Table of Contents

• Information-theoretic lower bounds on the oracle complexity of convex optimizationAlekh Agarwal, Peter L. Bartlett, Pradeep D. Ravikumar, Martin J. Wainwright. 1-9 [doi]
• Streaming k-means approximationNir Ailon, Ragesh Jaiswal, Claire Monteleoni. 10-18 [doi]
• Complexity of Decentralized Control: Special CasesMartin Allen, Shlomo Zilberstein. 19-27 [doi]
• Learning from Multiple Partially Observed Views - an Application to Multilingual Text CategorizationMassih-Reza Amini, Nicolas Usunier, Cyril Goutte. 28-36 [doi]
• Constructing Topological Maps using Markov Random Fields and Loop-Closure DetectionRoy Anati, Kostas Daniilidis. 37-45 [doi]
• Data-driven calibration of linear estimators with minimal penaltiesSylvain Arlot, Francis R. Bach. 46-54 [doi]
• On Learning RotationsRaman Arora. 55-63 [doi]
• Polynomial Semantic IndexingBing Bai, Jason Weston, David Grangier, Ronan Collobert, Kunihiko Sadamasa, Yanjun Qi, Corinna Cortes, Mehryar Mohri. 64-72 [doi]
• Nonparametric Bayesian Models for Unsupervised Event Coreference ResolutionCosmin Adrian Bejan, Matthew Titsworth, Andrew Hickl, Sanda M. Harabagiu. 73-81 [doi]
• Group Sparse CodingSamy Bengio, Fernando C. N. Pereira, Yoram Singer, Dennis Strelow. 82-89 [doi]
• Neurometric function analysis of population codesPhilipp Berens, Sebastian Gerwinn, Alexander S. Ecker, Matthias Bethge. 90-98 [doi]
• Slow, Decorrelated Features for Pretraining Complex Cell-like NetworksJames Bergstra, Yoshua Bengio. 99-107 [doi]
• No evidence for active sparsification in the visual cortexPietro Berkes, Ben White, József Fiser. 108-116 [doi]
• Manifold Regularization for SIR with Rate Root-n ConvergenceWei Bian, Dacheng Tao. 117-125 [doi]
• Augmenting Feature-driven fMRI Analyses: Semi-supervised learning and resting state activityMatthew B. Blaschko, Jacquelyn A. Shelton, Andreas Bartels. 126-134 [doi]
• Efficient Match Kernel between Sets of Features for Visual RecognitionLiefeng Bo, Cristian Sminchisescu. 135-143 [doi]
• Randomized Pruning: Efficiently Calculating Expectations in Large Dynamic ProgramsAlexandre Bouchard-Côté, Slav Petrov, Dan Klein. 144-152 [doi]
• Unsupervised Feature Selection for the $k$-means Clustering ProblemChristos Boutsidis, Michael W. Mahoney, Petros Drineas. 153-161 [doi]
• On Invariance in Hierarchical ModelsJake V. Bouvrie, Lorenzo Rosasco, Tomaso Poggio. 162-170 [doi]
• Nash Equilibria of Static Prediction GamesMichael Brückner, Tobias Scheffer. 171-179 [doi]
• Optimal context separation of spiking haptic signals by second-order somatosensory neuronsRomain Brasselet, Roland S. Johansson, Angelo Arleo. 180-188 [doi]
• Manifold Embeddings for Model-Based Reinforcement Learning under Partial ObservabilityKeith Bush, Joelle Pineau. 189-197 [doi]
• Learning to Explore and Exploit in POMDPsChenghui Cai, Xuejun Liao, Lawrence Carin. 198-206 [doi]
• Speaker Comparison with Inner Product Discriminant FunctionsWilliam M. Campbell, Zahi N. Karam, Douglas E. Sturim. 207-215 [doi]
• A Stochastic approximation method for inference in probabilistic graphical modelsPeter Carbonetto, Matthew King, Firas Hamze. 216-224 [doi]
• Bayesian Nonparametric Models on Decomposable GraphsFrancois Caron, Arnaud Doucet. 225-233 [doi]
• Adaptive Design Optimization in Experiments with PeopleDaniel R. Cavagnaro, Mark A. Pitt, Jay I. Myung. 234-242 [doi]
• Efficient Bregman Range SearchLawrence Cayton. 243-251 [doi]
• Discriminative Network Models of SchizophreniaGuillermo A. Cecchi, Irina Rish, Benjamin Thyreau, Bertrand Thirion, Marion Plaze, Marie-Laure Paillere-Martinot, Catherine Martelli, Jean-Luc Martinot, Jean-Baptiste Poline. 252-260 [doi]
• Learning with Compressible PriorsVolkan Cevher. 261-269 [doi]
• Exploring Functional Connectivities of the Human Brain using Multivariate Information AnalysisBarry Chai, Dirk B. Walther, Diane M. Beck, Fei-Fei Li. 270-278 [doi]
• Generalization Errors and Learning Curves for Regression with Multi-task Gaussian ProcessesKian Ming Adam Chai. 279-287 [doi]
• Reading Tea Leaves: How Humans Interpret Topic ModelsJonathan Chang, Jordan L. Boyd-Graber, Sean Gerrish, Chong Wang, David M. Blei. 288-296 [doi]
• A Parameter-free Hedging AlgorithmKamalika Chaudhuri, Yoav Freund, Daniel Hsu. 297-305 [doi]
• An Online Algorithm for Large Scale Image Similarity LearningGal Chechik, Uri Shalit, Varun Sharma, Samy Bengio. 306-314 [doi]
• Ranking Measures and Loss Functions in Learning to RankWei Chen, Tie-Yan Liu, Yanyan Lan, Zhiming Ma, Hang Li. 315-323 [doi]
• Factor Modeling for Advertisement TargetingYe Chen, Michael Kapralov, Dmitry Pavlov, John Canny. 324-332 [doi]
• The Ordered Residual Kernel for Robust Motion Subspace ClusteringTat-Jun Chin, Hanzi Wang, David Suter. 333-341 [doi]
• Kernel Methods for Deep LearningYoungmin Cho, Lawrence K. Saul. 342-350 [doi]
• Approximating MAP by Compensating for Structural RelaxationsArthur Choi, Adnan Darwiche. 351-359 [doi]
• AUC optimization and the two-sample problemStéphan Clémençon, Nicolas Vayatis, Marine Depecker. 360-368 [doi]
• Statistical Models of Linear and Nonlinear Contextual Interactions in Early Visual ProcessingRuben Coen Cagli, Peter Dayan, Odelia Schwartz. 369-377 [doi]
• fMRI-Based Inter-Subject Cortical Alignment Using Functional ConnectivityBryan R. Conroy, Ben Singer, James V. Haxby, Peter J. Ramadge. 378-386 [doi]
• Sensitivity analysis in HMMs with application to likelihood maximizationPierre-Arnaud Coquelin, Romain Deguest, Rémi Munos. 387-395 [doi]
• Learning Non-Linear Combinations of KernelsCorinna Cortes, Mehryar Mohri, Afshin Rostamizadeh. 396-404 [doi]
• An Infinite Factor Model Hierarchy Via a Noisy-Or MechanismAaron C. Courville, Douglas Eck, Yoshua Bengio. 405-413 [doi]
• Adaptive Regularization of Weight VectorsKoby Crammer, Alex Kulesza, Mark Dredze. 414-422 [doi]
• Learning transport operators for image manifoldsBenjamin J. Culpepper, Bruno A. Olshausen. 423-431 [doi]
• White Functionals for Anomaly Detection in Dynamical SystemsMarco Cuturi, Jean-Philippe Vert, Alexandre d'Aspremont. 432-440 [doi]
• $L_1$-Penalized Robust Estimation for a Class of Inverse Problems Arising in Multiview GeometryArnak S. Dalalyan, Renaud Keriven. 441-449 [doi]
• Distribution-Calibrated Hierarchical ClassificationOfer Dekel. 450-458 [doi]
• A Smoothed Approximate Linear ProgramVijay V. Desai, Vivek F. Farias, Ciamac Cyrus Moallemi. 459-467 [doi]
• Localizing Bugs in Program Executions with Graphical ModelsLaura Dietz, Valentin Dallmeier, Andreas Zeller, Tobias Scheffer. 468-476 [doi]
• The Infinite Partially Observable Markov Decision ProcessFinale Doshi-Velez. 477-485 [doi]
• A Bayesian Model for Simultaneous Image Clustering, Annotation and Object SegmentationLan Du, Lu Ren, David B. Dunson, Lawrence Carin. 486-494 [doi]
• Efficient Learning using Forward-Backward SplittingJohn C. Duchi, Yoram Singer. 495-503 [doi]
• A Data-Driven Approach to Modeling ChoiceVivek F. Farias, Srikanth Jagabathula, Devavrat Shah. 504-512 [doi]
• Subject independent EEG-based BCI decodingSiamac Fazli, Cristian Grozea, Márton Danóczy, Benjamin Blankertz, Florin Popescu, Klaus-Robert Müller. 513-521 [doi]
• Semi-Supervised Learning in Gigantic Image CollectionsRob Fergus, Yair Weiss, Antonio Torralba. 522-530 [doi]
• Evaluating multi-class learning strategies in a generative hierarchical framework for object detectionSanja Fidler, Marko Boben, Ales Leonardis. 531-539 [doi]
• Orthogonal Matching Pursuit From Noisy Random Measurements: A New AnalysisAlyson K. Fletcher, Sundeep Rangan. 540-548 [doi]
• Sharing Features among Dynamical Systems with Beta ProcessesEmily B. Fox, Erik B. Sudderth, Michael I. Jordan, Alan S. Willsky. 549-557 [doi]
• An Additive Latent Feature Model for Transparent Object RecognitionMario Fritz, Michael J. Black, Gary R. Bradski, Sergey Karayev, Trevor Darrell. 558-566 [doi]
• An LP View of the M-best MAP problemMenachem Fromer, Amir Globerson. 567-575 [doi]
• Estimating image bases for visual image reconstruction from human brain activityYusuke Fujiwara, Yoichi Miyawaki, Yukiyasu Kamitani. 576-584 [doi]
• Graph-based Consensus Maximization among Multiple Supervised and Unsupervised ModelsJing Gao, Feng Liang, Wei Fan, Yizhou Sun, Jiawei Han. 585-593 [doi]
• Lattice RegressionEric K. Garcia, Maya R. Gupta. 594-602 [doi]
• From PAC-Bayes Bounds to KL RegularizationPascal Germain, Alexandre Lacasse, François Laviolette, Mario Marchand, Sara Shanian. 603-610 [doi]
• Perceptual Multistability as Markov Chain Monte Carlo InferenceSamuel Gershman, Ed Vul, Joshua B. Tenenbaum. 611-619 [doi]
• A joint maximum-entropy model for binary neural population patterns and continuous signalsSebastian Gerwinn, Philipp Berens, Matthias Bethge. 620-628 [doi]
• A Biologically Plausible Model for Rapid Natural Scene IdentificationSennay Ghebreab, H. Steven Scholte, Victor A. F. Lamme, Arnold W. M. Smeulders. 629-637 [doi]
• A Gaussian Tree Approximation for Integer Least-SquaresJacob Goldberger, Amir Leshem. 638-645 [doi]
• Measuring Invariances in Deep NetworksIan J. Goodfellow, Quoc V. Le, Andrew M. Saxe, Honglak Lee, Andrew Y. Ng. 646-654 [doi]
• Region-based Segmentation and Object DetectionStephen Gould, Tianshi Gao, Daphne Koller. 655-663 [doi]
• Posterior vs Parameter Sparsity in Latent Variable ModelsJoão Graça, Kuzman Ganchev, Ben Taskar, Fernando C. N. Pereira. 664-672 [doi]
• A Fast, Consistent Kernel Two-Sample TestArthur Gretton, Kenji Fukumizu, Zaïd Harchaoui, Bharath K. Sriperumbudur. 673-681 [doi]
• Non-stationary continuous dynamic Bayesian networksMarco Grzegorczyk, Dirk Husmeier. 682-690 [doi]
• Label Selection on GraphsAndrew Guillory, Jeff A. Bilmes. 691-699 [doi]
• Beyond Convexity: Online Submodular MinimizationElad Hazan, Satyen Kale. 700-708 [doi]
• On Stochastic and Worst-case Models for InvestingElad Hazan, Satyen Kale. 709-717 [doi]
• Robust Nonparametric Regression with Metric-Space Valued OutputMatthias Hein. 718-726 [doi]
• Hierarchical Learning of Dimensional Biases in Human CategorizationKatherine A. Heller, Adam Sanborn, Nick Chater. 727-735 [doi]
• Bayesian Sparse Factor Models and DAGs Inference and ComparisonRicardo Henao, Ole Winther. 736-744 [doi]
• Sparse and Locally Constant Gaussian Graphical ModelsJean Honorio, Luis E. Ortiz, Dimitris Samaras, Nikos Paragios, Rita Z. Goldstein. 745-753 [doi]
• Differential Use of Implicit Negative Evidence in Generative and Discriminative Language LearningAnne S. Hsu, Thomas L. Griffiths. 754-762 [doi]
• Periodic Step Size Adaptation for Single Pass On-line LearningChun-Nan Hsu, Yu-Ming Chang, Han-Shen Huang, Yuh-Jye Lee. 763-771 [doi]
• Multi-Label Prediction via Compressed SensingDaniel Hsu, Sham Kakade, John Langford, Tong Zhang 0001. 772-780 [doi]
• Accelerated Gradient Methods for Stochastic Optimization and Online LearningChonghai Hu, James T. Kwok, Weike Pan. 781-789 [doi]
• Reconstruction of Sparse Circuits Using Multi-neuronal Excitation (RESCUME)Tao Hu, Anthony M. Leonardo, Dmitri B. Chklovskii. 790-798 [doi]
• Riffled Independence for Ranked DataJonathan Huang, Carlos Guestrin. 799-807 [doi]
• Learning Brain Connectivity of Alzheimer's Disease from Neuroimaging DataShuai Huang, Jing Li, Liang Sun, Jun Liu, Teresa Wu, Kewei Chen, Adam Fleisher, Eric Reiman, Jieping Ye. 808-816 [doi]
• Discrete MDL Predicts in Total VariationMarcus Hutter. 817-825 [doi]
• Particle-based Variational Inference for Continuous SystemsAlexander T. Ihler, Andrew J. Frank, Padhraic Smyth. 826-834 [doi]
• Modeling Social Annotation Data with Content Relevance using a Topic ModelTomoharu Iwata, Takeshi Yamada, Naonori Ueda. 835-843 [doi]
• On the Algorithmics and Applications of a Mixed-norm based Kernel Learning FormulationJagarlapudi Saketha Nath, G. Dinesh, Sankaran Raman, Chiranjib Bhattacharyya, Aharon Ben-Tal, K. R. Ramakrishnan. 844-852 [doi]
• Bayesian Belief PolarizationAlan Jern, Kai-min Chang, Charles Kemp. 853-861 [doi]
• Regularized Distance Metric Learning: Theory and AlgorithmRong Jin, Shijun Wang, Yang Zhou. 862-870 [doi]
• Local Rules for Global MAP: When Do They Work ?Kyomin Jung, Pushmeet Kohli, Devavrat Shah. 871-879 [doi]
• Potential-Based Agnostic BoostingAdam Kalai, Varun Kanade. 880-888 [doi]
• Directed RegressionYi-Hao Kao, Benjamin Van Roy, Xiang Yan. 889-897 [doi]
• Breaking Boundaries Between Induction Time and Diagnosis Time Active Information AcquisitionAshish Kapoor, Eric Horvitz. 898-906 [doi]
• Multiple Incremental Decremental Learning of Support Vector MachinesMasayuki Karasuyama, Ichiro Takeuchi. 907-915 [doi]
• Submodularity Cuts and ApplicationsYoshinobu Kawahara, Kiyohito Nagano, Koji Tsuda, Jeff A. Bilmes. 916-924 [doi]
• Individuation, Identification and Object DiscoveryCharles Kemp, Alan Jern, Fei Xu. 925-933 [doi]
• Abstraction and Relational learningCharles Kemp, Alan Jern. 934-942 [doi]
• Quantification and the language of thoughtCharles Kemp. 943-951 [doi]
• Matrix Completion from Noisy EntriesRaghunandan H. Keshavan, Andrea Montanari, Sewoong Oh. 952-960 [doi]
• Unsupervised Detection of Regions of Interest Using Iterative Link AnalysisGunhee Kim, Antonio Torralba. 961-969 [doi]
• Clustering sequence sets for motif discoveryJong Kyoung Kim, Seungjin Choi. 970-978 [doi]
• Semi-supervised Regression using Hessian energy with an application to semi-supervised dimensionality reductionKwang In Kim, Florian Steinke, Matthias Hein. 979-987 [doi]
• Replacing supervised classification learning by Slow Feature Analysis in spiking neural networksStefan Klampfl, Wolfgang Maass. 988-996 [doi]
• Efficient and Accurate Lp-Norm Multiple Kernel LearningMarius Kloft, Ulf Brefeld, Sören Sonnenburg, Pavel Laskov, Klaus-Robert Müller, Alexander Zien. 997-1005 [doi]
• Sparsistent Learning of Varying-coefficient Models with Structural ChangesMladen Kolar, Le Song, Eric P. Xing. 1006-1014 [doi]
• Skill Discovery in Continuous Reinforcement Learning Domains using Skill ChainingGeorge Konidaris, Andrew G. Barto. 1015-1023 [doi]
• Fast, smooth and adaptive regression in metric spacesSamory Kpotufe. 1024-1032 [doi]
• Fast Image Deconvolution using Hyper-Laplacian PriorsDilip Krishnan, Rob Fergus. 1033-1041 [doi]
• Learning to Hash with Binary Reconstructive EmbeddingsBrian Kulis, Trevor Darrell. 1042-1050 [doi]
• Learning a Small Mixture of TreesM. Pawan Kumar, Daphne Koller. 1051-1059 [doi]
• Ensemble Nystrom MethodSanjiv Kumar, Mehryar Mohri, Ameet Talwalkar. 1060-1068 [doi]
• Occlusive Components AnalysisJörg Lücke, Richard Turner, Maneesh Sahani, Marc Henniges. 1069-1077 [doi]
• Monte Carlo Sampling for Regret Minimization in Extensive GamesMarc Lanctot, Kevin Waugh, Martin Zinkevich, Michael H. Bowling. 1078-1086 [doi]
• Inter-domain Gaussian Processes for Sparse Inference using Inducing FeaturesMiguel Lázaro-Gredilla, Aníbal R. Figueiras-Vidal. 1087-1095 [doi]
• Unsupervised feature learning for audio classification using convolutional deep belief networksHonglak Lee, Peter T. Pham, Yan Largman, Andrew Y. Ng. 1096-1104 [doi]
• Functional network reorganization in motor cortex can be explained by reward-modulated Hebbian learningRobert A. Legenstein, Steven M. Chase, Andrew B. Schwartz, Wolfgang Maass. 1105-1113 [doi]
• An Integer Projected Fixed Point Method for Graph Matching and MAP InferenceMarius Leordeanu, Martial Hebert, Rahul Sukthankar. 1114-1122 [doi]
• Probabilistic Relational PCAWu-Jun Li, Dit-Yan Yeung, Zhihua Zhang. 1123-1131 [doi]
• Asymptotically Optimal Regularization in Smooth Parametric ModelsPercy Liang, Francis R. Bach, Guillaume Bouchard, Michael I. Jordan. 1132-1140 [doi]
• Nonparametric Greedy Algorithms for the Sparse Learning ProblemHan Liu, Xi Chen. 1141-1149 [doi]
• Grouped Orthogonal Matching Pursuit for Variable Selection and PredictionAurelie C. Lozano, Grzegorz Swirszcz, Naoki Abe. 1150-1158 [doi]
• Modeling the spacing effect in sequential category learningHongjing Lu, Matthew Weiden, Alan L. Yuille. 1159-1167 [doi]
• Who's Doing What: Joint Modeling of Names and Verbs for Simultaneous Face and Pose AnnotationJie Luo, Barbara Caputo, Vittorio Ferrari. 1168-1176 [doi]
• Variational Gaussian-process factor analysis for modeling spatio-temporal dataJaakko Luttinen, Alexander Ilin. 1177-1185 [doi]
• Solving Stochastic GamesLiam Mac Dermed, Charles L. Isbell. 1186-1194 [doi]
• Bayesian estimation of orientation preference mapsJakob H. Macke, Sebastian Gerwinn, Leonard E. White, Matthias Kaschube, Matthias Bethge. 1195-1203 [doi]
• Convergent Temporal-Difference Learning with Arbitrary Smooth Function ApproximationHamid Reza Maei, Csaba Szepesvári, Shalabh Bhatnagar, Doina Precup, David Silver, Richard S. Sutton. 1204-1212 [doi]
• Compressed Least-Squares RegressionOdalric-Ambrym Maillard, Rémi Munos. 1213-1221 [doi]
• Beyond Categories: The Visual Memex Model for Reasoning About Object RelationshipsTomasz Malisiewicz, Alexei A. Efros. 1222-1230 [doi]
• Efficient Large-Scale Distributed Training of Conditional Maximum Entropy ModelsGideon Mann, Ryan T. McDonald, Mehryar Mohri, Nathan Silberman, Dan Walker. 1231-1239 [doi]
• Toward Provably Correct Feature Selection in Arbitrary DomainsDimitris Margaritis. 1240-1248 [doi]
• FACTORIE: Probabilistic Programming via Imperatively Defined Factor GraphsAndrew McCallum, Karl Schultz, Sameer Singh. 1249-1257 [doi]
• Matrix Completion from Power-Law Distributed SamplesRaghu Meka, Prateek Jain 0002, Inderjit S. Dhillon. 1258-1266 [doi]
• Extending Phase Mechanism to Differential Motion Opponency for Motion Pop-outYicong Meng, Bertram E. Shi. 1267-1275 [doi]
• Nonparametric Latent Feature Models for Link PredictionKurt T. Miller, Thomas L. Griffiths, Michael I. Jordan. 1276-1284 [doi]
• Accelerating Bayesian Structural Inference for Non-Decomposable Gaussian Graphical ModelsBaback Moghaddam, Benjamin M. Marlin, Mohammad Emtiyaz Khan, Kevin P. Murphy. 1285-1293 [doi]
• Large Scale Nonparametric Bayesian Inference: Data Parallelisation in the Indian Buffet ProcessFinale Doshi-Velez, David A. Knowles, Shakir Mohamed, Zoubin Ghahramani. 1294-1302 [doi]
• Which graphical models are difficult to learn?Andrea Montanari, Jose Ayres Pereira. 1303-1311 [doi]
• A Generalized Natural Actor-Critic AlgorithmTetsuro Morimura, Eiji Uchibe, Junichiro Yoshimoto, Kenji Doya. 1312-1320 [doi]
• Predicting the Optimal Spacing of Study: A Multiscale Context Model of MemoryMichael Mozer, Harold Pashler, Nicholas Cepeda, Robert A. Lindsey, Ed Vul. 1321-1329 [doi]
• Statistical Analysis of Semi-Supervised Learning: The Limit of Infinite Unlabelled DataBoaz Nadler, Nathan Srebro, Xueyuan Zhou. 1330-1338 [doi]
• 3D Object Recognition with Deep Belief NetsVinod Nair, Geoffrey E. Hinton. 1339-1347 [doi]
• A unified framework for high-dimensional analysis of $M$-estimators with decomposable regularizersSahand Negahban, Pradeep D. Ravikumar, Martin J. Wainwright, Bin Yu. 1348-1356 [doi]
• STDP enables spiking neurons to detect hidden causes of their inputsBernhard Nessler, Michael Pfeiffer, Wolfgang Maass. 1357-1365 [doi]
• Noisy Generalized Binary SearchRobert D. Nowak. 1366-1374 [doi]
• Submanifold density estimationArkadas Ozakin, Alexander G. Gray. 1375-1382 [doi]
• Correlation Coefficients are Insufficient for Analyzing Spike Count DependenciesArno Onken, Steffen Grünewälder, Klaus Obermayer. 1383-1391 [doi]
• Construction of Nonparametric Bayesian Models from Parametric Bayes EquationsPeter Orbanz. 1392-1400 [doi]
• Learning from Neighboring Strokes: Combining Appearance and Context for Multi-Domain Sketch RecognitionTom Y. Ouyang, Randall Davis. 1401-1409 [doi]
• Zero-shot Learning with Semantic Output CodesMark Palatucci, Dean Pomerleau, Geoffrey E. Hinton, Tom M. Mitchell. 1410-1418 [doi]
• Conditional Neural FieldsJian Peng 0001, Liefeng Bo, Jinbo Xu. 1419-1427 [doi]
• Free energy score spaceAlessandro Perina, Marco Cristani, Umberto Castellani, Vittorio Murino, Nebojsa Jojic. 1428-1436 [doi]
• Maximum likelihood trajectories for continuous-time Markov chainsTheodore J. Perkins. 1437-1445 [doi]
• Robust Value Function Approximation Using Bilinear ProgrammingMarek Petrik, Shlomo Zilberstein. 1446-1454 [doi]
• Exponential Family Graph Matching and RankingJames Petterson, Tibério S. Caetano, Julian John McAuley, Jin Yu. 1455-1463 [doi]
• Know Thy Neighbour: A Normative Theory of Synaptic DepressionJean-Pascal Pfister, Peter Dayan, Máté Lengyel. 1464-1472 [doi]
• Time-rescaling methods for the estimation and assessment of non-Poisson neural encoding modelsJonathan W. Pillow. 1473-1481 [doi]
• Bilinear classifiers for visual recognitionHamed Pirsiavash, Deva Ramanan, Charless Fowlkes. 1482-1490 [doi]
• Convex Relaxation of Mixture Regression with Efficient AlgorithmsNovi Quadrianto, Tibério S. Caetano, John Lim, Dale Schuurmans. 1491-1499 [doi]
• Distribution Matching for TransductionNovi Quadrianto, James Petterson, Alex J. Smola. 1500-1508 [doi]
• Locality-sensitive binary codes from shift-invariant kernelsMaxim Raginsky, Svetlana Lazebnik. 1509-1517 [doi]
• Multi-Label Prediction via Sparse Infinite CCAPiyush Rai, Hal Daumé III. 1518-1526 [doi]
• Linear-time Algorithms for Pairwise Statistical ProblemsParikshit Ram, Dongryeol Lee, William B. March, Alexander G. Gray. 1527-1535 [doi]
• Rank-Approximate Nearest Neighbor Search: Retaining Meaning and Speed in High DimensionsParikshit Ram, Dongryeol Lee, Hua Ouyang, Alexander G. Gray. 1536-1544 [doi]
• Asymptotic Analysis of MAP Estimation via the Replica Method and Compressed SensingSundeep Rangan, Alyson K. Fletcher, Vivek K. Goyal. 1545-1553 [doi]
• Spatial Normalized Gamma ProcessesVinayak Rao, Yee Whye Teh. 1554-1562 [doi]
• Lower bounds on minimax rates for nonparametric regression with additive sparsity and smoothnessGarvesh Raskutti, Martin J. Wainwright, Bin Yu. 1563-1570 [doi]
• A Game-Theoretic Approach to Hypergraph ClusteringSamuel Rota Bulò, Marcello Pelillo. 1571-1579 [doi]
• Segmenting Scenes by Matching Image CompositesBryan C. Russell, Alexei A. Efros, Josef Sivic, Bill Freeman, Andrew Zisserman. 1580-1588 [doi]
• Filtering Abstract Senses From Image Search ResultsKate Saenko, Trevor Darrell. 1589-1597 [doi]
• Learning in Markov Random Fields using Tempered TransitionsRuslan Salakhutdinov. 1598-1606 [doi]
• Replicated Softmax: an Undirected Topic ModelRuslan Salakhutdinov, Geoffrey E. Hinton. 1607-1614 [doi]
• Learning models of object structureJoseph Schlecht, Kobus Barnard. 1615-1623 [doi]
• Linearly constrained Bayesian matrix factorization for blind source separationMikkel N. Schmidt. 1624-1632 [doi]
• Speeding up Magnetic Resonance Image Acquisition by Bayesian Multi-Slice Adaptive Compressed SensingMatthias W. Seeger. 1633-1641 [doi]
• Improving Existing Fault Recovery PoliciesGuy Shani, Christopher Meek. 1642-1650 [doi]
• Positive Semidefinite Metric Learning with BoostingChunhua Shen, Junae Kim, Lei Wang 0001, Anton van den Hengel. 1651-1659 [doi]
• Fast subtree kernels on graphsNino Shervashidze, Karsten M. Borgwardt. 1660-1668 [doi]
• Neural Implementation of Hierarchical Bayesian Inference by Importance SamplingLei Shi, Thomas L. Griffiths. 1669-1677 [doi]
• Learning Label Embeddings for Nearest-Neighbor Multi-class Classification with an Application to Speech RecognitionNatasha Singh-Miller, Michael Collins. 1678-1686 [doi]
• Semi-supervised Learning using Sparse Eigenfunction BasesKaushik Sinha, Mikhail Belkin. 1687-1695 [doi]
• Hierarchical Modeling of Local Image Features through $L_p$-Nested Symmetric DistributionsFabian H. Sinz, Eero P. Simoncelli, Matthias Bethge. 1696-1704 [doi]
• A Sparse Non-Parametric Approach for Single Channel Separation of Known SoundsParis Smaragdis, Madhusudana V. S. Shashanka, Bhiksha Raj. 1705-1713 [doi]
• A Bayesian Analysis of Dynamics in Free RecallRichard Socher, Samuel Gershman, Adler J. Perotte, Per B. Sederberg, David M. Blei, Kenneth A. Norman. 1714-1722 [doi]
• Kernels and learning curves for Gaussian process regression on random graphsPeter Sollich, Matthew Urry, Camille Coti. 1723-1731 [doi]
• Time-Varying Dynamic Bayesian NetworksLe Song, Mladen Kolar, Eric P. Xing. 1732-1740 [doi]
• Code-specific policy gradient rules for spiking neuronsHenning Sprekeler, Guillaume Hennequin, Wulfram Gerstner. 1741-1749 [doi]
• Kernel Choice and Classifiability for RKHS Embeddings of Probability DistributionsBharath K. Sriperumbudur, Kenji Fukumizu, Arthur Gretton, Gert R. G. Lanckriet, Bernhard Schölkopf. 1750-1758 [doi]
• On the Convergence of the Concave-Convex ProcedureBharath K. Sriperumbudur, Gert R. G. Lanckriet. 1759-1767 [doi]
• Fast Learning from Non-i.i.d. ObservationsIngo Steinwart, Andreas Christmann. 1768-1776 [doi]
• Structural inference affects depth perception in the context of potential occlusionIan H. Stevenson, Konrad Koerding. 1777-1784 [doi]
• The Wisdom of Crowds in the Recollection of Order InformationMark Steyvers, Michael D. Lee, Brent Miller, Pernille Hemmer. 1785-1793 [doi]
• Online Learning of AssignmentsMatthew J. Streeter, Daniel Golovin, Andreas Krause. 1794-1802 [doi]
• Entropic Graph Regularization in Non-Parametric Semi-Supervised ClassificationAmarnag Subramanya, Jeff A. Bilmes. 1803-1811 [doi]
• Efficient Recovery of Jointly Sparse VectorsLiang Sun, Jun Liu, Jianhui Chen, Jieping Ye. 1812-1820 [doi]
• Modelling Relational Data using Bayesian Clustered Tensor FactorizationIlya Sutskever, Ruslan Salakhutdinov, Joshua B. Tenenbaum. 1821-1828 [doi]
• Adapting to the Shifting Intent of Search QueriesUmar Syed, Aleksandrs Slivkins, Nina Mishra. 1829-1837 [doi]
• Indian Buffet Processes with Power-law BehaviorYee Whye Teh, Dilan Görür. 1838-1846 [doi]
• Nonlinear directed acyclic structure learning with weakly additive noise modelsRobert E. Tillman, Arthur Gretton, Peter Spirtes. 1847-1855 [doi]
• Compositionality of optimal control lawsEmanuel Todorov. 1856-1864 [doi]
• Maximin affinity learning of image segmentationSrinivas C. Turaga, Kevin L. Briggman, Moritz Helmstaedter, Winfried Denk, H. Sebastian Seung. 1865-1873 [doi]
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