Tutorial: Uncertain Entity Resolution %@Avigdor Gal %t2014 %cVLDB %f/VLDB/VLDB-2014-7769.pdf %*Knowledge Bases in the Age of Big Data Analytics %@Fabian M. Suchanek, Gerhard Weikum %t2014 %cVLDB %f/VLDB/VLDB-2014-7770.pdf %*Causality and Explanations in Databases %@Alexandra Meliou, Sudeepa Roy, Dan Suciu %t2014 %cVLDB %f/VLDB/VLDB-2014-7771.pdf %*Enterprise Search in the Big Data Era: Recent Developments and Open Challenges %@Yunyao Li, Ziyang Liu, Huaiyu Zhu %t2014 %cVLDB %f/VLDB/VLDB-2014-7772.pdf %*VLDB 2014 Ph.D. Workshop - An Overview %@Yunyao Li, Erich Neuhold %t2014 %cVLDB %f/VLDB/VLDB-2014-7773.pdf %*Datacenters as Computers: Google Engineering & Database Research Perspectives %@Shivakumar Venkataraman, Divyakant Agrawal %t2014 %cVLDB %f/VLDB/VLDB-2014-7774.pdf %*The Impact of Columnar In-Memory Databases on Enterprise Systems %@Hasso Plattner %t2014 %cVLDB %f/VLDB/VLDB-2014-7775.pdf %*Breaking the Chains: On Declarative Data Analysis and Data Independence in the Big Data Era %@Volker Markl %t2014 %cVLDB %f/VLDB/VLDB-2014-7776.pdf %*Engineering High-Performance Database Engines %@Thomas Neumann %t2014 %cVLDB %f/VLDB/VLDB-2014-7777.pdf %*Realization of the Low Cost and High Performance MySQL Cloud Database %@Wei Cao, Feng Yu, Jiasen Xie %t2014 %cVLDB %f/VLDB/VLDB-2014-7778.pdf %*Fatman: Cost-saving and reliable archival storage based on volunteer resources %@An Qin, Dianming Hu, Jun Liu, Wenjun Yang, Dai Tan %t2014 %cVLDB %f/VLDB/VLDB-2014-7779.pdf %*Design and Implementation of a Real-Time Interactive Analytics System for Large Spatio-Temporal Data %@Shiming Zhang, Yin Yang, Wei Fan, Marianne Winslet %t2014 %cVLDB %f/VLDB/VLDB-2014-7780.pdf %*A Personalized Recommendation System for NetEase Dating Site %@Chaoyue Dai, Feng Qian, Wei Jiang, Zhoutian Wang, Zenghong Wu %t2014 %cVLDB %f/VLDB/VLDB-2014-7781.pdf %*GEMINI: An Integrative Healthcare Analytics System %@Zheng Jye Ling, Quoc Trung Tran, Ju Fan, Gerald C.H. Koh, Thi Nguyen, Chuen Seng Tan, James W. L. Yip, Meihui Zhang %t2014 %cVLDB %f/VLDB/VLDB-2014-7782.pdf %*Mariana: Tencent Deep Learning Platform and its Applications %@Yongqiang Zou, Xing Jin, Yi Li, Zhimao Guo, Eryu Wang, Bin Xiao %t2014 %cVLDB %f/VLDB/VLDB-2014-7783.pdf %*yzStack: Provisioning Customizable Solution for Big Data %@Sai Wu, Chun Chen, Gang Chen, Ke Chen, Lidan Shou, Hui Cao, He Bai %t2014 %cVLDB %f/VLDB/VLDB-2014-7784.pdf %*Errata for "Building Efficient Query Engines in a High-Level Language" (PVLDB 7(10): 853-864) %@Yannis Klonatos, Christoph Koch, Tiark Rompf, Hassan Chafi %t2014 %cVLDB %f/VLDB/VLDB-2014-7785.pdf %*Front Matter %@Peer Kröger and Stratis D. Viglas %t2014 %cVLDB %f/VLDB/VLDB-2014-7799.pdf %*When Speed Has a Price: Fast Information Extraction Using Approximate Algorithms. %@Goncalo Simoes, Helena Galhardas, Luis Gravano %t2014 %cVLDB %f/VLDB/VLDB-2014-7800.pdf %*Design and Evaluation of Storage Organizations for Read-Optimized Main Memory Databases. %@Craig Chasseur, Jignesh M. Patel %t2014 %cVLDB %f/VLDB/VLDB-2014-7801.pdf %*Aggregating Semantic Annotators. %@Luying Chen, Stefano Ortona, Giorgio Orsi, Michael Benedikt %t2014 %cVLDB %f/VLDB/VLDB-2014-7802.pdf %*Discovering Denial Constraints. %@Xu Chu, Ihab F. Ilyas, Paolo Papotti %t2014 %cVLDB %f/VLDB/VLDB-2014-7803.pdf %*Diversified Top-k Graph Pattern Matching. %@Wenfei Fan, Xin Wang, Yinghui Wu %t2014 %cVLDB %f/VLDB/VLDB-2014-7804.pdf %*Bitlist: New Full-text Index for Low Space Cost and Efficient Keyword Search. %@Weixiong Rao, Lei Chen, Pan Hui, Sasu Tarkoma %t2014 %cVLDB %f/VLDB/VLDB-2014-7805.pdf %*RCSI: Scalable similarity search in thousand(s) of genomes. %@Sebastian Wandelt, Johannes Starlinger, Marc Bux, Ulf Leser %t2014 %cVLDB %f/VLDB/VLDB-2014-7806.pdf %*Approximate MaxRS in Spatial Databases. %@Yufei Tao, Xiaocheng Hu, Dong-Wan Choi, Chin-Wan Chung %t2014 %cVLDB %f/VLDB/VLDB-2014-7807.pdf %*Multi-Tuple Deletion Propagation: Approximations and Complexity. %@Benny Kimelfeld, Jan Vondrak, David P. Woodruff %t2014 %cVLDB %f/VLDB/VLDB-2014-7808.pdf %*Supporting Distributed Feed-Following Apps over Edge Devices. %@Badrish Chandramouli, Suman Nath, Wenchao Zhou %t2014 %cVLDB %f/VLDB/VLDB-2014-7809.pdf %*Rank Discovery From Web Databases. %@Saravanan Thirumuruganathan, Nan Zhang, Gautam Das %t2014 %cVLDB %f/VLDB/VLDB-2014-7810.pdf %*SPARSI: Partitioning Sensitive Data amongst Multiple Adversaries. %@Theodoros Rekatsinas, Amol Deshpande, Ashwin Machanavajjhala %t2014 %cVLDB %f/VLDB/VLDB-2014-7811.pdf %*Scalable Column Concept Determination for Web Tables Using Large Knowledge Bases. %@Dong Deng, Yu Jiang, Guoliang Li, Jian Li, Cong Yu %t2014 %cVLDB %f/VLDB/VLDB-2014-7812.pdf %*Top-K Structural Diversity Search in Large Networks. %@Xin Huang, Hong Cheng, Rong-Hua Li, Lu Qin, Jeffrey Xu Yu %t2014 %cVLDB %f/VLDB/VLDB-2014-7813.pdf %*Synthetising Changes in XML Documents as PULs. %@Federico Cavalieri, Alessandro Solimando, Giovanna Guerrini %t2014 %cVLDB %f/VLDB/VLDB-2014-7814.pdf %*Front Matter. %@null %t2014 %cVLDB %f/VLDB/VLDB-2014-7815.pdf %*Probabilistic Query Rewriting for Efficient and Effective Keyword Search on Graph Data. %@Lei Zhang, Thanh Tran, Achim Rettinger %t2014 %cVLDB %f/VLDB/VLDB-2014-7816.pdf %*QuEval: Beyond high-dimensional indexing a la carte. %@Martin Schäler, Alexander Grebhahn, Reimar Schröter, Sandro Schulze, Veit Köppen, Gunter Saake %t2014 %cVLDB %f/VLDB/VLDB-2014-7817.pdf %*Discovering Longest-lasting Correlation in Sequence Databases. %@Yuhong Li, Leong Hou U, Man Lung Yiu, Zhiguo Gong %t2014 %cVLDB %f/VLDB/VLDB-2014-7818.pdf %*PREDIcT: Towards Predicting the Runtime of Large Scale Iterative Analytics. %@Adrian Daniel Popescu, Andrey Balmin, Vuk Ercegovac, Anastasia Ailamaki %t2014 %cVLDB %f/VLDB/VLDB-2014-7819.pdf %*On the Embeddability of Random Walk Distances. %@Xiaohan Zhao, Adelbert Chang, Atish Das Sarma, Haitao Zheng, Ben Y. Zhao %t2014 %cVLDB %f/VLDB/VLDB-2014-7820.pdf %*Instant Loading for Main Memory Databases. %@Tobias Mühlbauer, Wolf Rödiger, Robert Seilbeck, Angelika Reiser, Alfons Kemper, Thomas Neumann %t2014 %cVLDB %f/VLDB/VLDB-2014-7821.pdf %*Adaptive Range Filters for Cold Data: Avoiding Trips to Siberia. %@Karolina Alexiou, Donald Kossmann, Per-Ake Larson %t2014 %cVLDB %f/VLDB/VLDB-2014-7822.pdf %*Scalable Progressive Analytics on Big Data in the Cloud. %@Badrish Chandramouli, Jonathan Goldstein, Abdul Quamar %t2014 %cVLDB %f/VLDB/VLDB-2014-7823.pdf %*Scalable XML Query Processing using Parallel Pushdown Transducers. %@Peter Ogden, David Thomas, Peter Pietzuch %t2014 %cVLDB %f/VLDB/VLDB-2014-7824.pdf %*Understanding Insights into the Basic Structure and Essential Issues of Table Placement Methods in Clusters. %@Yin Huai, Siyuan Ma, Rubao Lee, Owen O’Malley, Xiaodong Zhang %t2014 %cVLDB %f/VLDB/VLDB-2014-7825.pdf %*A Probabilistic Optimization Framework for the Empty-Answer Problem. %@Davide Mottin, Alice Marascu, Senjuti Basu Roy, Gautam Das, Themis Palpanas, Yannis Velegrakis %t2014 %cVLDB %f/VLDB/VLDB-2014-7826.pdf %*Summarizing Answer Graphs Induced by Keyword Queries. %@Yinghui Wu, Shengqi Yang, Mudhakar Srivatsa, Arun Iyengar, Xifeng Yan %t2014 %cVLDB %f/VLDB/VLDB-2014-7827.pdf %*Supporting Keyword Search in Product Database: A Probabilistic Approach. %@Huizhong Duan, ChengXiang Zhai, Jinxing Cheng, Abhishek Gattani %t2014 %cVLDB %f/VLDB/VLDB-2014-7828.pdf %*A Sampling Algebra for Aggregate Estimation. %@Supriya Nirkhiwale, Alin Dobra, Christopher Jermaine %t2014 %cVLDB %f/VLDB/VLDB-2014-7829.pdf %*A Temporal-Probabilistic Database Model for Information Extraction. %@Maximilian Dylla, Iris Miliaraki, Martin Theobald %t2014 %cVLDB %f/VLDB/VLDB-2014-7830.pdf %*Counter Strike: Generic Top-Down Join Enumeration for Hypergraphs. %@Pit Fender, Guido Moerkotte %t2014 %cVLDB %f/VLDB/VLDB-2014-7831.pdf %*Efficient Bulk Updates on Multiversion B-trees. %@Daniar Achakeev, Bernhard Seeger %t2014 %cVLDB %f/VLDB/VLDB-2014-7832.pdf %*Query-Driven Approach to Entity Resolution. %@Hotham Altwaijry, Dmitri V. Kalashnikov, Sharad Mehrotra %t2014 %cVLDB %f/VLDB/VLDB-2014-7833.pdf %*Expressiveness and Complexity of Order Dependencies. %@Jaroslaw Szlichta, Parke Godfrey, Jarek Gryz, Calisto Zuzarte %t2014 %cVLDB %f/VLDB/VLDB-2014-7834.pdf %*Counting and Sampling Triangles from a Graph Stream. %@A. Pavan, Kanat Tangwongsan, Srikanta Tirthapura, Kun-Lung Wu %t2014 %cVLDB %f/VLDB/VLDB-2014-7835.pdf %*An Experimental Analysis of Iterated Spatial Joins in Main Memory. %@Benjamin Sowell, Marcos Vaz Salles, Tuan Cao, Alan Demers, Johannes Gehrke %t2014 %cVLDB %f/VLDB/VLDB-2014-7836.pdf %*Scaling Queries over Big RDF Graphs with Semantic Hash Partitioning. %@Kisung Lee, Ling Liu %t2014 %cVLDB %f/VLDB/VLDB-2014-7837.pdf %*Distributed SociaLite: A Datalog-Based Language for Large-Scale Graph Analysis. %@Jiwon Seo, Jongsoo Park, Jaeho Shin, Monica S. Lam %t2014 %cVLDB %f/VLDB/VLDB-2014-7838.pdf %*Horton+: A Distributed System for Processing Declarative Reachability Queries over Partitioned Graphs. %@Mohamed Sarwat, Sameh Elnikety, Yuxiong He, Mohamed F. Mokbel %t2014 %cVLDB %f/VLDB/VLDB-2014-7839.pdf %*Streaming Similarity Search over one Billion Tweets using Parallel Locality-Sensitive Hashing. %@Narayanan Sundaram, Aizana Turmukhametova, Nadathur Satish, Todd Mostak, Piotr Indyk, Samuel Madden, Pradeep Dubey %t2014 %cVLDB %f/VLDB/VLDB-2014-7840.pdf %*Anti-Caching: A New Approach to Database Management System Architecture. %@Justin DeBrabant, Andrew Pavlo, Stephen Tu, Michael Stonebraker, Stan Zdonik %t2014 %cVLDB %f/VLDB/VLDB-2014-7841.pdf %*Understanding Hierarchical Methods for Differentially Private Histograms. %@Wahbeh Qardaji, Weining Yang, Ninghui Li %t2014 %cVLDB %f/VLDB/VLDB-2014-7842.pdf %*Towards Social Data Platform: Automatic Topic-focused Monitor for Twitter Stream. %@Rui Li, Shengjie Wang, Kevin Chen-Chuan Chang %t2014 %cVLDB %f/VLDB/VLDB-2014-7843.pdf %*Simple, Fast, and Scalable Reachability Oracle. %@Ruoming Jin, Guan Wang %t2014 %cVLDB %f/VLDB/VLDB-2014-7844.pdf %*Aggregation and Ordering in Factorised Databases. %@Nurzhan Bakibayev, Tomas Kocisky, Dan Olteanu, Jakub Zavodny %t2014 %cVLDB %f/VLDB/VLDB-2014-7845.pdf %*Parallel Computation of Skyline and Reverse Skyline Queries Using MapReduce. %@Yoonjae Park, Jun-Ki Min, Kyuseok Shim %t2014 %cVLDB %f/VLDB/VLDB-2014-7846.pdf %*Fast Iterative Graph Computation with Block Updates. %@Wenlei Xie, Guozhang Wang, David Bindel, Alan Demers, Johannes Gehrke %t2014 %cVLDB %f/VLDB/VLDB-2014-7847.pdf %*Inferring Continuous Dynamic Social Influence and Personal Preference for Temporal Behavior Prediction %@Jun Zhang, Chaokun Wang, Jianmin Wang, Jeffrey Xu Yu %t2015 %cVLDB %f/VLDB/VLDB-2015-7848.pdf %*Large-Scale Distributed Graph Computing Systems: An Experimental Evaluation %@Yi Lu, James Cheng, Da Yan, Huanhuan Wu %t2015 %cVLDB %f/VLDB/VLDB-2015-7849.pdf %*Faster Set Intersection with SIMD instructions by Reducing Branch Mispredictions %@Hiroshi Inoue, Moriyoshi Ohara, Kenjiro Taura %t2015 %cVLDB %f/VLDB/VLDB-2015-7850.pdf %*Scalable Topical Phrase Mining from Text Corpora %@Ahmed El-Kishky, Yanglei Song, Chi Wang, Clare R. Voss, Jiawei Han %t2015 %cVLDB %f/VLDB/VLDB-2015-7851.pdf %*Efficient Top-K SimRank-based Similarity Join %@Wenbo Tao, Minghe Yu, Guoliang Li %t2015 %cVLDB %f/VLDB/VLDB-2015-7852.pdf %*Front Matter %@Shivnath Babu %t2015 %cVLDB %f/VLDB/VLDB-2015-7853.pdf %*In-Cache Query Co-Processing on Coupled CPU-GPU Architectures %@Jiong He, Shuhao Zhang, Bingsheng He %t2015 %cVLDB %f/VLDB/VLDB-2015-7854.pdf %*Scaling Manifold Ranking Based Image Retrieval %@Yasuhiro Fujiwara, Go Irie, Shari Kuroyama, Makoto Onizuka %t2015 %cVLDB %f/VLDB/VLDB-2015-7855.pdf %*Memory-Efficient Hash Joins %@R. Barber, G. Lohman, I. Pandis, V. Raman, R. Sidle, G. Attaluri, N. Chainani, S. Lightstone, D. Sharpe %t2015 %cVLDB %f/VLDB/VLDB-2015-7856.pdf %*Preference-aware Integration of Temporal Dat %@Bogdan Alexe, Mary Roth, Wang-Chiew Tan %t2015 %cVLDB %f/VLDB/VLDB-2015-7857.pdf %*MOCgraph: Scalable Distributed Graph Processing Using Message Online Computing %@Chang Zhou, Jun Gao, Binbin Sun, Jeffrey Xu Yu %t2015 %cVLDB %f/VLDB/VLDB-2015-7858.pdf %*NVRAM-aware Logging in Transaction Systems %@Jian Huang, Karsten Schwan, Moinuddin K. Qureshi %t2015 %cVLDB %f/VLDB/VLDB-2015-7859.pdf %*Trill: A High-Performance Incremental Query Processor for Diverse Analytics %@Badrish Chandramouli, Jonathan Goldstein, Mike Barnett, Robert DeLine, John C. Platt, James F. Terwilliger, John Wernsing %t2015 %cVLDB %f/VLDB/VLDB-2015-7860.pdf %*Event Pattern Matching over Graph Streams %@Chunyao Song, Tingjian Ge, Cindy Chen, Jie Wang %t2015 %cVLDB %f/VLDB/VLDB-2015-7861.pdf %*A Confidence-Aware Approach for Truth Discovery on Long-Tail Data %@Qi Li, Yaliang Li, Jing Gao, Lu Su, Bo Zhao, Murat Demirbas, Wei Fan, Jiawei Han %t2015 %cVLDB %f/VLDB/VLDB-2015-7862.pdf %*Fast Failure Recovery in Distributed Graph Processing Systems %@Yanyan Shen, Gang Chen, H. V. Jagadish, Wei Lu, Beng Chin Ooi, Bogdan Marius Tudor %t2015 %cVLDB %f/VLDB/VLDB-2015-7863.pdf %*The More the Merrier: Efficient Multi-Source Graph Traversal %@Manuel Then, Moritz Kaufmann, Fernando Chirigati, Tuan-Anh Hoang-Vu, Kien Pham, Alfons Kemper, Thomas Neumann, Huy T. Vo %t2015 %cVLDB %f/VLDB/VLDB-2015-7864.pdf %*Front Matter %@Magdalena Balazinska %t2015 %cVLDB %f/VLDB/VLDB-2015-7865.pdf %*MRCSI: Compressing and Searching String Collections with Multiple References %@Sebastian Wandelt, Ulf Leser %t2015 %cVLDB %f/VLDB/VLDB-2015-7866.pdf %*YADING: Fast Clustering of Large-Scale Time Series Data %@Rui Ding, Qiang Wang, Yingnong Dang, Qiang Fu, Haidong Zhang, Dongmei Zhang %t2015 %cVLDB %f/VLDB/VLDB-2015-7867.pdf %*Hear the Whole Story: Towards the Diversity of Opinion in Crowdsourcing Markets %@Ting Wu, Lei Chen, Pan Hui, Chen Jason Zhang, Weikai Li %t2015 %cVLDB %f/VLDB/VLDB-2015-7868.pdf %*REWIND: Recovery Write-Ahead System for In-Memory Non-Volatile Data-Structures %@Andreas Chatzistergiou, Marcelo Cintra, Stratis D. Viglas %t2015 %cVLDB %f/VLDB/VLDB-2015-7869.pdf %*Influential Community Search in Large Networks %@Rong-Hua Li, Lu Qin, Jeffrey Xu Yu, Rui Mao %t2015 %cVLDB %f/VLDB/VLDB-2015-7870.pdf %*Rapid Sampling for Visualizations with Ordering Guarantees %@Albert Kim, Eric Blais, Aditya Parameswaran, Piotr Indyk, Sam Madden, Ronitt Rubinfeld %t2015 %cVLDB %f/VLDB/VLDB-2015-7871.pdf %*Optimal Enumeration: Efficient Top-k Tree Matching %@Lijun Chang, Xuemin Lin, Wenjie Zhang, Jeffrey Xu Yu, Ying Zhang, Lu Qin %t2015 %cVLDB %f/VLDB/VLDB-2015-7872.pdf %*Monitoring Distributed Streams using Convex Decomposition %@Arnon Lazerson, Izchak Sharfman, Daniel Keren, Assaf Schuster, Minos Garofalakis, Vasilis Samoladas %t2015 %cVLDB %f/VLDB/VLDB-2015-7873.pdf %*UDA-GIST: An In-database Framework to Unify Data-Parallel and State-Parallel Analytics %@Kun Li, Daisy Zhe Wang, Alin Dobra, Christopher Dudley %t2015 %cVLDB %f/VLDB/VLDB-2015-7874.pdf %*Efficient Partial-Pairs SimRank Search for Large Networks %@Weiren Yu, Julie A. McCann %t2015 %cVLDB %f/VLDB/VLDB-2015-7875.pdf %*Linearized and Single-Pass Belief Propagation %@Wolfgang Gatterbauer, Stephan Günnemann, Danai Koutra, Christos Faloutsos %t2015 %cVLDB %f/VLDB/VLDB-2015-7876.pdf %*Mining Revenue-Maximizing Bundling Configuration %@Loc Do, Hady W. Lauw, Ke Wang %t2015 %cVLDB %f/VLDB/VLDB-2015-7877.pdf %*Reverse k Nearest Neighbors Query Processing: Experiments and Analysis %@Shiyu Yang, Muhammad Aamir Cheema, Xuemin Lin, Wei Wang %t2015 %cVLDB %f/VLDB/VLDB-2015-7878.pdf %*Exploiting Vertex Relationships in Speeding up Subgraph Isomorphism over Large Graphs %@Xuguang Ren, Junhu Wang %t2015 %cVLDB %f/VLDB/VLDB-2015-7879.pdf %*Approximate Lifted Inference with Probabilistic Databases %@Wolfgang Gatterbauer, Dan Suciu %t2015 %cVLDB %f/VLDB/VLDB-2015-7880.pdf %*Errata for “Crowdsourcing Algorithms for Entity Resolution” (PVLDB 7(12):1071-1082) %@Norases Vesdapunt, Kedar Bellare, Nilesh Dalvi %t2015 %cVLDB %f/VLDB/VLDB-2015-7881.pdf %*Front Matter %@Felix Naumann %t2015 %cVLDB %f/VLDB/VLDB-2015-7882.pdf %*Improving Main Memory Hash Joins on Intel Xeon Phi Processors: An Experimental Approach %@Saurabh Jha, Bingsheng He, Mian Lu, Xuntao Cheng, Huynh Phung Huynh %t2015 %cVLDB %f/VLDB/VLDB-2015-7883.pdf %*DREAM: Distributed RDF Engine with Adaptive Query Planner and Minimal Communication %@Mohammad Hammoud, Dania Abed Rabbou, Reza Nouri, Seyed-Mehdi-Reza Beheshti, Sherif Sakr %t2015 %cVLDB %f/VLDB/VLDB-2015-7884.pdf %*Online Topic-Aware Influence Maximization %@Shuo Chen, Ju Fan, Guoliang Li, Jianhua Feng, Kian-Iee Tan, Jinhui Tang %t2015 %cVLDB %f/VLDB/VLDB-2015-7885.pdf %*Walk, Not Wait: Faster Sampling Over Online Social Networks %@Azade Nazi, Zhuojie Zhou, Saravanan Thirumuruganathan, Nan Zhang, Gautam Das %t2015 %cVLDB %f/VLDB/VLDB-2015-7886.pdf %*Querying with Access Patterns and Integrity Constraints %@Michael Benedikt, Julien Leblay, Efthymia Tsamoura %t2015 %cVLDB %f/VLDB/VLDB-2015-7887.pdf %*Front Matter %@Stefan Manegold %t2015 %cVLDB %f/VLDB/VLDB-2015-7888.pdf %*General Incremental Sliding-Window Aggregation %@Kanat Tangwongsan, Martin Hirzel, Scott Schneider, Kun-Lung Wu %t2015 %cVLDB %f/VLDB/VLDB-2015-7889.pdf %*Shared Execution of Recurring Workloads in MapReduce %@Chuan Lei, Zhongfang Zhuang, Elke A. Rundensteiner, Mohamed Eltabakh %t2015 %cVLDB %f/VLDB/VLDB-2015-7890.pdf %*Sharing Buffer Pool Memory in Multi-Tenant Relational Database-as-a-Service %@Vivek Narasayya, Ishai Menache, Mohit Singh, Feng Li, Manoj Syamala, Surajit Chaudhuri %t2015 %cVLDB %f/VLDB/VLDB-2015-7891.pdf %*Answering Why-not Questions on Reverse Top-k Queries %@Yunjun Gao, Qing Liu, Gang Chen, Baihua Zheng, Linlin Zhou %t2015 %cVLDB %f/VLDB/VLDB-2015-7892.pdf %*Practical Authenticated Pattern Matching with Optimal Proof Size %@Dimitrios Papadopoulos, Charalampos Papamanthou, Roberto Tamassia, Nikos Triandopoulos %t2015 %cVLDB %f/VLDB/VLDB-2015-7893.pdf %*A Performance Study of Big Data on Small Nodes %@Dumitrel Loghin, Bogdan Marius Tudor, Hao Zhang, Beng Chin Ooi, Yong Meng Teo %t2015 %cVLDB %f/VLDB/VLDB-2015-7894.pdf %*Divide & Conquer-based Inclusion Dependency Discovery %@Thorsten Papenbrock, Sebastian Kruse, Jorge-Arnulfo Quiané-Ruiz, Felix Naumann %t2015 %cVLDB %f/VLDB/VLDB-2015-7895.pdf %*Persistent B+-Trees in Non-Volatile Main Memory %@Shimin Chen, Qin Jin %t2015 %cVLDB %f/VLDB/VLDB-2015-7896.pdf %*Robust Local Community Detection: On Free Rider Effect and Its Elimination %@Yubao Wu, Ruoming Jin, Jing Li, Xiang Zhang %t2015 %cVLDB %f/VLDB/VLDB-2015-7897.pdf %*Understanding the Causes of Consistency Anomalies in Apache Cassandra %@Hua Fan, Aditya Ramaraju, Marlon McKenzie, Wojciech Golab, Bernard Wong %t2015 %cVLDB %f/VLDB/VLDB-2015-7898.pdf %*Viral Marketing Meets Social Advertising: Ad Allocation with Minimum Regret %@Cigdem Aslay, Wei Lu, Francesco Bonchi, Amit Goyal, Laks V.S. Lakshmanan %t2015 %cVLDB %f/VLDB/VLDB-2015-7899.pdf %*Front Matter. i – ix %@Yi Chen %t2015 %cVLDB %f/VLDB/VLDB-2015-7900.pdf %*ALID: Scalable Dominant Cluster Detection. 826 – 837 %@Lingyang Chu, Shuhui Wang, Siyuan Liu, Qingming Huang, Jian Pei %t2015 %cVLDB %f/VLDB/VLDB-2015-7901.pdf %*An Efficient Similarity Search Framework for SimRank over Large Dynamic Graphs. 838 – 84 %@Yingxia Shao, Bin Cui, Lei Chen, Mingming Liu, Xing Xie %t2015 %cVLDB %f/VLDB/VLDB-2015-7902.pdf %*Compaction Management in Distributed Key-Value Datastores. 850 – 861 %@Muhammad Yousuf Ahmad, Bettina Kemme %t2015 %cVLDB %f/VLDB/VLDB-2015-7903.pdf %*D2P: Distance-Based Differential Privacy in Recommenders. 862 – 873 %@Rachid Guerraoui, Anne-Marie Kermarrec, Rhicheek Patra, Mahsa Taziki %t2015 %cVLDB %f/VLDB/VLDB-2015-7904.pdf %*FrogWild! – Fast PageRank Approximations on Graph Engines. 874 – 885 %@Ioannis Mitliagkas, Michael Borokhovich, Alexandros G. Dimakis, Constantine Caramanis %t2015 %cVLDB %f/VLDB/VLDB-2015-7905.pdf %*Optimal Probabilistic Cache Stampede Prevention. 886 – 897 %@Andrea Vattani, Flavio Chierichetti, Keegan Lowenstein %t2015 %cVLDB %f/VLDB/VLDB-2015-7906.pdf %*Front Matter %@Fatma Ó¦zcan %t2015 %cVLDB %f/VLDB/VLDB-2015-7907.pdf %*DAQ: A New Paradigm for Approximate Query Processing %@Navneet Potti, Jignesh M. Patel %t2015 %cVLDB %f/VLDB/VLDB-2015-7908.pdf %*A Scalable Search Engine for Mass Storage Smart Objects %@Nicolas Anciaux, Saliha Lallali, Iulian Sandu Popa, Philippe Pucheral %t2015 %cVLDB %f/VLDB/VLDB-2015-7909.pdf %*Schema Management for Document Stores %@Lanjun Wang, Oktie Hassanzadeh, Shuo Zhang, Juwei Shi, Limei Jiao, Jia Zou, and Chen Wang %t2015 %cVLDB %f/VLDB/VLDB-2015-7910.pdf %*On the Surprising Difficulty of Simple Things: the Case of Radix Partitioning %@Felix Martin Schuhknecht, Pankaj Khanchandani, Jens Dittrich %t2015 %cVLDB %f/VLDB/VLDB-2015-7911.pdf %*Knowledge-Based Trust: Estimating the Trustworthiness of Web Sources %@Xin Luna Dong, Evgeniy Gabrilovich, Kevin Murphy, Van Dang Wilko Horn, Camillo Lugaresi, Shaohua Sun, Wei Zhang %t2015 %cVLDB %f/VLDB/VLDB-2015-7912.pdf %*Giraph Unchained: Barrierless Asynchronous Parallel Execution in Pregel-like Graph Processing System %@Minyang Han, Khuzaima Daudjee %t2015 %cVLDB %f/VLDB/VLDB-2015-7913.pdf %*Work-Efficient Parallel Skyline Computation for the GPU %@Kenneth S. Bøgh, Sean Chester, Ira Assent %t2015 %cVLDB %f/VLDB/VLDB-2015-7914.pdf %*Front Matter %@Jignesh M. Patel %t2015 %cVLDB %f/VLDB/VLDB-2015-7915.pdf %*Scalable Subgraph Enumeration in MapReduce %@Longbin Lai, Lu Qin, Xuemin Lin, Lijun Chang %t2015 %cVLDB %f/VLDB/VLDB-2015-7916.pdf %*Indexing Highly Dynamic Hierarchical Data %@Jan Finis, Robert Brunel, Alfons Kemper, Thomas Neumann, Norman May, Franz Faerber %t2015 %cVLDB %f/VLDB/VLDB-2015-7917.pdf %*Community Detection in Social Networks: An In-depth Benchmarking Study with a Procedure-Oriented Framework %@Meng Wang, Chaokun Wang, Jeffrey Xu Yu, Jun Zhang %t2015 %cVLDB %f/VLDB/VLDB-2015-7918.pdf %*Growing a Graph Matching from a Handful of Seeds %@Ehsan Kazemi, S. Hamed Hassani, Matthias Grossglauser %t2015 %cVLDB %f/VLDB/VLDB-2015-7919.pdf %*Reliable Diversity-Based Spatial Crowdsourcing by Moving Workers %@Peng Cheng, Xiang Lian, Zhao Chen, Rui Fu, Lei Chen, Jinsong Han, Jizhong Zhao %t2015 %cVLDB %f/VLDB/VLDB-2015-7920.pdf %*Leveraging History for Faster Sampling of Online Social Networks %@Zhuojie Zhou, Nan Zhang, Gautam Das %t2015 %cVLDB %f/VLDB/VLDB-2015-7921.pdf %*TOP: A Framework for Enabling Algorithmic Optimizations for Distance-Related Problems %@Yufei Ding, Xipeng Shen, Madanlal Musuvathi, Todd Mytkowicz %t2015 %cVLDB %f/VLDB/VLDB-2015-7922.pdf %*Efficient Processing of Window Functions in Analytical SQL Queries %@Viktor Leis, Kan Kundhikanjana, Alfons Kemper, Thomas Neumann %t2015 %cVLDB %f/VLDB/VLDB-2015-7923.pdf %*Real-time Targeted Influence Maximization for Online Advertisements %@Yuchen Li, Dongxiang Zhang, Kian-Lee Tan %t2015 %cVLDB %f/VLDB/VLDB-2015-7924.pdf %*Functional Dependency Discovery: An Experimental Evaluation of Seven Algorithms %@Thorsten Papenbrock, Jens Ehrlich, Jannik Marten, Tommy Neubert, Jan-Peer Rudolph, Martin Schönberg Jakob Zwiener, Felix Naumann %t2015 %cVLDB %f/VLDB/VLDB-2015-7925.pdf %*Searchlight: Enabling Integrated Search and Exploration over Large Multidimensional Data %@Alexander Kalinin, Ugur Cetintemel, Stan Zdonik %t2015 %cVLDB %f/VLDB/VLDB-2015-7926.pdf %*Privacy Implications of Database Ranking %@Md Farhadur Rahman, Weimo Liu, Saravanan Thirumuruganathan, Nan Zhang, Gautam Das %t2015 %cVLDB %f/VLDB/VLDB-2015-7927.pdf %*Front Matter %@Rainer Gemulla %t2015 %cVLDB %f/VLDB/VLDB-2015-7928.pdf %*Possible and Certain SQL Key %@Henning Köhler, Sebastian Link, Xiaofang Zhou %t2015 %cVLDB %f/VLDB/VLDB-2015-7929.pdf %*Scaling Similarity Joins over Tree-Structured Data %@Yu Tang, Yilun Cai, Nikos Mamoulis %t2015 %cVLDB %f/VLDB/VLDB-2015-7930.pdf %*Worker Skill Estimation in Team-Based Tasks %@Habibur Rahman, Saravanan Thirumuruganathan, Senjuti Basu Roy, Sihem Amer-Yahia, Gautam Das %t2015 %cVLDB %f/VLDB/VLDB-2015-7931.pdf %*DPT: Differentially Private Trajectory Synthesis Using Hierarchical Reference Systems %@Xi He, Graham Cormode, Ashwin Machanavajjhala, Cecilia M. Procopiuc, Divesh Srivastava %t2015 %cVLDB %f/VLDB/VLDB-2015-7932.pdf %*Supporting Scalable Analytics with Latency Constraints %@Boduo Li, Yanlei Diao, Prashant Shenoy %t2015 %cVLDB %f/VLDB/VLDB-2015-7933.pdf %*SCAN++: Efficient Algorithm for Finding Clusters, Hubs and Outliers on Large-scale Graphs %@Hiroaki Shiokawa, Yasuhiro Fujiwara, Makoto Onizuka %t2015 %cVLDB %f/VLDB/VLDB-2015-7934.pdf %*Rethinking serializable multiversion concurrency control %@Jose M. Faleiro, Daniel J. Abadi %t2015 %cVLDB %f/VLDB/VLDB-2015-7935.pdf %*Rank aggregation with ties: Experiments and Analysis %@Bryan Brancotte, Bo Yang, Guillaume Blin, Sarah Cohen-Boulakia, Alain Denise, Sylvie Hamel %t2015 %cVLDB %f/VLDB/VLDB-2015-7936.pdf %*GraphMat: High performance graph analytics made productive %@Narayanan Sundaram, Nadathur Satish, Md Mostofa Ali Patwary, Subramanya R Dulloor, Michael J. Anderson, Satya Gautam Vadlamudi, Dipankar Das, Pradeep Dubey %t2015 %cVLDB %f/VLDB/VLDB-2015-7937.pdf %*Mega-KV: A Case for GPUs to Maximize the Throughput of In-Memory Key-Value Stores %@Kai Zhang, Kaibo Wang, Yuan Yuan, Lei Guo, Rubao Lee, Xiaodong Zhang %t2015 %cVLDB %f/VLDB/VLDB-2015-7938.pdf %*Taming Subgraph Isomorphism for RDF Query Processing %@Jinha Kim, Hyungyu Shin, Wook-Shin Han, Sungpack Hong, Hassan Chafi %t2015 %cVLDB %f/VLDB/VLDB-2015-7939.pdf %*SnapToQuery: Providing Interactive Feedback during Exploratory Query Specification %@Lilong Jiang, Arnab Nandi %t2015 %cVLDB %f/VLDB/VLDB-2015-7940.pdf %*GraphTwist: Fast Iterative Graph Computation with Two-tier Optimizations %@Yang Zhou, Ling Liu, Kisung Lee, Qi Zhang %t2015 %cVLDB %f/VLDB/VLDB-2015-7941.pdf %*SIMD- and Cache-Friendly Algorithm for Sorting an Array of Structures %@Hiroshi Inoue, Kenjiro Taura %t2015 %cVLDB %f/VLDB/VLDB-2015-7942.pdf %*Enriching Data Imputation with Extensive Similarity Neighbors %@Shaoxu Song, Aoqian Zhang, Lei Chen, Jianmin Wang %t2015 %cVLDB %f/VLDB/VLDB-2015-7943.pdf %*To Lock, Swap, or Elide: On the Interplay of Hardware Transactional Memory and Lock-Free Indexing %@Darko Makreshanski, Justin Levandoski, Ryan Stutsman %t2015 %cVLDB %f/VLDB/VLDB-2015-7944.pdf %*Incremental Knowledge Base Construction Using DeepDive %@Jaeho Shin, Sen Wu, Feiran Wang, Christopher De Sa, Ce Zhang, Christopher Ré %t2015 %cVLDB %f/VLDB/VLDB-2015-7945.pdf %*Learning User Preferences By Adaptive Pairwise Comparison %@Li Qian, Jinyang Gao, H. V. Jagadish %t2015 %cVLDB %f/VLDB/VLDB-2015-7946.pdf %*Aggregate Estimations over Location Based Services %@Weimo Liu, Md Farhadur Rahman, Saravanan Thirumuruganathan, Nan Zhang, Gautam Das %t2015 %cVLDB %f/VLDB/VLDB-2015-7947.pdf %*Principles of Dataset Versioning: Exploring the Recreation/Storage Tradeoff %@Souvik Bhattacherjee, Amit Chavan, Silu Huang, Amol Deshpande, Aditya Parameswaran %t2015 %cVLDB %f/VLDB/VLDB-2015-7948.pdf %*SEMA-JOIN: Joining Semantically-Related Tables Using Big Table Corpora %@Yeye He, Kris Ganjam, Xu Chu %t2015 %cVLDB %f/VLDB/VLDB-2015-7949.pdf %*Stale View Cleaning: Getting Fresh Answers from Stale Materialized Views %@Sanjay Krishnan, Jiannan Wang, Michael J. Franklin, Ken Goldberg, Tim Kraska %t2015 %cVLDB %f/VLDB/VLDB-2015-7950.pdf %*Compressed Spatial Hierarchical Bitmap (cSHB) Indexes for Efficiently Processing Spatial Range Query Workloads %@Parth Nagarkar, K. Selçuk Candan, Aneesha Bhat %t2015 %cVLDB %f/VLDB/VLDB-2015-7951.pdf %*Selective Provenance for Datalog Programs Using Top-K Queries %@Daniel Deutch, Amir Gilad, Yuval Moskovitch %t2015 %cVLDB %f/VLDB/VLDB-2015-7952.pdf %*Processing of Probabilistic Skyline Queries Using MapReduce %@Yoonjae Park, Jun-Ki Min, Kyuseok Shim %t2015 %cVLDB %f/VLDB/VLDB-2015-7953.pdf %*Bonding Vertex Sets Over Distributed Graph: A Betweenness Aware Approach %@Xiaofei Zhang, Hong Cheng, Lei Chen %t2015 %cVLDB %f/VLDB/VLDB-2015-7954.pdf %*A Natural Language Interface for Querying General and Individual Knowledge %@Yael Amsterdamer, Anna Kukliansky, Tova Milo %t2015 %cVLDB %f/VLDB/VLDB-2015-7955.pdf %*Scaling Up Concurrent Main-Memory Column-Store Scans: Towards Adaptive NUMA-aware Data and Task Placement %@Iraklis Psaroudakis, Tobias Scheuer, Norman May, Abdelkader Sellami, Anastasia Ailamaki %t2015 %cVLDB %f/VLDB/VLDB-2015-7956.pdf %*SQLite Optimization with Phase Change Memory for Mobile Applications %@Gihwan Oh, Sangchul Kim, Sang-Won Lee, Bongki Moon %t2015 %cVLDB %f/VLDB/VLDB-2015-7957.pdf %*An Architecture for Compiling UDF-centric Workflows %@Andrew Crotty, Alex Galakatos, Kayhan Dursun, Tim Kraska, Carsten Binnig, Ugur Cetintemel, Stan Zdonik %t2015 %cVLDB %f/VLDB/VLDB-2015-7958.pdf %*A Scalable Distributed Graph Partitioner. %@Daniel Margo, Margo Seltzer %t2015 %cVLDB %f/VLDB/VLDB-2015-7959.pdf %*Take me to your leader! Online Optimization of Distributed Storage Configurations %@Artyom Sharov, Alexander Shraer, Arif Merchant, Murray Stokely %t2015 %cVLDB %f/VLDB/VLDB-2015-7960.pdf %*Association Rules with Graph Patterns %@Wenfei Fan, Xin Wang, Yinghui Wu, Jingbo Xu %t2015 %cVLDB %f/VLDB/VLDB-2015-7961.pdf %*Fuzzy Joins in MapReduce: An Experimental Study %@Ben Kimmett, Venkatesh Srinivasan, Alex Thomo %t2015 %cVLDB %f/VLDB/VLDB-2015-7962.pdf %*PARADIS: An Efficient Parallel Algorithm for In-place Radix Sort %@Minsik Cho, Daniel Brand, Rajesh Bordawekar, Ulrich Finkler, Vincent Kulandaisamy, Ruchir Puri %t2015 %cVLDB %f/VLDB/VLDB-2015-7963.pdf %*Join Size Estimation Subject to Filter Conditions %@David Vengerov, Andre Cavalheiro Menck, Mohamed Zait, Sunil P. Chakkappen %t2015 %cVLDB %f/VLDB/VLDB-2015-7964.pdf %*Asynchronous and Fault-Tolerant Recursive Datalog Evaluation in Shared-Nothing Engines %@Jingjing Wang, Magdalena Balazinska, Daniel Halperin %t2015 %cVLDB %f/VLDB/VLDB-2015-7965.pdf %*Maximum Rank Query %@Kyriakos Mouratidis, Jilian Zhang, HweeHwa Pang %t2015 %cVLDB %f/VLDB/VLDB-2015-7966.pdf %*Performance and Scalability of Indexed Subgraph Query Processing Methods %@Foteini Katsarou, Nikos Ntarmos, Peter Triantafillou %t2015 %cVLDB %f/VLDB/VLDB-2015-7967.pdf %*Lenses: An On-Demand Approach to ETL %@Ying Yang, Niccolo Meneghetti, Ronny Fehling, Zhen Hua Liu, Oliver Kennedy %t2015 %cVLDB %f/VLDB/VLDB-2015-7968.pdf %*Keys for Graphs %@Wenfei Fan, Zhe Fan, Chao Tian, Xin Luna Dong %t2015 %cVLDB %f/VLDB/VLDB-2015-7969.pdf %*Spatial Partitioning Techniques in Spatial Hadoop %@Ahmed Eldawy, Louai Alarabi, Mohamed F. Mokbel %t2015 %cVLDB %f/VLDB/VLDB-2015-7970.pdf %*Extracting Logical Hierarchical Structure of HTML Documents Based on Headings %@Tomohiro Manabe, Keishi Tajima %t2015 %cVLDB %f/VLDB/VLDB-2015-7971.pdf %*Permutation Search Methods are Efficient, Yet Faster Search is Possible %@Bilegsaikhan Naidan, Leonid Boytsov, Eric Nyberg %t2015 %cVLDB %f/VLDB/VLDB-2015-7972.pdf %*Distributed Architecture of Oracle Database In-memory %@Niloy Mukherjee, Shasank Chavan, Maria Colgan, Dinesh Das, Mike Gleeson, Sanket Hase, Allison Holloway, Hui Jin, Jesse Kamp, Kartik Kulkarni, Tirthankar Lahiri, Juan Loaiza, Neil Macnaughton, Vineet Marwah, Atrayee Mullick, Andy Witkowski, Jiaqi Yan, Mohamed Zait %t2015 %cVLDB %f/VLDB/VLDB-2015-7973.pdf %*Argonaut: Macrotask Crowdsourcing for Complex Data Processing %@Daniel Haas, Jason Ansel, Lydia Gu, Adam Marcus %t2015 %cVLDB %f/VLDB/VLDB-2015-7974.pdf %*Building a Replicated Logging System with Apache Kafka %@Guozhang Wang, Joel Koshy, Sriram Subramanian, Kartik Paramasivam, Mammad Zadeh, Neha Narkhede, Jun Rao, Jay Kreps, Joe Stein %t2015 %cVLDB %f/VLDB/VLDB-2015-7975.pdf %*Indexing and Selecting Hierarchical Business Logic %@Alessandra Loro, Anja Gruenheid, Donald Kossmann, Damien Profeta, Philippe Beaudequin %t2015 %cVLDB %f/VLDB/VLDB-2015-7976.pdf %*Schema-Agnostic Indexing with Azure DocumentDB %@Dharma Shukla, Shireesh Thota, Karthik Raman, Madhan Gajendran, Ankur Shah, Sergii Ziuzin, Krishnan Sundaram, Miguel Gonzalez Guajardo, Anna Wawrzyniak, Samer Boshra, Renato Ferreira, Mohamed Nassar, Michael Koltachev, Ji Huang, Sudipta Sengupta, Justin Levandoski, David Lomet %t2015 %cVLDB %f/VLDB/VLDB-2015-7977.pdf %*JetScope: Reliable and Interactive Analytics at Cloud Scale %@Eric Boutin, Paul Brett, Xiaoyu Chen, Jaliya Ekanayake, Tao Guan, Anna Korsun, Zhicheng Yin, Nan Zhang, Jingren Zhou %t2015 %cVLDB %f/VLDB/VLDB-2015-7978.pdf %*Differential Privacy in Telco Big Data Platform %@Xueyang Hu, Mingxuan Yuan, Jianguo Yao, Yu Deng, Lei Chen, Qiang Yang, Haibing Guan, Jia Zeng %t2015 %cVLDB %f/VLDB/VLDB-2015-7979.pdf %*Optimization of Common Table Expressions in MPP Database Systems %@Amr El-Helw, Venkatesh Raghavan, Mohamed A. Soliman, George Caragea, Zhongxian Gu, Michalis Petropoulos %t2015 %cVLDB %f/VLDB/VLDB-2015-7980.pdf %*Towards Scalable Real-time Analytics: An Architecture for Scale-out of OLxP Workloads %@Anil K Goel, Jeffrey Pound, Nathan Auch, Peter Bumbulis, Scott MacLean, Franz Farber, Francis Gropengiesser, Christian Mathis, Thomas Bodner, Wolfgang Lehner %t2015 %cVLDB %f/VLDB/VLDB-2015-7981.pdf %*Real-Time Analytical Processing with SQL Server %@Per-Åke Larson, Adrian Birka, Eric N. Hanson, Weiyun Huang, Michal Nowakiewicz, Vassilis Papadimos %t2015 %cVLDB %f/VLDB/VLDB-2015-7983.pdf %*Efficient Evaluation of Object-Centric Exploration Queries for Visualization %@You Wu, Boulos Harb, Jun Yang, Gong Yu %t2015 %cVLDB %f/VLDB/VLDB-2015-7984.pdf %*Gobblin: Unifying Data Ingestion for Hadoop %@Lin Qiao, Yinan Li, Sahil Takiar, Ziyang Liu, Narasimha Veeramreddy, Min Tu, Ying Dai, Issac Buenrostro, Kapil Surlaker, Shirshanka Das, Chavdar Botev %t2015 %cVLDB %f/VLDB/VLDB-2015-7985.pdf %*Query Optimization in Oracle 12c Database In-Memory %@Dinesh Das, Jiaqi Yan, Mohamed Zait, Satyanarayana R Valluri, Nirav Vyas, Ramarajan Krishnamachari, Prashant Gaharwar, Jesse Kamp, Niloy Mukherjee %t2015 %cVLDB %f/VLDB/VLDB-2015-7986.pdf %*Live Programming in the LogicBlox System: A MetaLogiQL Approach %@Todd J. Green, Dan Olteanu, Geoffrey Washburn %t2015 %cVLDB %f/VLDB/VLDB-2015-7987.pdf %*The Dataflow Model: A Practical Approach to Balancing Correctness, Latency, and Cost in Massive-Scale, Unbounded, Out-of-Order Data Processing %@Tyler Akidau, Robert Bradshaw, Craig Chambers, Slava Chernyak, Rafael J. Fernandez-Moctezuma, Reuven Lax, Sam McVeety, Daniel Mills, Frances Perry, Eric Schmidt, Sam Whittle %t2015 %cVLDB %f/VLDB/VLDB-2015-7988.pdf %*One Trillion Edges: Graph Processing at Facebook-Scale %@Avery Ching, Sergey Edunov, Maja Kabiljo, Dionysios Logothetis, Sambavi Muthukrishnan %t2015 %cVLDB %f/VLDB/VLDB-2015-7989.pdf %*Gorilla: A Fast, Scalable, In-Memory Time Series Database %@Tuomas Pelkonen, Scott Franklin, Paul Cavallaro, Qi Huang, Justin Meza, Justin Teller, Kaushik Veeraraghavan %t2015 %cVLDB %f/VLDB/VLDB-2015-7990.pdf %*ConfSeer: Leveraging Customer Support Knowledge Bases for Automated Misconfiguration Detection %@Rahul Potharaju, Joseph Chan, Luhui Hu, Cristina Nita-Rotaru, Mingshi Wang, Liyuan Zhang, Navendu Jain %t2015 %cVLDB %f/VLDB/VLDB-2015-7991.pdf %*Scaling Spark in the Real World: Performance and Usability %@Michael Armbrust, Tathagata Das, Aaron Davidson, Ali Ghodsi, Andrew Or, Josh Rosen, Ion Stoica, Patrick Wendell, Reynold Xin, Matei Zaharia %t2015 %cVLDB %f/VLDB/VLDB-2015-7992.pdf %*StarDB: A Large-Scale DBMS for Strings %@Majed Sahli, Essam Mansour, Panos Kalnis %t2015 %cVLDB %f/VLDB/VLDB-2015-7993.pdf %*Evaluating SPARQL Queries on Massive RDF Datasets %@Razen Harbi, Ibrahim Abdelaziz, Panos Kalnis, Nikos Mamoulis %t2015 %cVLDB %f/VLDB/VLDB-2015-7994.pdf %*A Topic-based Reviewer Assignment System %@Ngai Meng Kou, Leong Hou U, Nikos Mamoulis, Yuhong Li, Ye Li, Zhiguo Gong %t2015 %cVLDB %f/VLDB/VLDB-2015-7995.pdf %*Data Profiling with Metanome %@Thorsten Papenbrock, Tanja Bergmann, Moritz Finke, Jakob Zwiener, Felix Naumann %t2015 %cVLDB %f/VLDB/VLDB-2015-7997.pdf %*Demonstration of Santoku: Optimizing Machine Learning over Normalized Data %@Arun Kumar, Mona Jalal, Boqun Yan, Jeffrey Naughton, Jignesh M. Patel %t2015 %cVLDB %f/VLDB/VLDB-2015-7998.pdf %*PRISM: Concept-preserving Summarization of Top-K Social Image Search Results %@Boon Siew Seah, Sourav S Bhowmick, Aixin Sun %t2015 %cVLDB %f/VLDB/VLDB-2015-7999.pdf %*Provenance for SQL through Abstract Interpretation: Value-less, but Worthwhile %@Tobias Muller, Torsten Grust %t2015 %cVLDB %f/VLDB/VLDB-2015-8000.pdf %*SDB: A Secure Query Processing System with Data Interoperability. %@Zhian He, Wai Kit Wong, Ben Kao, David Wai Lok Cheung, Rongbin Li, Siu Ming Yiu, Eric Lo %t2015 %cVLDB %f/VLDB/VLDB-2015-8001.pdf %*SPARTex: A Vertex-Centric Framework for RDF Data Analytics %@Ibrahim Abdelaziz, Razen Harbi, Semih Salihoglu, Panos Kalnis, Nikos Mamoulis %t2015 %cVLDB %f/VLDB/VLDB-2015-8002.pdf %*I2RS: A Distributed Geo-Textual Image Retrieval and Recommendation System %@Lu Chen, Yunjun Gao, Zhihao Xing, Christian S. Jensen, Gang Chen %t2015 %cVLDB %f/VLDB/VLDB-2015-8003.pdf %*Reformulation-based query answering in RDF: alternatives and performance %@Damian Bursztyn, Francois Goasdoue, Ioana Manolescu %t2015 %cVLDB %f/VLDB/VLDB-2015-8004.pdf %*SAASFEE: Scalable Scientific Workflow Execution Engine %@Marc Bux, Jorgen Brandt, Carsten Lipka, Kamal Hakimzadeh, Jim Dowling, Ulf Leser %t2015 %cVLDB %f/VLDB/VLDB-2015-8005.pdf %*A Demonstration of HadoopViz: An Extensible MapReduce System for Visualizing Big Spatial Data %@Ahmed Eldawy, Mohamed F. Mokbel, Christopher Jonathan %t2015 %cVLDB %f/VLDB/VLDB-2015-8006.pdf %*QOCO: A Query Oriented Data Cleaning System with Oracles %@Moria Bergman, Tova Milo, Slava Novgorodov, Wang-Chiew Tan %t2015 %cVLDB %f/VLDB/VLDB-2015-8007.pdf %*TreeScope: Finding Structural Anomalies In Semi-Structured Data %@Shanshan Ying, Flip Korn, Barna Saha, Divesh Srivastava %t2015 %cVLDB %f/VLDB/VLDB-2015-8008.pdf %*A Demonstration of the BigDAWG Polystore System %@A. Elmore, J. Duggan, M. Stonebraker, M. Balazinska, U. Cetintemel, V. Gadepally, J. Heer, B. Howe, J. Kepner, T. Kraska, S. Madden, D. Maier, T. Mattson, S. Papadopoulos, J. Parkhurst, N. Tatbul, M. Vartak, S. Zdonik %t2015 %cVLDB %f/VLDB/VLDB-2015-8009.pdf %*RINSE: Interactive Data Series Exploration with ADS+ %@Kostas Zoumpatianos, Stratos Idreos, Themis Palpanas %t2015 %cVLDB %f/VLDB/VLDB-2015-8010.pdf %*Collaborative Data Analytics with DataHub %@Anant Bhardwaj, Amol Deshpande, Aaron J. Elmore, David Karger, Sam Madden, Aditya Parameswaran, Harihar Subramanyam, Eugene Wu, Rebecca Zhang %t2015 %cVLDB %f/VLDB/VLDB-2015-8011.pdf %*Mindtagger: A Demonstration of Data Labeling in Knowledge Base Construction %@Jaeho Shin, Christopher Re, Michael Cafarella %t2015 %cVLDB %f/VLDB/VLDB-2015-8012.pdf %*Perseus: An Interactive Large-Scale Graph Mining and Visualization Tool %@Danai Koutra, Di Jin, Yuanshi Ning, Christos Faloutsos %t2015 %cVLDB %f/VLDB/VLDB-2015-8013.pdf %*Smart Drill-Down: A New Data Exploration Operator %@Manas Joglekar, Hector Garcia-Molina, Aditya Parameswaran %t2015 %cVLDB %f/VLDB/VLDB-2015-8014.pdf %*Virtual eXist-db: Liberating Hierarchical Queries from the Shackles of Access Path Dependence %@Curtis E. Dyreson, Sourav S Bhowmick, Ryan Grapp %t2015 %cVLDB %f/VLDB/VLDB-2015-8015.pdf %*Annotating Database Schemas to Help Enterprise Search %@Eli Cortez, Philip A. Bernstein, Yeye He, Lev Novik %t2015 %cVLDB %f/VLDB/VLDB-2015-8016.pdf %*VIIQ: Auto-Suggestion Enabled Visual Interface for Interactive Graph Query Formulation %@Nandish Jayaram, Sidharth Goyal, Chengkai Li %t2015 %cVLDB %f/VLDB/VLDB-2015-8017.pdf %*FLORIN – A System to Support (Near) Real-Time Applications on User Generated Content on Daily News %@Qingyuan Liu, Eduard C. Dragut, Arjun Mukherjee, Weiyi Meng %t2015 %cVLDB %f/VLDB/VLDB-2015-8018.pdf %*VINERy: A Visual IDE for Information Extraction %@Yunyao Li, Elmer Kim, Marc A. Touchette, Ramiya Venkatachalam, Hao Wang %t2015 %cVLDB %f/VLDB/VLDB-2015-8019.pdf %*KATARA: Reliable Data Cleaning with Knowledge Bases and Crowdsourcing %@Xu Chu, Mourad Ouzzani, John Morcos, Ihab F. Ilyas, Paolo Papotti, Nan Tang, Yin Ye %t2015 %cVLDB %f/VLDB/VLDB-2015-8020.pdf %*GIS Navigation Boosted by Column Stores %@Foteini Alvanaki, Romulo Goncalves, Milena Ivanovaa, Martin Kersten, Kostis Kyzirakos %t2015 %cVLDB %f/VLDB/VLDB-2015-8021.pdf %*Gain Control over your Integration Evaluations %@Patricia C. Arocena, Radu Ciucanu, Boris Glavic, Renee J. Miller %t2015 %cVLDB %f/VLDB/VLDB-2015-8022.pdf %*AIDE: An Automatic User Navigation System for Interactive Data Exploration %@Yanlei Diao, Kyriaki Dimitriadou, Zhan Li, Wenzhao Liu, Olga Papaemmanouil, Kemi Peng, Liping Peng %t2015 %cVLDB %f/VLDB/VLDB-2015-8023.pdf %*A Demonstration of AQWA: Adaptive Query-Workload-Aware Partitioning of Big Spatial Data %@Ahmed M. Aly, Ahmed S. Abdelhamid, Ahmed R. Mahmood, Walid G. Aref, Mohamed S. Hassan, Hazem Elmeleegy, Mourad Ouzzani %t2015 %cVLDB %f/VLDB/VLDB-2015-8024.pdf %*Janiform Intra-Document Analytics for Reproducible Research %@Jens Dittrich, Patrick Bender %t2015 %cVLDB %f/VLDB/VLDB-2015-8025.pdf %*A Framework for Clustering Uncertain Data %@Erich Schubert, Alexander Koos, Tobias Emrich, Andreas Zufle, Klaus Arthur Schmid, Arthur Zimek %t2015 %cVLDB %f/VLDB/VLDB-2015-8026.pdf %*EFQ: Why-Not Answer Polynomials in Action %@Nicole Bidoit, Melanie Herschel, Katerina Tzompanaki %t2015 %cVLDB %f/VLDB/VLDB-2015-8027.pdf %*Error Diagnosis and Data Profiling with Data X-Ray. %@Xiaolan Wang, Mary Feng, Yue Wang, Xin Luna Dong, Alexandra Meliou %t2015 %cVLDB %f/VLDB/VLDB-2015-8028.pdf %*Sharing and Reproducing Database Applications %@Quan Pham, Severin Thaler, Tanu Malik, Ian Foster, Boris Glavic %t2015 %cVLDB %f/VLDB/VLDB-2015-8029.pdf %*A Demonstration of TripleProv: Tracking and Querying Provenance over Web Data %@Marcin Wylot, Philippe Cudre-Mauroux, Paul Groth %t2015 %cVLDB %f/VLDB/VLDB-2015-8030.pdf %*WADaR: Joint Wrapper and Data Repair %@Stefano Ortona, Giorgio Orsi, Marcello Buoncristiano, Tim Furche %t2015 %cVLDB %f/VLDB/VLDB-2015-8031.pdf %*DATASPREAD: Unifying Databases and Spreadsheets %@Mangesh Bendre, Bofan Sun, Ding Zhang, Xinyan Zhou, Kevin Chen-Chuan Chang, Aditya Parameswaran %t2015 %cVLDB %f/VLDB/VLDB-2015-8032.pdf %*Wisteria: Nurturing Scalable Data Cleaning Infrastructure %@Daniel Haas, Sanjay Krishnan, Jiannan Wang, Michael J. Franklin, Eugene Wu %t2015 %cVLDB %f/VLDB/VLDB-2015-8033.pdf %*CODD: A Dataless Approach to Big Data Testing %@Ashoke S., Jayant R. Haritsa %t2015 %cVLDB %f/VLDB/VLDB-2015-8034.pdf %*Query-Oriented Summarization of RDF Graphs %@Sejla Cebiric, Francois Goasdoue, Ioana Manolescu %t2015 %cVLDB %f/VLDB/VLDB-2015-8035.pdf %*Universal-DB: Towards Representation Independent Graph Analytics %@Yodsawalai Chodpathumwan, Amirhossein, Aleyasen, Arash Termehchy, Yizhou Sun %t2015 %cVLDB %f/VLDB/VLDB-2015-8036.pdf %*Tornado: A Distributed Spatio-Textual Stream Processing System %@Ahmed R. Mahmood, Ahmed M. Aly, Thamir Qadah, El Kindi Rezig, Anas Daghistani, Amgad Madkour, Ahmed S. Abdelhamid, Mohamed S. Hassan, Walid G. Aref, Seleh Basalamah %t2015 %cVLDB %f/VLDB/VLDB-2015-8037.pdf %*Vizdom: Interactive Analytics through Pen and Touch %@Andrew Crotty, Alex Galakatos, Emanuel Zgraggen, Carsten Binnig, Tim Kraska %t2015 %cVLDB %f/VLDB/VLDB-2015-8038.pdf %*S+EPPs: Construct and Explore Bisimulation Summaries, plus Optimize Navigational Queries; all on Existing SPARQL Systems %@Mariano P. Consens, Valeria Fionda, Shahan Khatchadourian, Giuseppe Pirro %t2015 %cVLDB %f/VLDB/VLDB-2015-8039.pdf %*GraphGen: Exploring Interesting Graphs in Relational Data %@Konstantinos Xirogiannopoulos, Udayan Khurana, Amol Deshpande %t2015 %cVLDB %f/VLDB/VLDB-2015-8040.pdf %*DBSeer: Pain-free Database Administration through Workload Intelligence %@Dong Young Yoon, Barzan Mozafari, Douglas P. Brown %t2015 %cVLDB %f/VLDB/VLDB-2015-8041.pdf %*Real Time Analytics: Algorithms and Systems %@Arun Kejariwal, Sanjeev Kulkarni, Karthik Ramasamy %t2015 %cVLDB %f/VLDB/VLDB-2015-8042.pdf %*On Uncertain Graphs Modeling and Queries %@Arijit Khan, Lei Chen %t2015 %cVLDB %f/VLDB/VLDB-2015-8043.pdf %*A Time Machine for Information: Looking Back to Look Forward %@Xin Luna Dong, Wang-Chiew Tan %t2015 %cVLDB %f/VLDB/VLDB-2015-8044.pdf %*Structured Analytics in Social Media %@Mahashweta Das, Gautam Das %t2015 %cVLDB %f/VLDB/VLDB-2015-8045.pdf %*Truth Discovery and Crowdsourcing Aggregation: A Unified Perspective %@Jing Gao, Qi Li, Bo Zhao, Wei Fan, Jiawei Han %t2015 %cVLDB %f/VLDB/VLDB-2015-8046.pdf %*Tutorial: SQL-on-Hadoop Systems %@Daniel Abadi, Shivnath Babu, Fatma Ozcan, Ippokratis Pandis %t2015 %cVLDB %f/VLDB/VLDB-2015-8047.pdf %*Engineering Database Hardware and Software Together. %@Juan Loaiza %t2015 %cVLDB %f/VLDB/VLDB-2015-8048.pdf %*Big Data Research: Will Industry Solve all the Problems? %@Magdalena Balazinska %t2015 %cVLDB %f/VLDB/VLDB-2015-8049.pdf %*Big Plateaus of Big Data on the Big Island %@Todd Walter %t2015 %cVLDB %f/VLDB/VLDB-2015-8050.pdf %*Databases and Hardware: The Beginning and Sequel of a Beautiful Friendship %@Anastasia Ailamaki %t2015 %cVLDB %f/VLDB/VLDB-2015-8051.pdf %*AQWA: Adaptive Query-Workload-Aware Partitioning of Big Spatial Data %@Ahmed M. Aly, Ahmed R. Mahmood, Mohamed S. Hassan, Walid G. Aref, Mourad Ouzzani, Hazem Elmeleegy, Thamir Qadah %t2015 %cVLDB %f/VLDB/VLDB-2015-8052.pdf %*Lightning Fast and Space Efficient Inequality Joins %@Zuhair Khayyat, William Lucia, Meghna Singh, Mourad Ouzzani, Paolo Papotti, Jorge-Arnulfo Quiane-Ruiz, Nan Tang, Panos Kalnis %t2015 %cVLDB %f/VLDB/VLDB-2015-8053.pdf %*Finding Pareto Optimal Groups: Group-based Skyline %@Jinfei Liu, Li Xiong, Jian Pei, Jun Luo, Haoyu Zhang %t2015 %cVLDB %f/VLDB/VLDB-2015-8054.pdf %*k-Regret Queries with Nonlinear Utilities %@Taylor Kessler Faulkner, Will Brackenbury, Ashwin Lall %t2015 %cVLDB %f/VLDB/VLDB-2015-8055.pdf %*Clash of the Titans: MapReduce vs. Spark for Large Scale Data Analytics %@Juwei Shi, Yunjie Qiu, Umar Farooq Minhas, Limei Jiao, Chen Wang, Berthold Reinwald, Fatma Ozcan %t2015 %cVLDB %f/VLDB/VLDB-2015-8056.pdf %*Towards Maximum Independent Sets on Massive Graphs %@Yu Liu, Jiaheng Lu, Hua Yang, Xiaokui Xiao, Zhewei Wei %t2015 %cVLDB %f/VLDB/VLDB-2015-8057.pdf %*S-Store: Streaming Meets Transaction Processing %@John Meehan, Nesime Tatbul, Stan Zdonik, Cansu Aslantas, Ugur Cetintemel, Jiang Du, Tim Kraska, Samuel Madden, David Maier, Andrew Pavlo, Michael Stonebraker, Kristin Tufte, Hao Wang %t2015 %cVLDB %f/VLDB/VLDB-2015-8058.pdf %*Multi-Version Range Concurrency Control in Deuteronomy %@Justin Levandoski, David Lomet, Sudipta Sengupta, Ryan Stutsman, Rui Wang %t2015 %cVLDB %f/VLDB/VLDB-2015-8059.pdf %*Query From Examples: An Iterative, Data-Driven Approach to Query Construction %@Hao Li, Chee-Yong Chan, David Maier %t2015 %cVLDB %f/VLDB/VLDB-2015-8060.pdf %*Tracking the Conductance of Rapidly Evolving Topic-Subgraphs %@Sainyam Galhotra, Amitabha Bagchi, Srikanta Bedathur, Maya Ramanath, Vidit Jain %t2015 %cVLDB %f/VLDB/VLDB-2015-8061.pdf %*SEEDB: Efficient Data-Driven Visualization Recommendations to Support Visual Analytics %@Manasi Vartak, Sajjadur Rahman, Samuel Madden, Aditya Parameswaran, Neoklis Polyzotis %t2015 %cVLDB %f/VLDB/VLDB-2015-8062.pdf %*DEXTER: Large-Scale Discovery and Extraction of Product Specifications on the Web %@Disheng Qiu, Luciano Barbosa, Xin Luna Dong, Yanyan Shen, Divesh Srivastava %t2015 %cVLDB %f/VLDB/VLDB-2015-8063.pdf %*Optimizing Display Advertising in Online Social Networks %@Zeinab Abbassi , Aditya Bhaskara , Vishal Misra %t2015 %cwww %f/www/www-2015-8064.pdf %*Frankenplace: Interactive Thematic Mapping for Ad Hoc Exploratory Search %@Benjamin Adams , Grant McKenzie , Mark Gahegan %t2015 %cwww %f/www/www-2015-8065.pdf %*Towards Reconciling SPARQL and Certain Answers %@Shqiponja Ahmetaj , Wolfgang Fischl , Reinhard Pichler , Mantas Šimkus , Sebastian Skritek %t2015 %cwww %f/www/www-2015-8066.pdf %*Donor Retention in Online Crowdfunding Communities: A Case Study of DonorsChoose.org %@Tim Althoff , Jure Leskovec %t2015 %cwww %f/www/www-2015-8067.pdf %*Budget-Constrained Item Cold-Start Handling in Collaborative Filtering Recommenders via Optimal Design %@Oren Anava , Shahar Golan , Nadav Golbandi , Zohar Karnin , Ronny Lempel , Oleg Rokhlenko , Oren Somekh %t2015 %cwww %f/www/www-2015-8068.pdf %*Improved Theoretical and Practical Guarantees for Chromatic Correlation Clustering %@Yael Anava , Noa Avigdor-Elgrabli , Iftah Gamzu %t2015 %cwww %f/www/www-2015-8069.pdf %*Global Diffusion via Cascading Invitations: Structure, Growth, and Homophily %@Ashton Anderson , Daniel Huttenlocher , Jon Kleinberg , Jure Leskovec , Mitul Tiwari %t2015 %cwww %f/www/www-2015-8070.pdf %*Recommendation Subgraphs for Web Discovery %@Arda Antikacioglu , R. Ravi , Srinath Sridhar %t2015 %cwww %f/www/www-2015-8071.pdf %*Is Sniping a Problem for Online Auction Markets? %@Matt Backus , Thomas Blake , Dimitriy V. Masterov , Steven Tadelis %t2015 %cwww %f/www/www-2015-8072.pdf %*Essential Web Pages Are Easy to Find %@Ricardo Baeza-Yates , Paolo Boldi (Università degli Studi di Milano) Flavio Chierichetti %t2015 %cwww %f/www/www-2015-8073.pdf %*Design and Analysis of Benchmarking Experiments for Distributed Internet Services %@Eytan Bakshy , Eitan Frachtenberg %t2015 %cwww %f/www/www-2015-8074.pdf %*ACCAMS: Additive Co-Clustering to Approximate Matrices Succinctly %@Alex Beutel , Amr Ahmed , Alexander J. Smola %t2015 %cwww %f/www/www-2015-8075.pdf %*Who, What, When, and Where: Multi-Dimensional Collaborative Recommendations Using Tensor Factorization on Sparse User-Generated Data %@Preeti Bhargava , Thomas Phan , Jiayu Zhou , Juhan Lee %t2015 %cwww %f/www/www-2015-8076.pdf %*Secrets, Lies, and Account Recovery: Lessons From the Use of Personal Knowledge Questions at Google %@Joseph Bonneau , Elie Bursztein , Ilan Caron , Rob Jackson , Mike Williamson %t2015 %cwww %f/www/www-2015-8077.pdf %*Supporting Ethical Web Research: A New Research Ethics Review %@Anne Bowser , Janice Y. Tsai %t2015 %cwww %f/www/www-2015-8078.pdf %*Sequential Hypothesis Tests for Adaptive Locality Sensitive Hashing %@Aniket Chakrabarti , Srinivasan Parthasarathy %t2015 %cwww %f/www/www-2015-8079.pdf %*Opinion Spam Detection in Web Forum: A Real Case Study %@Yu-Ren Chen , Hsin-Hsi Chen %t2015 %cwww %f/www/www-2015-8080.pdf %*Summarizing Entity Descriptions for Effective and Efficient Human-centered Entity Linking %@Gong Cheng , Danyun Xu , Yuzhong Qu %t2015 %cwww %f/www/www-2015-8081.pdf %*Semantic Tagging of Mathematical Expressions %@Pao-Yu Chien , Pu-Jen Cheng %t2015 %cwww %f/www/www-2015-8082.pdf %*Collaborative Ranking with a Push at the Top %@Konstantina Christakopoulou , Arindam Banerjee %t2015 %cwww %f/www/www-2015-8083.pdf %*Parallel Streaming Signature EM-Tree: A Clustering Algorithm for Web Scale Applications %@Christopher M. De Vries , Lance De Vine , Shlomo Geva , Richi Nayak %t2015 %cwww %f/www/www-2015-8084.pdf %*Network-based Origin Confusion Attacks against HTTPS Virtual Hosting %@Antoine Delignat-Lavaud , Karthikeyan Bhargavan %t2015 %cwww %f/www/www-2015-8085.pdf %*The Dynamics of Micro-Task Crowdsourcing: The Case of Amazon MTurk %@Djellel Eddine Difallah , Michele Catasta (École Polytechnique Fédérale de Lausanne) Gianluca Demartini , Panagiotis G. Ipeirotis , Philippe Cudré-Mauroux %t2015 %cwww %f/www/www-2015-8086.pdf %*Hierarchical Neural Language Models for Joint Representation of Streaming Documents and Their Content %@Nemanja Djuric , Hao Wu , Vladan Radosavljevic , Mihajlo Grbovic , Narayan Bhamidipati %t2015 %cwww %f/www/www-2015-8087.pdf %*Future User Engagement Prediction and Its Application to Improve the Sensitivity of Online Experiments %@Alexey Drutsa , Gleb Gusev , Pavel Serdyukov %t2015 %cwww %f/www/www-2015-8088.pdf %*Enriching Structured Knowledge with Open Information %@Arnab Dutta , Christian Meilicke , Heiner Stuckenschmidt %t2015 %cwww %f/www/www-2015-8089.pdf %*A Multi-View Deep Learning Approach for Cross Domain User Modeling in Recommendation Systems %@Ali Elkahky , Yang Song , Xiaodong He %t2015 %cwww %f/www/www-2015-8090.pdf %*Cookies That Give You Away: The Surveillance Implications of Web Tracking %@Steven Englehardt , Dillon Reisman , Christian Eubank , Peter Zimmerman , Jonathan Mayer , Arvind Narayanan , Edward W. Felten %t2015 %cwww %f/www/www-2015-8091.pdf %*Efficient Densest Subgraph Computation in Evolving Graphs %@Alessandro Epasto , Silvio Lattanzi , Mauro Sozio (Institut Mines-Télécom, Télécom ParisTech, CNRS LTCI, Paris) %t2015 %cwww %f/www/www-2015-8092.pdf %*A Practical Framework for Privacy-Preserving Data Analytics %@Liyue Fan , Hongxia Jin %t2015 %cwww %f/www/www-2015-8093.pdf %*Compressed Indexes for String Searching in Labeled Graphs %@Paolo Ferragina , Francesco Piccinno , Rossano Venturini %t2015 %cwww %f/www/www-2015-8094.pdf %*Improving Paid Microtasks through Gamification and Adaptive Furtherance Incentives %@Oluwaseyi Feyisetan , Elena Simperl , Max Van Kleek , Nigel Shadbolt %t2015 %cwww %f/www/www-2015-8095.pdf %*Tagging Personal Photos with Transfer Deep Learning %@Jianlong Fu , Tao Mei , Kuiyuan Yang , Hanqing Lu , Yong Rui %t2015 %cwww %f/www/www-2015-8096.pdf %*MobInsight: On Improving the Performance of Mobile Apps in Cellular Networks %@Vijay Gabale , Dilip Krishnaswamy %t2015 %cwww %f/www/www-2015-8097.pdf %*Rethinking Security of Web-Based System Applications %@Martin Georgiev , Suman Jana , Vitaly Shmatikov %t2015 %cwww %f/www/www-2015-8098.pdf %*Cardinal Contests %@Arpita Ghosh , Patrick Hummel %t2015 %cwww %f/www/www-2015-8099.pdf %*Accessible On-Line Floor Plans %@Cagatay Goncu , Anuradha Madugalla , Simone Marinai , Kim Marriott %t2015 %cwww %f/www/www-2015-8100.pdf %*Network A/B Testing: From Sampling to Estimation %@Huan Gui , Ya Xu , Anmol Bhasin , Jiawei Han %t2015 %cwww %f/www/www-2015-8101.pdf %*User Session Identification Based on Strong Regularities in Inter-Activity Time %@Aaron Halfaker , Oliver Keyes , Daniel Kluver , Jacob Thebault-Spieker , Tien Nguyen , Kenneth Shores , Anuradha Uduwage , Morten Warncke-Wang %t2015 %cwww %f/www/www-2015-8102.pdf %*Incentivizing High Quality Crowdwork %@Chien-Ju Ho , Aleksandrs Slivkins , Siddharth Suri , Jennifer Wortman Vaughan %t2015 %cwww %f/www/www-2015-8103.pdf %*Skolemising Blank Nodes while Preserving Isomorphism %@Aidan Hogan %t2015 %cwww %f/www/www-2015-8104.pdf %*Scalable Methods for Adaptively Seeding a Social Network %@Thibaut Horel , Yaron Singer %t2015 %cwww %f/www/www-2015-8105.pdf %*User Review Sites as a Resource for Large-Scale Sociolinguistic Studies %@Dirk Hovy , Anders Johannsen , Anders Søgaard %t2015 %cwww %f/www/www-2015-8106.pdf %*When Does Improved Targeting Increase Revenue? %@Patrick Hummel , R. Preston McAfee %t2015 %cwww %f/www/www-2015-8107.pdf %*Social Status and Badge Design %@Nicole Immorlica , Greg Stoddard , Vasilis Syrgkanis %t2015 %cwww %f/www/www-2015-8108.pdf %*Mapping Temporal Horizons: Analysis of Collective Future and Past Related Attention in Twitter %@Adam Jatowt , Émilien Antoine , Yukiko Kawai , Toyokazu Akiyama %t2015 %cwww %f/www/www-2015-8109.pdf %*Path Sampling: A Fast and Provable Method for Estimating 4-Vertex Subgraph Counts %@Madhav Jha , C. Seshadhri , Ali Pinar %t2015 %cwww %f/www/www-2015-8110.pdf %*Automatic Online Evaluation of Intelligent Assistants %@Jiepu Jiang , Ahmed Hassan Awadallah , Rosie Jones , Umut Ozertem , Imed Zitouni , Ranjitha Gurunath Kulkarni , Omar Zia Khan %t2015 %cwww %f/www/www-2015-8111.pdf %*Incorporating Social Context and Domain Knowledge for Entity Recognition %@Jie Tang , Zhanpeng Fang , Jimeng Sun %t2015 %cwww %f/www/www-2015-8112.pdf %*Querying Web-Scale Information Networks Through Bounding Matching Scores %@Jiahui Jin , Samamon Khemmarat , Lixin Gao , Junzhou Luo %t2015 %cwww %f/www/www-2015-8113.pdf %*LN-Annote: An Alternative Approach to Information Extraction from Emails Using Locally-Customized Named-Entity Recognition %@YoungHoon Jung , Karl Stratos , Luca P. Carloni %t2015 %cwww %f/www/www-2015-8114.pdf %*Describing and Understanding Neighborhood Characteristics through Online Social Media %@Mohamed Kafsi (École Polytechnique Fédérale de Lausanne) Henriette Cramer , Bart Thomee , David A. Shamma %t2015 %cwww %f/www/www-2015-8115.pdf %*Active Learning for Multi-relational Data Construction %@Hiroshi Kajino , Akihiro Kishimoto , Adi Botea , Elizabeth Daly , Spyros Kotoulas %t2015 %cwww %f/www/www-2015-8116.pdf %*The Social World of Content Abusers in Community Question Answering %@Imrul Kayes , Nicolas Kourtellis , Daniele Quercia , Adriana Iamnitchi , Francesco Bonchi %t2015 %cwww %f/www/www-2015-8117.pdf %*The Lifecycles of Apps in a Social Ecosystem %@Isabel Kloumann , Lada Adamic , Jon Kleinberg , Shaomei Wu %t2015 %cwww %f/www/www-2015-8118.pdf %*Getting More for Less: Optimized Crowdsourcing with Dynamic Tasks and Goals %@Ari Kobren , Chun How Tan , Panagiotis Ipeirotis , Evgeniy Gabrilovich %t2015 %cwww %f/www/www-2015-8119.pdf %*Evolution of Conversations in the Age of Email Overload %@Farshad Kooti , Luca Maria Aiello , Mihajlo Grbovic , Kristina Lerman , Amin Mantrach %t2015 %cwww %f/www/www-2015-8120.pdf %*Events and Controversies: Influences of a Shocking News Event on Information Seeking %@Danai Koutra , Paul N. Bennett , Eric Horvitz %t2015 %cwww %f/www/www-2015-8121.pdf %*Statistically Significant Detection of Linguistic Change %@Vivek Kulkarni , Rami Al-Rfou , Bryan Perozzi , Steven Skiena %t2015 %cwww %f/www/www-2015-8122.pdf %*Replacing the Irreplaceable: Fast Algorithms for Team Member Recommendation %@Liangyue Li , Hanghang Tong , Nan Cao , Kate Ehrlich , Yu-Ru Lin , Norbou Buchler %t2015 %cwww %f/www/www-2015-8123.pdf %*Robust Group Linkage %@Pei Li , Xin Luna Dong , Songtao Guo , Andrea Maurino , Divesh Srivastava %t2015 %cwww %f/www/www-2015-8124.pdf %*Uncovering the Small Community Structure in Large Networks: A Local Spectral Approach %@Yixuan Li , Kun He , David Bindel , John E. Hopcroft %t2015 %cwww %f/www/www-2015-8125.pdf %*Scalable Parallel EM Algorithms for Latent Dirichlet Allocation in Multi-Core Systems %@Xiaosheng Liu , Jia Zeng , Xi Yang , Jianfeng Yan , Qiang Yang %t2015 %cwww %f/www/www-2015-8126.pdf %*Grading the Graders: Motivating Peer Graders in a MOOC %@Yanxin Lu , Joe Warren , Christopher Jermaine , Swarat Chaudhuri , Scott Rixner %t2015 %cwww %f/www/www-2015-8127.pdf %*Measurement and Analysis of Mobile Web Cache Performance %@Yun Ma , Xuanzhe Liu , Shuhui Zhang , Ruirui Xiang , Yunxin Liu , Tao Xie %t2015 %cwww %f/www/www-2015-8128.pdf %*SCULPT: A Schema Language for Tabular Data on the Web %@Wim Martens (Universität Bayreuth) Frank Neven , Stijn Vansummeren (Université Libre de Bruxelles) %t2015 %cwww %f/www/www-2015-8129.pdf %*The Web as a Jungle: Non-Linear Dynamical Systems for Co-Evolving Online Activities %@Yasuko Matsubara , Yasushi Sakurai , Christos Faloutsos %t2015 %cwww %f/www/www-2015-8130.pdf %*Spanning Edge Centrality: Large-Scale Computation and Applications %@Charalampos Mavroforakis , Richard Garcia-Lebron , Ioannis Koutis , Evimaria Terzi %t2015 %cwww %f/www/www-2015-8131.pdf %*No Escape from Reality: Security and Privacy of Augmented Reality Browsers %@Richard McPherson , Suman Jana , Vitaly Shmatikov %t2015 %cwww %f/www/www-2015-8132.pdf %*Discovering Meta-Paths in Large Heterogeneous Information Networks %@Changping Meng , Reynold Cheng , Silviu Maniu , Pierre Senellart (Telecom ParisTech; CNRS LTCI) Wangda Zhang %t2015 %cwww %f/www/www-2015-8133.pdf %*From "Selena Gomez" to "Marlon Brando": Understanding Explorative Entity Search %@Iris Miliaraki , Roi Blanco , Mounia Lalmas %t2015 %cwww %f/www/www-2015-8134.pdf %*Children Seen But Not Heard: When Parents Compromise Children's Online Privacy %@Tehila Minkus , Kelvin Liu , Keith W. Ross %t2015 %cwww %f/www/www-2015-8135.pdf %*TrueView: Harnessing the Power of Multiple Review Sites %@Amanda J. Minnich , Nikan Chavoshi , Abdullah Mueen , Shuang Luan , Michalis Faloutsos %t2015 %cwww %f/www/www-2015-8136.pdf %*QUOTUS: The Structure of Political Media Coverage as Revealed By Quoting Patterns %@Vlad Niculae , Caroline Suen , Justine Zhang , Cristian Danescu-Niculescu-Mizil , Jure Leskovec %t2015 %cwww %f/www/www-2015-8137.pdf %*Energy and Performance of Smartphone Radio Bundling in Outdoor Environments %@Ana Nika , Yibo Zhu , Ning Ding , Abhilash Jindal , Y. Charlie Hu , Xia Zhou , Ben Y. Zhao , Haitao Zheng %t2015 %cwww %f/www/www-2015-8138.pdf %*PriVaricator: Deceiving Fingerprinters with Little White Lies %@Nick Nikiforakis , Wouter Joosen , Benjamin Livshits %t2015 %cwww %f/www/www-2015-8139.pdf %*Diagnoses, Decisions, and Outcomes: Web Search as Decision Support for Cancer %@Michael J. Paul , Ryen W. White , Eric Horvitz %t2015 %cwww %f/www/www-2015-8140.pdf %*PocketTrend: Timely Identification and Delivery of Trending Search Content to Mobile Users %@Gennady Pekhimenko , Dimitrios Lymberopoulos , Oriana Riva , Karin Strauss , Doug Burger %t2015 %cwww %f/www/www-2015-8141.pdf %*Overcoming Relational Learning Biases to Accurately Predict Preferences in Large Scale Networks %@Joseph J. Pfeiffer III , Jennifer Neville , Paul N. Bennett %t2015 %cwww %f/www/www-2015-8142.pdf %*Deriving an Emergent Relational Schema from RDF Data %@Minh-Duc Pham , Linnea Passing (Technische Universität München) Orri Erling , Peter Boncz %t2015 %cwww %f/www/www-2015-8143.pdf %*The Digital Life of Walkable Streets %@Daniele Quercia , Luca Maria Aiello , Rossano Schifanella , Adam Davies %t2015 %cwww %f/www/www-2015-8144.pdf %*Beyond Models: Forecasting Complex Network Processes Directly From Data %@Bruno Ribeiro , Minh X. Hoang , Ambuj K. Singh %t2015 %cwww %f/www/www-2015-8145.pdf %*Weakly Supervised Extraction of Computer Security Events from Twitter %@Alan Ritter , Evan Wright , William Casey , Tom Mitchell %t2015 %cwww %f/www/www-2015-8146.pdf %*Groupsourcing: Team Competition Designs for Crowdsourcing %@Markus Rokicki , Sergej Zerr , Stefan Siersdorfer %t2015 %cwww %f/www/www-2015-8147.pdf %*Authentication Melee: A Usability Analysis of Seven Web Authentication Systems %@Scott Ruoti , Brent Roberts , Kent Seamons %t2015 %cwww %f/www/www-2015-8148.pdf %*Finding the Hierarchy of Dense Subgraphs Using Nucleus Decompositions %@Ahmet Erdem Sarıyüce , C. Seshadhri , Ali Pınar , Ümit V. Çatalyürek %t2015 %cwww %f/www/www-2015-8149.pdf %*Bringing CUPID Indoor Positioning System to Practice %@Souvik Sen , Dongho Kim , Stephane Laroche , Kyu-Han Kim , Jeongkeun Lee %t2015 %cwww %f/www/www-2015-8150.pdf %*Early Detection of Spam Mobile Apps %@Suranga Seneviratne , Aruna Seneviratne , Mohamed Ali Kaafar , Anirban Mahanti , Prasant Mohapatra %t2015 %cwww %f/www/www-2015-8151.pdf %*N-gram IDF: A Global Term Weighting Scheme Based on Information Distance %@Masumi Shirakawa , Takahiro Hara , Shojiro Nishio %t2015 %cwww %f/www/www-2015-8152.pdf %*Query Suggestion and Data Fusion in Contextual Disambiguation %@Milad Shokouhi , Marc Sloan , Paul N. Bennett , Kevyn Collins-Thompson , Siranush Sarkizova %t2015 %cwww %f/www/www-2015-8153.pdf %*Asymmetric Minwise Hashing for Indexing Binary Inner Products and Set Containment %@Anshumali Shrivastava , Ping Li %t2015 %cwww %f/www/www-2015-8154.pdf %*Language Understanding in the Wild: Combining Crowdsourcing and Machine Learning %@Edwin Simpson , Matteo Venanzi , Steven Reece , Pushmeet Kohli , John Guiver , Stephen J. Roberts , Nicholas R. Jennings %t2015 %cwww %f/www/www-2015-8155.pdf %*HypTrails: A Bayesian Approach for Comparing Hypotheses About Human Trails on the Web %@Philipp Singer , Denis Helic , Andreas Hotho (University of Würzburg) Markus Strohmaier %t2015 %cwww %f/www/www-2015-8156.pdf %*Exploiting Collective Hidden Structures in Webpage Titles for Open Domain Entity Extraction %@Wei Song , Shiqi Zhao , Chao Zhang , Hua Wu , Haifeng Wang , Lizhen Liu , Hanshi Wang %t2015 %cwww %f/www/www-2015-8157.pdf %*Rocker - a Refinement Operator for Key Discovery %@Tommaso Soru , Edgard Marx , Axel-Cyrille Ngonga Ngomo %t2015 %cwww %f/www/www-2015-8158.pdf %*Random Walk TripleRush: Asynchronous Graph Querying and Sampling %@Philip Stutz , Bibek Paudel , Mihaela Verman , Abraham Bernstein %t2015 %cwww %f/www/www-2015-8159.pdf %*Open Domain Question Answering Via Semantic Enrichment %@Huan Sun , Hao Ma , Wen-tau Yih , Chen-Tse Tsai , Jingjing Liu , Ming-Wei Chang %t2015 %cwww %f/www/www-2015-8160.pdf %*All Who Wander: On the Prevalence and Characteristics of Multi-community Engagement %@Chenhao Tan , Lillian Lee %t2015 %cwww %f/www/www-2015-8161.pdf %*LINE: Large-Scale Information Network Embedding %@Jian Tang , Meng Qu , Mingzhe Wang , Ming Zhang , Jun Yan , Qiaozhu Mei %t2015 %cwww %f/www/www-2015-8162.pdf %*Leveraging Pattern Semantics for Extracting Entities in Enterprises %@Fangbo Tao , Bo Zhao , Ariel Fuxman , Yang Li , Jiawei Han %t2015 %cwww %f/www/www-2015-8163.pdf %*Density-Friendly Graph Decomposition %@Nikolaj Tatti , Aristides Gionis %t2015 %cwww %f/www/www-2015-8164.pdf %*Crowd Fraud Detection in Internet Advertising %@Tian Tian , Jun Zhu , Fen Xia , Xin Zhuang , Tong Zhang %t2015 %cwww %f/www/www-2015-8165.pdf %*Provably Fast Inference of Latent Features from Networks: With Applications to Learning Social Circles and Multilabel Classification %@Charalampos E. Tsourakakis %t2015 %cwww %f/www/www-2015-8166.pdf %*The K-Clique Densest Subgraph Problem %@Charalampos E. Tsourakakis %t2015 %cwww %f/www/www-2015-8167.pdf %*GERBIL - General Entity Annotator Benchmarking Framework %@Ricardo Usbeck , Michael Röder , Axel-Cyrille Ngonga Ngomo , Ciro Baron , Andreas Both , Martin Brümmer , Diego Ceccarelli , Marco Cornolti , Didier Cherix , Bernd Eickmann , Paolo Ferragina , Christiane Lemke , Andrea Moro , Roberto Navigli , Francesco Piccinno , Giuseppe Rizzo , Harald Sack , René Speck , Raphaël Troncy , Jörg Waitelonis , Lars Wesemann %t2015 %cwww %f/www/www-2015-8168.pdf %*An Optimization Framework for Weighting Implicit Relevance Labels for Personalized Web Search %@Yury Ustinovskiy , Gleb Gusev , Pavel Serdyukov %t2015 %cwww %f/www/www-2015-8169.pdf %*A First Look at Tribal Web Traffic %@Morgan Vigil , Matthew Rantanen , Elizabeth Belding %t2015 %cwww %f/www/www-2015-8170.pdf %*A Weighted Correlation Index for Rankings with Ties %@Sebastiano Vigna (Università degli Studi di Milano) %t2015 %cwww %f/www/www-2015-8171.pdf %*Gathering Additional Feedback on Search Results By Multi-Armed Bandits with Respect to Production Ranking %@Aleksandr Vorobev , Damien Lefortier , Gleb Gusev , Pavel Serdyukov %t2015 %cwww %f/www/www-2015-8172.pdf %*The E-Commerce Market for "Lemons": Identification and Analysis of Websites Selling Counterfeit Goods %@John Wadleigh , Jake Drew , Tyler Moore %t2015 %cwww %f/www/www-2015-8173.pdf %*Concept Expansion Using Web Tables %@Chi Wang , Kaushik Chakrabarti , Yeye He , Kris Ganjam , Zhimin Chen , Philip A. Bernstein %t2015 %cwww %f/www/www-2015-8174.pdf %*User Latent Preference Model for Better Downside Management in Recommender Systems %@Jian Wang , David Hardtke %t2015 %cwww %f/www/www-2015-8175.pdf %*The Role of Data Cap in Optimal Two-Part Network Pricing %@Xin Wang , Richard T. B. Ma , Yinlong Xu %t2015 %cwww %f/www/www-2015-8176.pdf %*Tweeting Cameras for Event Detection %@Yuhui Wang , Mohan S. Kankanhalli %t2015 %cwww %f/www/www-2015-8177.pdf %*Mining Missing Hyperlinks from Human Navigation Traces: A Case Study of Wikipedia %@Robert West , Ashwin Paranjape , Jure Leskovec %t2015 %cwww %f/www/www-2015-8178.pdf %*Semantic Annotaion of Mobility Data Using Social Media %@Fei Wu , Zhenhui Li , Wang-Chien Lee , Hongjian Wang , Zhuojie Huang %t2015 %cwww %f/www/www-2015-8179.pdf %*Automatic Web Content Extraction By Combination of Learning and Grouping %@Shanchan Wu , Jerry Liu , Jian Fan %t2015 %cwww %f/www/www-2015-8180.pdf %*Executing Provenance-Enabled Queries over Web Data %@Marcin Wylot , Philippe Cudré-Mauroux , Paul Groth %t2015 %cwww %f/www/www-2015-8181.pdf %*Understanding Malvertising Through Ad-Injecting Browser Extensions %@Xinyu Xing , Wei Meng , Byoungyoung Lee , Udi Weinsberg , Anmol Sheth (A9.com/Amazon) Roberto Perdisci , Wenke Lee %t2015 %cwww %f/www/www-2015-8182.pdf %*E-Commerce Reputation Manipulation: The Emergence of Reputation-Escalation-as-a-Service %@Haitao Xu , Daiping Liu , Haining Wang , Angelos Stavrou %t2015 %cwww %f/www/www-2015-8183.pdf %*Effective Techniques for Message Reduction and Load Balancing in Distributed Graph Computation %@Da Yan , James Cheng , Yi Lu , Wilfred Ng %t2015 %cwww %f/www/www-2015-8184.pdf %*Tackling the Achilles Heel of Social Networks: Influence Propagation Based Language Model Smoothing %@Rui Yan , Ian E.H. Yen , Cheng-Te Li , Shiqi Zhao , Xiaohua Hu %t2015 %cwww %f/www/www-2015-8185.pdf %*A Game Theoretic Model for the Formation of Navigable Small-World Networks %@Zhi Yang , Wei Chen %t2015 %cwww %f/www/www-2015-8186.pdf %*A Scalable Asynchronous Distributed Algorithm for Topic Modeling %@Hsiang-Fu Yu , Cho-Jui Hsieh , Hyokun Yun , S.V.N. Vishwanathan , Inderjit S. Dhillon %t2015 %cwww %f/www/www-2015-8187.pdf %*Lightlda: Big Topic Models on Modest Computer Clusters %@Jinhui Yuan , Fei Gao , Qirong Ho , Wei Dai , Jinliang Wei , Xun Zheng , Eric P. Xing , Tie-Yan Liu , Wei-Ying Ma %t2015 %cwww %f/www/www-2015-8188.pdf %*A Novelty-Seeking based Dining Recommender System %@Fuzheng Zhang , Kai Zheng , Nicholas Jing Yuan , Xing Xie , Enhong Chen , Xiaofang Zhou %t2015 %cwww %f/www/www-2015-8189.pdf %*Daily-Aware Personalized Recommendation based on Feature-Level Time Series Analysis %@Yongfeng Zhang , Min Zhang , Yi Zhang , Guokun Lai , Yiqun Liu , Honghui Zhang , Shaoping Ma %t2015 %cwww %f/www/www-2015-8190.pdf %*Automatic Detection of Information Leakage Vulnerabilities in Browser Extensions %@Rui Zhao , Chuan Yue , Qing Yi %t2015 %cwww %f/www/www-2015-8191.pdf %*Enquiring Minds: Early Detection of Rumors in Social Media From Enquiry Posts %@Zhe Zhao , Paul Resnick , Qiaozhu Mei %t2015 %cwww %f/www/www-2015-8192.pdf %*Improving User Topic Interest Profiles By Behavior Factorization %@Zhe Zhao , Zhiyuan Cheng , Lichan Hong , Ed H. Chi %t2015 %cwww %f/www/www-2015-8193.pdf %*Predicting Pinterest: Automating a Distributed Human Computation %@Changtao Zhong , Dmytro Karamshuk , Nishanth Sastry %t2015 %cwww %f/www/www-2015-8194.pdf