Table of Contents

• Structure Learning in Human Sequential Decision-MakingDaniel Acuña, Paul R. Schrater. 1-8 [doi]
• The Gaussian Process Density SamplerRyan Prescott Adams, Iain Murray, David J. C. MacKay. 9-16 [doi]
• Online Models for Content OptimizationDeepak Agarwal, Bee-Chung Chen, Pradheep Elango, Nitin Motgi, Seung-Taek Park, Raghu Ramakrishnan, Scott Roy, Joe Zachariah. 17-24 [doi]
• Reconciling Real Scores with Binary Comparisons: A New Logistic Based Model for RankingNir Ailon. 25-32 [doi]
• Mixed Membership Stochastic BlockmodelsEdoardo Airoldi, David M. Blei, Stephen E. Fienberg, Eric P. Xing. 33-40 [doi]
• Nonrigid Structure from Motion in Trajectory SpaceIjaz Akhter, Yaser Sheikh, Sohaib Khan, Takeo Kanade. 41-48 [doi]
• Probabilistic detection of short events, with application to critical care monitoringNorm Aleks, Stuart Russell, Michael G. Madden, Diane Morabito, Kristan Staudenmayer, Mitchell Cohen, Geoffrey T. Manley. 49-56 [doi]
• Sparse Convolved Gaussian Processes for Multi-output RegressionMauricio Alvarez, Neil D. Lawrence. 57-64 [doi]
• A Transductive Bound for the Voted Classifier with an Application to Semi-supervised LearningMassih-Reza Amini, François Laviolette, Nicolas Usunier. 65-72 [doi]
• Sparse probabilistic projectionsCédric Archambeau, Francis Bach. 73-80 [doi]
• Asynchronous Distributed Learning of Topic ModelsArthur Asuncion, Padhraic Smyth, Max Welling. 81-88 [doi]
• Near-optimal Regret Bounds for Reinforcement LearningPeter Auer, Thomas Jaksch, Ronald Ortner. 89-96 [doi]
• Analyzing human feature learning as nonparametric Bayesian inferenceJoseph Austerweil, Thomas L. Griffiths. 97-104 [doi]
• Exploring Large Feature Spaces with Hierarchical Multiple Kernel LearningFrancis Bach. 105-112 [doi]
• Differentiable Sparse CodingJ. Andrew Bagnell, David M. Bradley. 113-120 [doi]
• Measures of Clustering Quality: A Working Set of Axioms for ClusteringShai Ben-David, Margareta Ackerman. 121-128 [doi]
• Characterizing neural dependencies with copula modelsPietro Berkes, Frank Wood, Jonathan Pillow. 129-136 [doi]
• On Bootstrapping the ROC CurvePatrice Bertail, Stéphan Clémençon, Nicolas Vayatis. 137-144 [doi]
• Transfer Learning by Distribution Matching for Targeted AdvertisingSteffen Bickel, Christoph Sawade, Tobias Scheffer. 145-152 [doi]
• Learning Taxonomies by Dependence MaximizationMatthew B. Blaschko, Arthur Gretton. 153-160 [doi]
• Bayesian Synchronous Grammar InductionPhil Blunsom, Trevor Cohn, Miles Osborne. 161-168 [doi]
• Goal-directed decision making in prefrontal cortex: a computational frameworkMatthew Botvinick, James An. 169-176 [doi]
• Efficient Inference in Phylogenetic InDel TreesAlexandre Bouchard-Côté, Michael I. Jordan, Dan Klein. 177-184 [doi]
• Syntactic Topic ModelsJordan L. Boyd-Graber, David M. Blei. 185-192 [doi]
• A spatially varying two-sample recombinant coalescent, with applications to HIV escape responseAlexander Braunstein, Zhi Wei, Shane T. Jensen, Jon D. McAuliffe. 193-200 [doi]
• Online Optimization in X-Armed BanditsSébastien Bubeck, Rémi Munos, Gilles Stoltz, Csaba Szepesvári. 201-208 [doi]
• Learning Transformational Invariants from Natural MoviesCharles Cadieu, Bruno Olshausen. 209-216 [doi]
• Accelerating Bayesian Inference over Nonlinear Differential Equations with Gaussian ProcessesBen Calderhead, Mark Girolami, Neil D. Lawrence. 217-224 [doi]
• Covariance Estimation for High Dimensional Data Vectors Using the Sparse Matrix TransformGuangzhi Cao, Charles A. Bouman. 225-232 [doi]
• An interior-point stochastic approximation method and an L1-regularized delta rulePeter Carbonetto, Mark Schmidt, Nando de Freitas. 233-240 [doi]
• Human Active LearningRui M. Castro, Charles Kalish, Robert Nowak, Ruichen Qian, Timothy J. Rogers, Xiaojin Zhu. 241-248 [doi]
• Linear Classification and Selective Sampling Under Low Noise ConditionsGiovanni Cavallanti, Nicolò Cesa-Bianchi, Claudio Gentile. 249-256 [doi]
• Sparse Signal Recovery Using Markov Random FieldsVolkan Cevher, Marco F. Duarte, Chinmay Hegde, Richard G. Baraniuk. 257-264 [doi]
• Multi-task Gaussian Process Learning of Robot Inverse DynamicsKian Ming Adam Chai, Christopher K. I. Williams, Stefan Klanke, Sethu Vijayakumar. 265-272 [doi]
• Mortal Multi-Armed BanditsDeepayan Chakrabarti, Ravi Kumar, Filip Radlinski, Eli Upfal. 273-280 [doi]
• Tighter Bounds for Structured EstimationOlivier Chapelle, Chuong B. Do, Quoc V. Le, Alexander J. Smola, Choon Hui Teo. 281-288 [doi]
• Privacy-preserving logistic regressionKamalika Chaudhuri, Claire Monteleoni. 289-296 [doi]
• Using Bayesian Dynamical Systems for Motion Template LibrariesSilvia Chiappa, Jens Kober, Jan Peters. 297-304 [doi]
• Empirical performance maximization for linear rank statisticsStéphan Clémençon, Nicolas Vayatis. 305-312 [doi]
• Overlaying classifiers: a practical approach for optimal rankingStéphan Clémençon, Nicolas Vayatis. 313-320 [doi]
• Logistic Normal Priors for Unsupervised Probabilistic Grammar InductionShay B. Cohen, Kevin Gimpel, Noah A. Smith. 321-328 [doi]
• Estimating Robust Query Models with Convex OptimizationKevyn Collins-Thompson. 329-336 [doi]
• Particle Filter-based Policy Gradient in POMDPsPierre-Arnaud Coquelin, Romain Deguest, Rémi Munos. 337-344 [doi]
• Exact Convex Confidence-Weighted LearningKoby Crammer, Mark Dredze, Fernando Pereira. 345-352 [doi]
• Translated Learning: Transfer Learning across Different Feature SpacesWenyuan Dai, Yuqiang Chen, Gui-Rong Xue, Qiang Yang, Yong Yu. 353-360 [doi]
• Adapting to a Market Shock: Optimal Sequential Market-MakingSanmay Das, Malik Magdon-Ismail. 361-368 [doi]
• Load and Attentional BayesPeter Dayan. 369-376 [doi]
• From Online to Batch Learning with Cutoff-AveragingOfer Dekel. 377-384 [doi]
• Temporal Difference Based Actor Critic Learning - Convergence and Neural ImplementationDotan Di Castro, Dmitry Volkinshtein, Ron Meir. 385-392 [doi]
• Look Ma, No Hands: Analyzing the Monotonic Feature Abstraction for Text ClassificationDoug Downey, Oren Etzioni. 393-400 [doi]
• Generative and Discriminative Learning with Unknown Labeling BiasMiroslav Dudík, Steven J. Phillips. 401-408 [doi]
• A Convex Upper Bound on the Log-Partition Function for Binary DistributionsLaurent El Ghaoui, Assane Gueye. 409-416 [doi]
• Learning Bounded Treewidth Bayesian NetworksGal Elidan, Stephen Gould. 417-424 [doi]
• Interpreting the neural code with Formal Concept AnalysisDominik Endres, Peter Földiák. 425-432 [doi]
• ICA based on a Smooth Estimation of the Differential EntropyLev Faivishevsky, Jacob Goldberger. 433-440 [doi]
• Regularized Policy IterationAmir Massoud Farahmand, Mohammad Ghavamzadeh, Csaba Szepesvári, Shie Mannor. 441-448 [doi]
• Resolution Limits of Sparse Coding in High DimensionsAlyson K. Fletcher, Sundeep Rangan, Vivek K. Goyal. 449-456 [doi]
• Nonparametric Bayesian Learning of Switching Linear Dynamical SystemsEmily B. Fox, Erik B. Sudderth, Michael I. Jordan, Alan S. Willsky. 457-464 [doi]
• Predicting the Geometry of Metal Binding Sites from Protein SequencePaolo Frasconi, Andrea Passerini. 465-472 [doi]
• Characteristic Kernels on Groups and SemigroupsKenji Fukumizu, Bharath K. Sriperumbudur, Arthur Gretton, Bernhard Schölkopf. 473-480 [doi]
• Tracking Changing Stimuli in Continuous Attractor Neural NetworksC. C. Alan Fung, K. Y. Michael Wong, Si Wu. 481-488 [doi]
• An Homotopy Algorithm for the Lasso with Online ObservationsPierre Garrigues, Laurent El Ghaoui. 489-496 [doi]
• Dependent Dirichlet Process Spike SortingJan Gasthaus, Frank Wood, Dilan Görür, Yee Whye Teh. 497-504 [doi]
• Predictive Indexing for Fast SearchSharad Goel, John Langford, Alexander L. Strehl. 505-512 [doi]
• Self-organization using synaptic plasticityVicenç Gómez, Andreas Kaltenbrunner, Vicente López, Hilbert J. Kappen. 513-520 [doi]
• An Efficient Sequential Monte Carlo Algorithm for Coalescent ClusteringDilan Görür, Yee Whye Teh. 521-528 [doi]
• A Massively Parallel Digital Learning ProcessorHans Peter Graf, Srihari Cadambi, Igor Durdanovic, Venkata Jakkula, Murugan Sankaradass, Eric Cosatto, Srimat T. Chakradhar. 529-536 [doi]
• Support Vector Machines with a Reject OptionYves Grandvalet, Alain Rakotomamonjy, Joseph Keshet, Stéphane Canu. 537-544 [doi]
• Offline Handwriting Recognition with Multidimensional Recurrent Neural NetworksAlex Graves, Jürgen Schmidhuber. 545-552 [doi]
• Modeling human function learning with Gaussian processesThomas L. Griffiths, Chris Lucas, Joseph Williams, Michael L. Kalish. 553-560 [doi]
• Understanding Brain Connectivity Patterns during Motor Imagery for Brain-Computer InterfacingMoritz Grosse-Wentrup. 561-568 [doi]
• Supervised Exponential Family Principal Component Analysis via Convex OptimizationYuhong Guo. 569-576 [doi]
• A Shape Aware Model for semi-supervised Learning of Objects and its ContextAbhinav Gupta, Jianbo Shi, Larry S. Davis. 577-584 [doi]
• An improved estimator of Variance Explained in the presence of noiseRalf M. Haefner, Bruce G. Cumming. 585-592 [doi]
• Unifying the Sensory and Motor Components of Sensorimotor AdaptationAdrian Haith, Carl P. T. Jackson, R. Chris Miall, Sethu Vijayakumar. 593-600 [doi]
• Extended Grassmann Kernels for Subspace-Based LearningJihun Ham, Daniel D. Lee. 601-608 [doi]
• Kernel Change-point AnalysisZaïd Harchaoui, Francis Bach, Eric Moulines. 609-616 [doi]
• Estimating vector fields using sparse basis field expansionsStefan Haufe, Vadim V. Nikulin, Andreas Ziehe, Klaus-Robert Müller, Guido Nolte. 617-624 [doi]
• Learning Hybrid Models for Image Annotation with Partially Labeled DataXuming He, Richard S. Zemel. 625-632 [doi]
• Shape-Based Object Localization for Descriptive ClassificationGeremy Heitz, Gal Elidan, Benjamin Packer, Daphne Koller. 633-640 [doi]
• Cascaded Classification Models: Combining Models for Holistic Scene UnderstandingGeremy Heitz, Stephen Gould, Ashutosh Saxena, Daphne Koller. 641-648 [doi]
• Online Prediction on Large Diameter GraphsMark Herbster, Guy Lever, Massimiliano Pontil. 649-656 [doi]
• Fast Prediction on a TreeMark Herbster, Massimiliano Pontil, Sergio Rojas Galeano. 657-664 [doi]
• Effects of Stimulus Type and of Error-Correcting Code Design on BCI Speller PerformanceN. Jeremy Hill, Jason Farquhar, Suzanna Martens, Felix Bießmann, Bernhard Schölkopf. 665-672 [doi]
• QUIC-SVD: Fast SVD Using Cosine TreesMichael P. Holmes, Alexander G. Gray, Charles Lee Isbell Jr.. 673-680 [doi]
• Dynamic visual attention: searching for coding length incrementsXiaodi Hou, Liqing Zhang. 681-688 [doi]
• Nonlinear causal discovery with additive noise modelsPatrik O. Hoyer, Dominik Janzing, Joris M. Mooij, Jonas Peters, Bernhard Schölkopf. 689-696 [doi]
• Structured ranking learning using cumulative distribution networksJim C. Huang, Brendan J. Frey. 697-704 [doi]
• Spectral Clustering with Perturbed DataLing Huang, Donghui Yan, Michael I. Jordan, Nina Taft. 705-712 [doi]
• Bio-inspired Real Time Sensory Map Realignment in a Robotic Barn OwlJuan Huo, Zhijun Yang, Alan F. Murray. 713-720 [doi]
• Theory of matching pursuitZakria Hussain, John Shawe-Taylor. 721-728 [doi]
• Psychiatry: Insights into depression through normative decision-making modelsQuentin J. M. Huys, Joshua T. Vogelstein, Peter Dayan. 729-736 [doi]
• Continuously-adaptive discretization for message-passing algorithmsMichael Isard, John MacCormick, Kannan Achan. 737-744 [doi]
• Clustered Multi-Task Learning: A Convex FormulationLaurent Jacob, Francis Bach, Jean-Philippe Vert. 745-752 [doi]
• Inferring rankings under constrained sensingSrikanth Jagabathula, Devavrat Shah. 753-760 [doi]
• Online Metric Learning and Fast Similarity SearchPrateek Jain, Brian Kulis, Inderjit S. Dhillon, Kristen Grauman. 761-768 [doi]
• Natural Image Denoising with Convolutional NetworksViren Jain, H. Sebastian Seung. 769-776 [doi]
• Multi-label Multiple Kernel LearningShuiwang Ji, Liang Sun, Rong Jin, Jieping Ye. 777-784 [doi]
• Optimal Response Initiation: Why Recent Experience MattersMatt Jones, Michael C. Mozer, Sachiko Kinoshita. 785-792 [doi]
• On the Complexity of Linear Prediction: Risk Bounds, Margin Bounds, and RegularizationSham M. Kakade, Karthik Sridharan, Ambuj Tewari. 793-800 [doi]
• On the Generalization Ability of Online Strongly Convex Programming AlgorithmsSham M. Kakade, Ambuj Tewari. 801-808 [doi]
• Efficient Direct Density Ratio Estimation for Non-stationarity Adaptation and Outlier DetectionTakafumi Kanamori, Shohei Hido, Masashi Sugiyama. 809-816 [doi]
• Extracting State Transition Dynamics from Multiple Spike Trains with Correlated Poisson HMMKentaro Katahira, Jun Nishikawa, Kazuo Okanoya, Masato Okada. 817-824 [doi]
• An ideal observer model of infant object perceptionCharles Kemp, Fei Xu. 825-832 [doi]
• Performance analysis for L_2 kernel classificationJooSeuk Kim, Clayton Scott. 833-840 [doi]
• MCBoost: Multiple Classifier Boosting for Perceptual Co-clustering of Images and Visual FeaturesTae-Kyun Kim, Roberto Cipolla. 841-856 [doi]
• Policy Search for Motor Primitives in RoboticsJens Kober, Jan Peters. 849-856 [doi]
• On the asymptotic equivalence between differential Hebbian and temporal difference learning using a local third factorChristoph Kolodziejski, Bernd Porr, Minija Tamosiunaite, Florentin Wörgötter. 857-864 [doi]
• Clustering via LP-based StabilitiesNikos Komodakis, Nikos Paragios, Georgios Tziritas. 865-872 [doi]
• Counting Solution Clusters in Graph Coloring Problems Using Belief PropagationLukas Kroc, Ashish Sabharwal, Bart Selman. 873-880 [doi]
• Scalable Algorithms for String Kernels with Inexact MatchingPavel P. Kuksa, Pai-Hsi Huang, Vladimir Pavlovic. 881-888 [doi]
• Improved Moves for Truncated Convex ModelsM. Pawan Kumar, Philip H. S. Torr. 889-896 [doi]
• DiscLDA: Discriminative Learning for Dimensionality Reduction and ClassificationSimon Lacoste-Julien, Fei Sha, Michael I. Jordan. 897-904 [doi]
• Sparse Online Learning via Truncated GradientJohn Langford, Lihong Li, Tong Zhang. 905-912 [doi]
• Multiscale Random Fields with Application to Contour GroupingLongin Jan Latecki, ChengEn Lu, Marc Sobel, Xiang Bai. 913-920 [doi]
• Adaptive Template Matching with Shift-Invariant Semi-NMFJonathan Le Roux, Alain de Cheveigné, Lucas C. Parra. 921-928 [doi]
• Fast High-dimensional Kernel Summations Using the Monte Carlo Multipole MethodDongryeol Lee, Alexander G. Gray. 929-936 [doi]
• Modeling the effects of memory on human online sentence processing with particle filtersRoger P. Levy, Florencia Reali, Thomas L. Griffiths. 937-944 [doi]
• Designing neurophysiology experiments to optimally constrain receptive field models along parametric submanifoldsJeremy Lewi, Robert J. Butera, David M. Schneider, Sarah M. N. Woolley, Liam Paninski. 945-952 [doi]
• One sketch for all: Theory and Application of Conditional Random SamplingPing Li, Kenneth Ward Church, Trevor Hastie. 953-960 [doi]
• Dimensionality Reduction for Data in Multiple Feature RepresentationsYen-Yu Lin, Tyng-Luh Liu, Chiou-Shann Fuh. 961-968 [doi]
• Nonparametric regression and classification with joint sparsity constraintsHan Liu, John D. Lafferty, Larry A. Wasserman. 969-976 [doi]
• Adaptive Martingale BoostingPhilip M. Long, Rocco A. Servedio. 977-984 [doi]
• A rational model of preference learning and choice prediction by childrenChristopher G. Lucas, Thomas L. Griffiths, Fei Xu, Christine Fawcett. 985-992 [doi]
• A computational model of hippocampal function in trace conditioningElliot A. Ludvig, Richard S. Sutton, Eric Verbeek, E. James Kehoe. 993-1000 [doi]
• Stress, noradrenaline, and realistic prediction of mouse behaviour using reinforcement learningGediminas Luksys, Carmen Sandi, Wulfram Gerstner. 1001-1008 [doi]
• Reducing statistical dependencies in natural signals using radial GaussianizationSiwei Lyu, Eero P. Simoncelli. 1009-1016 [doi]
• Deflation Methods for Sparse PCALester Mackey. 1017-1024 [doi]
• Influence of graph construction on graph-based clustering measuresMarkus Maier, Ulrike von Luxburg, Matthias Hein. 1025-1032 [doi]
• Supervised Dictionary LearningJulien Mairal, Francis Bach, Jean Ponce, Guillermo Sapiro, Andrew Zisserman. 1033-1040 [doi]
• Domain Adaptation with Multiple SourcesYishay Mansour, Mehryar Mohri, Afshin Rostamizadeh. 1041-1048 [doi]
• On the Design of Loss Functions for Classification: theory, robustness to outliers, and SavageBoostHamed Masnadi-Shirazi, Nuno Vasconcelos. 1049-1056 [doi]
• Robust Near-Isometric Matching via Structured Learning of Graphical ModelsJulian John McAuley, Tibério S. Caetano, Alexander J. Smola. 1057-1064 [doi]
• MDPs with Non-Deterministic PoliciesMahdi Milani Fard, Joelle Pineau. 1065-1072 [doi]
• GatesTom Minka, John M. Winn. 1073-1080 [doi]
• A Scalable Hierarchical Distributed Language ModelAndriy Mnih, Geoffrey E. Hinton. 1081-1088 [doi]
• Bayesian Exponential Family PCAShakir Mohamed, Katherine A. Heller, Zoubin Ghahramani. 1089-1096 [doi]
• Rademacher Complexity Bounds for Non-I.I.D. ProcessesMehryar Mohri, Afshin Rostamizadeh. 1097-1104 [doi]
• Bounds on marginal probability distributionsJoris M. Mooij, Hilbert J. Kappen. 1105-1112 [doi]
• Automatic online tuning for fast Gaussian summationVlad I. Morariu, Balaji Vasan Srinivasan, Vikas C. Raykar, Ramani Duraiswami, Larry S. Davis. 1113-1120 [doi]
• Artificial Olfactory Brain for Mixture IdentificationMehmet K. Muezzinoglu, Alexander Vergara, Ramón Huerta, Thomas Nowotny, Nikolai Rulkov, Henry D. I. Abarbanel, Allen I. Selverston, Mikhail I. Rabinovich. 1121-1128 [doi]
• Relative Performance Guarantees for Approximate Inference in Latent Dirichlet AllocationIndraneel Mukherjee, David M. Blei. 1129-1136 [doi]
• Evaluating probabilities under high-dimensional latent variable modelsIain Murray, Ruslan Salakhutdinov. 1137-1144 [doi]
• Implicit Mixtures of Restricted Boltzmann MachinesVinod Nair, Geoffrey E. Hinton. 1145-1152 [doi]
• Characterizing response behavior in multisensory perception with conflicting cuesRama Natarajan, Iain Murray, Ladan Shams, Richard S. Zemel. 1153-1160 [doi]
• Phase transitions for high-dimensional joint support recoverySahand Negahban, Martin J. Wainwright. 1161-1168 [doi]
• Hebbian Learning of Bayes Optimal DecisionsBernhard Nessler, Michael Pfeiffer, Wolfgang Maass. 1169-1176 [doi]
• Fitted Q-iteration by Advantage Weighted RegressionGerhard Neumann, Jan Peters. 1177-1184 [doi]
• Robust Kernel Principal Component AnalysisMinh Hoai Nguyen, Fernando De la Torre. 1185-1192 [doi]
• Local Gaussian Process Regression for Real Time Online Model LearningDuy Nguyen-Tuong, Matthias Seeger, Jan Peters. 1193-1200 [doi]
• On the Efficient Minimization of Classification Calibrated SurrogatesRichard Nock, Frank Nielsen. 1201-1208 [doi]
• Multi-resolution Exploration in Continuous SpacesAli Nouri, Michael L. Littman. 1209-1216 [doi]
• High-dimensional support union recovery in multivariate regressionGuillaume Obozinski, Martin J. Wainwright, Michael I. Jordan. 1217-1224 [doi]
• A general framework for investigating how far the decoding process in the brain can be simplifiedMasafumi Oizumi, Toshiyuki Ishii, Kazuya Ishibashi, Toshihiko Hosoya, Masato Okada. 1225-1232 [doi]
• Modeling Short-term Noise Dependence of Spike Counts in Macaque Prefrontal CortexArno Onken, Steffen Grünewälder, Matthias Munk, Klaus Obermayer. 1233-1240 [doi]
• Improving on Expectation PropagationManfred Opper, Ulrich Paquet, Ole Winther. 1241-1248 [doi]
• Finding Latent Causes in Causal Networks: an Efficient Approach Based on Markov BlanketsJean-Philippe Pellet, André Elisseeff. 1249-1256 [doi]
• Estimation of Information Theoretic Measures for Continuous Random VariablesFernando Pérez-Cruz. 1257-1264 [doi]
• Biasing Approximate Dynamic Programming with a Lower Discount FactorMarek Petrik, Bruno Scherrer. 1265-1272 [doi]
• Cell Assemblies in Large Sparse Inhibitory Networks of Biologically Realistic Spiking NeuronsAdam Ponzi, Jeff Wickens. 1273-1280 [doi]
• Global Ranking Using Continuous Conditional Random FieldsTao Qin, Tie-Yan Liu, Xu-Dong Zhang, De-Sheng Wang, Hang Li. 1281-1288 [doi]
• Kernelized SortingNovi Quadrianto, Le Song, Alex J. Smola. 1289-1296 [doi]
• A mixture model for the evolution of gene expression in non-homogeneous datasetsGerald Quon, Yee Whye Teh, Esther Chan, Timothy R. Hughes, Michael Brudno, Quaid Morris. 1297-1304 [doi]
• Near-minimax recursive density estimation on the binary hypercubeMaxim Raginsky, Svetlana Lazebnik, Rebecca Willett, Jorge Silva. 1305-1312 [doi]
• Weighted Sums of Random Kitchen Sinks: Replacing minimization with randomization in learningAli Rahimi, Benjamin Recht. 1313-1320 [doi]
• The Infinite Hierarchical Factor Regression ModelPiyush Rai, Hal Daumé III. 1321-1328 [doi]
• Model Selection in Gaussian Graphical Models: High-Dimensional Consistency of l::1::-regularized MLEPradeep Ravikumar, Garvesh Raskutti, Martin Wainwright, Bin Yu. 1329-1336 [doi]
• Nonparametric sparse hierarchical models describe V1 fMRI responses to natural imagesPradeep Ravikumar, Vincent Q. Vu, Bin Yu, Thomas Naselaris, Kendrick Kay, Jack L. Gallant. 1337-1344 [doi]
• Bayesian Model of Behaviour in Economic GamesDebajyoti Ray, Brooks King-Casas, P. Read Montague, Peter Dayan. 1345-1352 [doi]
• Temporal Dynamics of Cognitive ControlJeremy Reynolds, Michael C. Mozer. 1353-1360 [doi]
• Signal-to-Noise Ratio Analysis of Policy Gradient AlgorithmsJohn W. Roberts, Russ Tedrake. 1361-1368 [doi]
• Non-stationary dynamic Bayesian networksJoshua W. Robinson, Alexander J. Hartemink. 1369-1376 [doi]
• The Mondrian ProcessDaniel M. Roy, Yee Whye Teh. 1377-1384 [doi]
• Optimization on a Budget: A Reinforcement Learning ApproachPaul Ruvolo, Ian R. Fasel, Javier R. Movellan. 1385-1392 [doi]
• Unsupervised Learning of Visual Sense Models for Polysemous WordsKate Saenko, Trevor Darrell. 1393-1400 [doi]
• Regularized Learning with Networks of FeaturesTed Sandler, John Blitzer, Partha Pratim Talukdar, Lyle H. Ungar. 1401-1408 [doi]
• Generative versus discriminative training of RBMs for classification of fMRI imagesTanya Schmah, Geoffrey E. Hinton, Richard S. Zemel, Steven L. Small, Stephen C. Strother. 1409-1416 [doi]
• Efficient Exact Inference in Planar Ising ModelsNicol N. Schraudolph, Dmitry Kamenetsky. 1417-1424 [doi]
• On Computational Power and the Order-Chaos Phase Transition in Reservoir ComputingBenjamin Schrauwen, Lars Buesing, Robert A. Legenstein. 1425-1432 [doi]
• An Empirical Analysis of Domain Adaptation Algorithms for Genomic Sequence AnalysisGabriele Schweikert, Christian Widmer, Bernhard Schölkopf, Gunnar Rätsch. 1433-1440 [doi]
• Bayesian Experimental Design of Magnetic Resonance Imaging SequencesMatthias W. Seeger, Hannes Nickisch, Rolf Pohmann, Bernhard Schölkopf. 1441-1448 [doi]
• Risk Bounds for Randomized Sample Compressed ClassifiersMohak Shah. 1449-1456 [doi]
• Mind the Duality Gap: Logarithmic regret algorithms for online optimizationShai Shalev-Shwartz, Sham M. Kakade. 1457-1464 [doi]
• On the Reliability of Clustering Stability in the Large Sample RegimeOhad Shamir, Naftali Tishby. 1465-1472 [doi]
• PSDBoost: Matrix-Generation Linear Programming for Positive Semidefinite Matrices LearningChunhua Shen, Alan Welsh, Lei Wang. 1473-1480 [doi]
• Relative Margin MachinesPannagadatta K. Shivaswamy, Tony Jebara. 1481-1488 [doi]
• Kernel-ARMA for Hand Tracking and Brain-Machine interfacing During 3D Motor ControlLavi Shpigelman, Hagai Lalazar, Eilon Vaadia. 1489-1496 [doi]
• Skill Characterization Based on BetweennessÖzgür Simsek, Andrew G. Barto. 1497-1504 [doi]
• Regularized Co-Clustering with Dual SupervisionVikas Sindhwani, Jianying Hu, Aleksandra Mojsilovic. 1505-1512 [doi]
• Unlabeled data: Now it helps, now it doesn tAarti Singh, Robert D. Nowak, Xiaojin Zhu. 1513-1520 [doi]
• The Conjoint Effect of Divisive Normalization and Orientation Selectivity on Redundancy ReductionFabian H. Sinz, Matthias Bethge. 1521-1528 [doi]
• Convergence and Rate of Convergence of a Manifold-Based Dimension Reduction AlgorithmAndrew Smith, Xiaoming Huo, Hongyuan Zha. 1529-1536 [doi]
• Clusters and Coarse Partitions in LP RelaxationsDavid Sontag, Amir Globerson, Tommi Jaakkola. 1537-1544 [doi]
• Fast Rates for Regularized ObjectivesKarthik Sridharan, Shai Shalev-Shwartz, Nathan Srebro. 1545-1552 [doi]
• Grouping Contours Via a Related ImagePraveen Srinivasan, Liming Wang, Jianbo Shi. 1553-1560 [doi]
• Non-parametric Regression Between ManifoldsFlorian Steinke, Matthias Hein. 1561-1568 [doi]
• Sparsity of SVMs that use the epsilon-insensitive lossIngo Steinwart, Andreas Christmann. 1569-1576 [doi]
• An Online Algorithm for Maximizing Submodular FunctionsMatthew J. Streeter, Daniel Golovin. 1577-1584 [doi]
• Shared Segmentation of Natural Scenes Using Dependent Pitman-Yor ProcessesErik B. Sudderth, Michael I. Jordan. 1585-1592 [doi]
• Using matrices to model symbolic relationshipIlya Sutskever, Geoffrey E. Hinton. 1593-1600 [doi]
• The Recurrent Temporal Restricted Boltzmann MachineIlya Sutskever, Geoffrey E. Hinton, Graham W. Taylor. 1601-1608 [doi]
• A Convergent O(n) Temporal-difference Algorithm for Off-policy Learning with Linear Function ApproximationRichard S. Sutton, Csaba Szepesvári, Hamid Reza Maei. 1609-1616 [doi]
• Simple Local Models for Complex Dynamical SystemsErik Talvitie, Satinder Singh. 1617-1624 [doi]
• Breaking Audio CAPTCHAsJennifer Tam, Jiri Simsa, Sean Hyde, Luis von Ahn. 1625-1632 [doi]
• Correlated Bigram LSA for Unsupervised Language Model AdaptationYik-Cheung Tam, Tanja Schultz. 1633-1640 [doi]
• Playing Pinball with non-invasive BCIMichael Tangermann, Matthias Krauledat, Konrad Grzeska, Max Sagebaum, Benjamin Blankertz, Carmen Vidaurre, Klaus-Robert Müller. 1641-1648 [doi]
• Bounding Performance Loss in Approximate MDP HomomorphismsJonathan Taylor, Doina Precup, Prakash Panangaden. 1649-1656 [doi]
• Hierarchical Semi-Markov Conditional Random Fields for Recursive Sequential DataTran The Truyen, Dinh Q. Phung, Hung Hai Bui, Svetha Venkatesh. 1657-1664 [doi]
• Integrating Locally Learned Causal Structures with Overlapping VariablesRobert E. Tillman, David Danks, Clark Glymour. 1665-1672 [doi]
• Bayesian Kernel Shaping for Learning ControlJo-Anne Ting, Mrinal Kalakrishnan, Sethu Vijayakumar, Stefan Schaal. 1673-1680 [doi]
• Efficient Sampling for Gaussian Process Inference using Control VariablesMichalis Titsias, Neil D. Lawrence, Magnus Rattray. 1681-1688 [doi]
• Learning to Use Working Memory in Partially Observable Environments through Dopaminergic ReinforcementMichael T. Todd, Yael Niv, Jonathan D. Cohen. 1689-1696 [doi]
• The Infinite Factorial Hidden Markov ModelJurgen Van Gael, Yee Whye Teh, Zoubin Ghahramani. 1697-1704 [doi]
• Multi-Level Active Prediction of Useful Image Annotations for RecognitionSudheendra Vijayanarasimhan, Kristen Grauman. 1705-1712 [doi]
• Diffeomorphic Dimensionality ReductionChristian Walder, Bernhard Schölkopf. 1713-1720 [doi]
• Learning a discriminative hidden part model for human action recognitionYang Wang, Greg Mori. 1721-1728 [doi]
• Algorithms for Infinitely Many-Armed BanditsYizao Wang, Jean-Yves Audibert, Rémi Munos. 1729-1736 [doi]
• Large Margin Taxonomy Embedding for Document CategorizationKilian Q. Weinberger, Olivier Chapelle. 1737-1744 [doi]
• Beyond Novelty Detection: Incongruent Events, when General and Specific Classifiers DisagreeDaphna Weinshall, Hynek Hermansky, Alon Zweig, Jie Luo, Holly Brügge Jimison, Frank Ohl, Misha Pavel. 1745-1752 [doi]
• Spectral HashingYair Weiss, Antonio B. Torralba, Robert Fergus. 1753-1760 [doi]
• MAS: a multiplicative approximation scheme for probabilistic inferenceYdo Wexler, Christopher Meek. 1761-1768 [doi]
• Dependence of Orientation Tuning on Recurrent Excitation and Inhibition in a Network Model of V1Klaus Wimmer, Marcel Stimberg, Robert Martin, Lars Schwabe, Jorge Mariño, James Schummers, David C. Lyon, Mriganka Sur, Klaus Obermayer. 1769-1776 [doi]
• Estimating the Location and Orientation of Complex, Correlated Neural Activity using MEGDavid Wipf, Julia Owen, Hagai Attias, Kensuke Sekihara, Srikantan S. Nagarajan. 1777-1784 [doi]
• Localized Sliced Inverse RegressionQiang Wu, Sayan Mukherjee, Feng Liang. 1785-1792 [doi]
• Model selection and velocity estimation using novel priors for motion patternsShuang Wu, Hongjing Lu, Alan L. Yuille. 1793-1800 [doi]
• Robust Regression and LassoHuan Xu, Constantine Caramanis, Shie Mannor. 1801-1808 [doi]
• How memory biases affect information transmission: A rational analysis of serial reproductionJing Xu, Thomas L. Griffiths. 1809-1816 [doi]
• Short-Term Depression in VLSI Stochastic SynapsePeng Xu, Timothy K. Horiuchi, Pamela Abshire. 1817-1824 [doi]
• An Extended Level Method for Efficient Multiple Kernel LearningZenglin Xu, Rong Jin, Irwin King, Michael R. Lyu. 1825-1832 [doi]
• Bayesian Network Score Approximation using a Metagraph KernelBenjamin Yackley, Eduardo Corona, Terran Lane. 1833-1840 [doi]
• Supervised Bipartite Graph InferenceYoshihiro Yamanishi. 1841-1848 [doi]
• Learning with Consistency between Inductive Functions and KernelsHaixuan Yang, Irwin King, Michael R. Lyu. 1849-1856 [doi]
• Semi-supervised Learning with Weakly-Related Unlabeled Data: Towards Better Text CategorizationLiu Yang, Rong Jin, Rahul Sukthankar. 1857-1864 [doi]
• Spike Feature Extraction Using Informative SamplesZhi Yang, Qi Zhao, Wentai Liu. 1865-1872 [doi]
• Sequential effects: Superstition or rational behavior?Angela J. Yu, Jonathan D. Cohen. 1873-1880 [doi]
• Gaussian-process factor analysis for low-dimensional single-trial analysis of neural population activityByron M. Yu, John P. Cunningham, Gopal Santhanam, Stephen I. Ryu, Krishna V. Shenoy, Maneesh Sahani. 1881-1888 [doi]
• Deep Learning with Kernel Regularization for Visual RecognitionKai Yu, Wei Xu, Yihong Gong. 1889-1896 [doi]
• Variational Mixture of Gaussian Process ExpertsChao Yuan, Claus Neubauer. 1897-1904 [doi]
• Multi-Agent Filtering with Infinitely Nested BeliefsLuke S. Zettlemoyer, Brian Milch, Leslie Pack Kaelbling. 1905-1912 [doi]
• Fast Computation of Posterior Mode in Multi-Level Hierarchical ModelsLiang Zhang, Deepak Agarwal. 1913-1920 [doi]
• Adaptive Forward-Backward Greedy Algorithm for Sparse Learning with Linear ModelsTong Zhang. 1921-1928 [doi]
• Multi-stage Convex Relaxation for Learning with Sparse RegularizationTong Zhang. 1929-1936 [doi]
• Kernel Measures of Independence for non-iid DataXinhua Zhang, Le Song, Arthur Gretton, Alex J. Smola. 1937-1944 [doi]
• Learning the Semantic Correlation: An Alternative Way to Gain from Unlabeled TextYi Zhang, Jeff Schneider, Artur Dubrawski. 1945-1952 [doi]
• Cyclizing Clusters via Zeta Function of a GraphDeli Zhao, Xiaoou Tang. 1953-1960 [doi]
• Hierarchical Fisher Kernels for Longitudinal DataZhengdong Lu, Todd K. Leen, Jeffrey Kaye. 1961-1968 [doi]
• Posterior Consistency of the Silverman g-prior in Bayesian Model ChoiceZhihua Zhang, Michael I. Jordan, Dit-Yan Yeung. 1969-1976 [doi]
• Partially Observed Maximum Entropy Discrimination Markov NetworksJun Zhu, Eric P. Xing, Bo Zhang. 1977-1984 [doi]
• Recursive Segmentation and Recognition Templates for 2D ParsingLeo Zhu, Yuanhao Chen, Yuan Lin, Chenxi Lin, Alan L. Yuille. 1985-1992 [doi]
• Stochastic Relational Models for Large-scale Dyadic Data using MCMCShenghuo Zhu, Kai Yu, Yihong Gong. 1993-2000 [doi]