Table of Contents

• Repeated Games against Budgeted AdversariesJacob Abernethy, Manfred K. Warmuth. 1-9 [doi]
• Towards Property-Based Classification of Clustering ParadigmsMargareta Ackerman, Shai Ben-David, David Loker. 10-18 [doi]
• Tree-Structured Stick Breaking for Hierarchical DataRyan Prescott Adams, Zoubin Ghahramani, Michael I. Jordan. 19-27 [doi]
• Sparse Instrumental Variables (SPIV) for Genome-Wide StudiesFelix V. Agakov, Paul McKeigue, Jon Krohn, Amos J. Storkey. 28-36 [doi]
• Fast global convergence rates of gradient methods for high-dimensional statistical recoveryAlekh Agarwal, Sahand Negahban, Martin J. Wainwright. 37-45 [doi]
• Learning Multiple Tasks using Manifold RegularizationArvind Agarwal, Hal Daumé III, Samuel Gerber. 46-54 [doi]
• Switched Latent Force Models for Movement SegmentationMauricio A. Álvarez, Jan Peters, Bernhard Schölkopf, Neil D. Lawrence. 55-63 [doi]
• A POMDP Extension with Belief-dependent RewardsMauricio Araya-López, Olivier Buffet, Vincent Thomas, François Charpillet. 64-72 [doi]
• Global seismic monitoring as probabilistic inferenceNimar S. Arora, Stuart J. Russell, Paul Kidwell, Erik B. Sudderth. 73-81 [doi]
• Learning invariant features using the Transformed Indian Buffet ProcessJoseph L. Austerweil, Thomas L. Griffiths. 82-90 [doi]
• Supervised ClusteringPranjal Awasthi, Reza Bosagh Zadeh. 91-99 [doi]
• Occlusion Detection and Motion Estimation with Convex OptimizationAlper Ayvaci, Michalis Raptis, Stefano Soatto. 100-108 [doi]
• Batch Bayesian Optimization via Simulation MatchingJavad Azimi, Alan Fern, Xiaoli Fern. 109-117 [doi]
• Structured sparsity-inducing norms through submodular functionsFrancis R. Bach. 118-126 [doi]
• A Bayesian Approach to Concept DriftStephen H. Bach, Marcus A. Maloof. 127-135 [doi]
• Auto-Regressive HMM Inference with Incomplete Data for Short-Horizon Wind ForecastingChris Barber, Joseph Bockhorst, Paul Roebber. 136-144 [doi]
• The LASSO risk: asymptotic results and real world examplesMohsen Bayati, José Bento, Andrea Montanari. 145-153 [doi]
• Extensions of Generalized Binary Search to Group Identification and Exponential CostsGowtham Bellala, Suresh K. Bhavnani, Clayton Scott. 154-162 [doi]
• Label Embedding Trees for Large Multi-Class TasksSamy Bengio, Jason Weston, David Grangier. 163-171 [doi]
• Learning Networks of Stochastic Differential EquationsJosé Bento, Morteza Ibrahimi, Andrea Montanari. 172-180 [doi]
• Exploiting weakly-labeled Web images to improve object classification: a domain adaptation approachAlessandro Bergamo, Lorenzo Torresani. 181-189 [doi]
• Online Classification with Specificity ConstraintsAndrey Bernstein, Shie Mannor, Nahum Shimkin. 190-198 [doi]
• Agnostic Active Learning Without ConstraintsAlina Beygelzimer, Daniel Hsu, John Langford, Tong Zhang 0001. 199-207 [doi]
• Inference with Multivariate Heavy-Tails in Linear ModelsDanny Bickson, Carlos Guestrin. 208-216 [doi]
• CUR from a Sparse Optimization ViewpointJacob Bien, Ya Xu, Michael W. Mahoney. 217-225 [doi]
• Optimal learning rates for Kernel Conjugate Gradient regressionGilles Blanchard, Nicole Krämer. 226-234 [doi]
• Simultaneous Object Detection and Ranking with Weak SupervisionMatthew B. Blaschko, Andrea Vedaldi, Andrew Zisserman. 235-243 [doi]
• Kernel Descriptors for Visual RecognitionLiefeng Bo, Xiaofeng Ren, Dieter Fox. 244-252 [doi]
• Fractionally Predictive Spiking NeuronsSander M. Bohte, Jaldert O. Rombouts. 253-261 [doi]
• Gaussian Process Preference ElicitationEdwin V. Bonilla, Shengbo Guo, Scott Sanner. 262-270 [doi]
• Predictive State Temporal Difference LearningByron Boots, Geoffrey J. Gordon. 271-279 [doi]
• Variational Inference over Combinatorial SpacesAlexandre Bouchard-Côté, Michael I. Jordan. 280-288 [doi]
• Bootstrapping Apprenticeship LearningAbdeslam Boularias, Brahim Chaib-draa. 289-297 [doi]
• Random Projections for $k$-means ClusteringChristos Boutsidis, Anastasios Zouzias, Petros Drineas. 298-306 [doi]
• Segmentation as Maximum-Weight Independent SetWilliam Brendel, Sinisa Todorovic. 307-315 [doi]
• Computing Marginal Distributions over Continuous Markov Networks for Statistical Relational LearningMatthias Broecheler, Lise Getoor. 316-324 [doi]
• Multi-label Multiple Kernel Learning by Stochastic Approximation: Application to Visual Object RecognitionSerhat Selcuk Bucak, Rong Jin, Anil K. Jain. 325-333 [doi]
• Learning concept graphs from text with stick-breaking priorsAmerica Chambers, Padhraic Smyth, Mark Steyvers. 334-342 [doi]
• Rates of convergence for the cluster treeKamalika Chaudhuri, Sanjoy Dasgupta. 343-351 [doi]
• Evidence-Specific Structures for Rich Tractable CRFsAnton Chechetka, Carlos Guestrin. 352-360 [doi]
• Predictive Subspace Learning for Multi-view Data: a Large Margin ApproachNing Chen, Jun Zhu, Eric P. Xing. 361-369 [doi]
• Two-Layer Generalization Analysis for Ranking Using Rademacher AverageWei Chen, Tie-Yan Liu, Zhiming Ma. 370-378 [doi]
• SpikeAnts, a spiking neuron network modelling the emergence of organization in a complex systemSylvain Chevallier, Hélène Paugam-Moisy, Michèle Sebag. 379-387 [doi]
• Movement extraction by detecting dynamics switches and repetitionsSilvia Chiappa, Jan Peters. 388-396 [doi]
• Learning sparse dynamic linear systems using stable spline kernels and exponential hyperpriorsAlessandro Chiuso, Gianluigi Pillonetto. 397-405 [doi]
• Universal Kernels on Non-Standard Input SpacesAndreas Christmann, Ingo Steinwart. 406-414 [doi]
• Causal discovery in multiple models from different experimentsTom Claassen, Tom Heskes. 415-423 [doi]
• Empirical Risk Minimization with Approximations of Probabilistic GrammarsShay B. Cohen, Noah A. Smith. 424-432 [doi]
• Mixture of time-warped trajectory models for movement decodingElaine Corbett, Eric J. Perreault, Konrad Koerding. 433-441 [doi]
• Learning Bounds for Importance WeightingCorinna Cortes, Yishay Mansour, Mehryar Mohri. 442-450 [doi]
• Learning via Gaussian HerdingKoby Crammer, Daniel D. Lee. 451-459 [doi]
• Spatial and anatomical regularization of SVM for brain image analysisRémi Cuingnet, Marie Chupin, Habib Benali, Olivier Colliot. 460-468 [doi]
• Phone Recognition with the Mean-Covariance Restricted Boltzmann MachineGeorge E. Dahl, Marc'Aurelio Ranzato, Abdel-rahman Mohamed, Geoffrey E. Hinton. 469-477 [doi]
• Co-regularization Based Semi-supervised Domain AdaptationHal Daumé III, Abhishek Kumar, Avishek Saha. 478-486 [doi]
• Spectral Regularization for Support EstimationErnesto De Vito, Lorenzo Rosasco, Alessandro Toigo. 487-495 [doi]
• Random Projection Trees RevisitedAman Dhesi, Purushottam Kar. 496-504 [doi]
• Throttling Poisson ProcessesUwe Dick, Peter Haider, Thomas Vanck, Michael Brückner, Tobias Scheffer. 505-513 [doi]
• t-logistic regressionNan Ding, S. V. N. Vishwanathan. 514-522 [doi]
• Implicit Differentiation by PerturbationJustin Domke. 523-531 [doi]
• Nonparametric Bayesian Policy Priors for Reinforcement LearningFinale Doshi-Velez, David Wingate, Nicholas Roy, Joshua B. Tenenbaum. 532-540 [doi]
• Over-complete representations on recurrent neural networks can support persistent perceptsShaul Druckmann, Dmitri B. Chklovskii. 541-549 [doi]
• Distributed Dual Averaging In NetworksJohn C. Duchi, Alekh Agarwal, Martin J. Wainwright. 550-558 [doi]
• Copula Bayesian NetworksGal Elidan. 559-567 [doi]
• Error Propagation for Approximate Policy and Value IterationAmir Massoud Farahmand, Rémi Munos, Csaba Szepesvári. 568-576 [doi]
• A Computational Decision Theory for Interactive AssistantsAlan Fern, Prasad Tadepalli. 577-585 [doi]
• Parametric Bandits: The Generalized Linear CaseSarah Filippi, Olivier Cappé, Aurélien Garivier, Csaba Szepesvári. 586-594 [doi]
• A Novel Kernel for Learning a Neuron Model from Spike Train DataNicholas Fisher, Arunava Banerjee. 595-603 [doi]
• Extended Bayesian Information Criteria for Gaussian Graphical ModelsRina Foygel, Mathias Drton. 604-612 [doi]
• Shadow Dirichlet for Restricted Probability ModelingBela A. Frigyik, Maya R. Gupta, Yihua Chen. 613-621 [doi]
• Size Matters: Metric Visual Search Constraints from Monocular MetadataMario Fritz, Kate Saenko, Trevor Darrell. 622-630 [doi]
• A Bayesian Framework for Figure-Ground InterpretationVicky Froyen, Jacob Feldman, Manish Singh. 631-639 [doi]
• Attractor Dynamics with Synaptic DepressionC. C. Alan Fung, K. Y. Michael Wong, He Wang, Si Wu. 640-648 [doi]
• Learning Kernels with Radiuses of Minimum Enclosing BallsKun Gai, Guangyun Chen, Changshui Zhang. 649-657 [doi]
• Implicit encoding of prior probabilities in optimal neural populationsDeep Ganguli, Eero P. Simoncelli. 658-666 [doi]
• Short-term memory in neuronal networks through dynamical compressed sensingSurya Ganguli, Haim Sompolinsky. 667-675 [doi]
• Group Sparse Coding with a Laplacian Scale Mixture PriorPierre Garrigues, Bruno A. Olshausen. 676-684 [doi]
• Improvements to the Sequence MemoizerJan Gasthaus, Yee Whye Teh. 685-693 [doi]
• On Herding and the Perceptron Cycling TheoremAndrew Gelfand, Yutian Chen, Laurens van der Maaten, Max Welling. 694-702 [doi]
• Rescaling, thinning or complementing? On goodness-of-fit procedures for point process models and Generalized Linear ModelsFelipe Gerhard, Wulfram Gerstner. 703-711 [doi]
• The Neural Costs of Optimal ControlSamuel Gershman, Robert Wilson. 712-720 [doi]
• LSTD with Random ProjectionsMohammad Ghavamzadeh, Alessandro Lazaric, Odalric-Ambrym Maillard, Rémi Munos. 721-729 [doi]
• Humans Learn Using Manifolds, ReluctantlyBryan R. Gibson, Xiaojin Zhu, Timothy T. Rogers, Chuck Kalish, Joseph Harrison. 730-738 [doi]
• Universal Consistency of Multi-Class Support Vector ClassificationTobias Glasmachers. 739-747 [doi]
• Learning Efficient Markov NetworksVibhav Gogate, William Austin Webb, Pedro Domingos. 748-756 [doi]
• Transduction with Matrix Completion: Three Birds with One StoneAndrew B. Goldberg, Xiaojin Zhu, Ben Recht, Jun Ming Xu, Robert D. Nowak. 757-765 [doi]
• Near-Optimal Bayesian Active Learning with Noisy ObservationsDaniel Golovin, Andreas Krause, Debajyoti Ray. 766-774 [doi]
• Discriminative Clustering by Regularized Information MaximizationRyan Gomes, Andreas Krause, Pietro Perona. 775-783 [doi]
• Learning to localise sounds with spiking neural networksDan F. M. Goodman, Romain Brette. 784-792 [doi]
• Feature Set Embedding for Incomplete DataDavid Grangier, Iain Melvin. 793-801 [doi]
• Active Instance Sampling via Matrix PartitionYuhong Guo. 802-810 [doi]
• Avoiding False Positive in Multi-Instance LearningYanjun Han, Qing Tao, Jue Wang. 811-819 [doi]
• Nonparametric Density Estimation for Stochastic Optimization with an Observable State VariableLauren Hannah, Warren B. Powell, David M. Blei. 820-828 [doi]
• Space-Variant Single-Image Blind Deconvolution for Removing Camera ShakeStefan Harmeling, Michael Hirsch, Bernhard Schölkopf. 829-837 [doi]
• A Primal-Dual Message-Passing Algorithm for Approximated Large Scale Structured PredictionTamir Hazan, Raquel Urtasun. 838-846 [doi]
• An Inverse Power Method for Nonlinear Eigenproblems with Applications in 1-Spectral Clustering and Sparse PCAMatthias Hein, Thomas Bühler. 847-855 [doi]
• Online Learning for Latent Dirichlet AllocationMatthew D. Hoffman, David M. Blei, Francis R. Bach. 856-864 [doi]
• Latent Variable Models for Predicting File Dependencies in Large-Scale Software DevelopmentDiane Hu, Laurens van der Maaten, Youngmin Cho, Lawrence K. Saul, Sorin Lerner. 865-873 [doi]
• Exact inference and learning for cumulative distribution functions on loopy graphsJim C. Huang, Nebojsa Jojic, Christopher Meek. 874-882 [doi]
• Predicting Execution Time of Computer Programs Using Sparse Polynomial RegressionLing Huang, Jinzhu Jia, Bin Yu, Byung-Gon Chun, Petros Maniatis, Mayur Naik. 883-891 [doi]
• Active Learning by Querying Informative and Representative ExamplesSheng-Jun Huang, Rong Jin, Zhi-Hua Zhou. 892-900 [doi]
• Inter-time segment information sharing for non-homogeneous dynamic Bayesian networksDirk Husmeier, Frank Dondelinger, Sophie Lèbre. 901-909 [doi]
• Deciphering subsampled data: adaptive compressive sampling as a principle of brain communicationGuy Isley, Christopher J. Hillar, Friedrich T. Sommer. 910-918 [doi]
• Dynamic Infinite Relational Model for Time-varying Relational Data AnalysisKatsuhiko Ishiguro, Tomoharu Iwata, Naonori Ueda, Joshua B. Tenenbaum. 919-927 [doi]
• Hashing Hyperplane Queries to Near Points with Applications to Large-Scale Active LearningPrateek Jain 0002, Sudheendra Vijayanarasimhan, Kristen Grauman. 928-936 [doi]
• Guaranteed Rank Minimization via Singular Value ProjectionPrateek Jain 0002, Raghu Meka, Inderjit S. Dhillon. 937-945 [doi]
• Inductive Regularized Learning of Kernel FunctionsPrateek Jain 0002, Brian Kulis, Inderjit S. Dhillon. 946-954 [doi]
• MAP estimation in Binary MRFs via Bipartite Multi-cutsSashank Jakkam Reddi, Sunita Sarawagi, Sundar Vishwanathan. 955-963 [doi]
• A Dirty Model for Multi-task LearningAli Jalali, Pradeep D. Ravikumar, Sujay Sanghavi, Chao Ruan. 964-972 [doi]
• Lifted Inference Seen from the Other Side : The Tractable FeaturesAbhay Kumar Jha, Vibhav Gogate, Alexandra Meliou, Dan Suciu. 973-981 [doi]
• Factorized Latent Spaces with Structured SparsityYangqing Jia, Mathieu Salzmann, Trevor Darrell. 982-990 [doi]
• Bayesian Action-Graph GamesAlbert Xin Jiang, Kevin Leyton-Brown. 991-999 [doi]
• On a Connection between Importance Sampling and the Likelihood Ratio Policy GradientJie Tang, Pieter Abbeel. 1000-1008 [doi]
• Linear Complementarity for Regularized Policy Evaluation and ImprovementJeffrey Johns, Christopher Painter-Wakefield, Ronald Parr. 1009-1017 [doi]
• Synergies in learning words and their referentsMark Johnson, Katherine Demuth, Michael C. Frank, Bevan K. Jones. 1018-1026 [doi]
• Structural epitome: a way to summarize one's visual experienceNebojsa Jojic, Alessandro Perina, Vittorio Murino. 1027-1035 [doi]
• Probabilistic Belief Revision with Structural ConstraintsPeter Jones, Venkatesh Saligrama, Sanjoy K. Mitter. 1036-1044 [doi]
• Efficient Optimization for Discriminative Latent Class ModelsArmand Joulin, Francis R. Bach, Jean Ponce. 1045-1053 [doi]
• Non-Stochastic Bandit Slate ProblemsSatyen Kale, Lev Reyzin, Robert E. Schapire. 1054-1062 [doi]
• Static Analysis of Binary Executables Using Structural SVMsNikos Karampatziakis. 1063-1071 [doi]
• Using body-anchored priors for identifying actions in single imagesLeonid Karlinsky, Michael Dinerstein, Shimon Ullman. 1072-1080 [doi]
• Effects of Synaptic Weight Diffusion on Learning in Decision Making NetworksKentaro Katahira, Kazuo Okanoya, Masato Okada. 1081-1089 [doi]
• Learning Convolutional Feature Hierarchies for Visual RecognitionKoray Kavukcuoglu, Pierre Sermanet, Y-Lan Boureau, Karol Gregor, Michaël Mathieu, Yann LeCun. 1090-1098 [doi]
• Accounting for network effects in neuronal responses using L1 regularized point process modelsRyan C. Kelly, Matthew A. Smith, Robert E. Kass, Tai Sing Lee. 1099-1107 [doi]
• Variational bounds for mixed-data factor analysisMohammad Emtiyaz Khan, Benjamin M. Marlin, Guillaume Bouchard, Kevin P. Murphy. 1108-1116 [doi]
• Sparse Coding for Learning Interpretable Spatio-Temporal PrimitivesTaehwan Kim, Gregory Shakhnarovich, Raquel Urtasun. 1117-1125 [doi]
• Regularized estimation of image statistics by Score MatchingDiederik P. Kingma, Yann LeCun. 1126-1134 [doi]
• Random Conic Pursuit for Semidefinite ProgrammingAriel Kleiner, Ali Rahimi, Michael I. Jordan. 1135-1143 [doi]
• Generalized roof duality and bisubmodular functionsVladimir Kolmogorov. 1144-1152 [doi]
• Energy Disaggregation via Discriminative Sparse CodingJ. Zico Kolter, Siddharth Batra, Andrew Y. Ng. 1153-1161 [doi]
• Constructing Skill Trees for Reinforcement Learning Agents from Demonstration TrajectoriesGeorge Konidaris, Scott Kuindersma, Andrew G. Barto, Roderic A. Grupen. 1162-1170 [doi]
• Structured Determinantal Point ProcessesAlex Kulesza, Ben Taskar. 1171-1179 [doi]
• MAP Estimation for Graphical Models by Likelihood MaximizationAkshat Kumar, Shlomo Zilberstein. 1180-1188 [doi]
• Self-Paced Learning for Latent Variable ModelsM. Pawan Kumar, Benjamin Packer, Daphne Koller. 1189-1197 [doi]
• Efficient algorithms for learning kernels from multiple similarity matrices with general convex loss functionsAchintya Kundu, Vikram Tankasali, Chiranjib Bhattacharyya, Aharon Ben-Tal. 1198-1206 [doi]
• Evaluation of Rarity of Fingerprints in ForensicsChang Su, Sargur N. Srihari. 1207-1215 [doi]
• Beyond Actions: Discriminative Models for Contextual Group ActivitiesTian Lan, Yang Wang 0003, Weilong Yang, Greg Mori. 1216-1224 [doi]
• Functional Geometry Alignment and Localization of Brain AreasGeorg Langs, Yanmei Tie, Laura Rigolo, Alexandra Golby, Polina Golland. 1225-1233 [doi]
• Efficient Relational Learning with Hidden Variable DetectionNi Lao, Jun Zhu, Xinwang Liu, Yandong Liu, William W. Cohen. 1234-1242 [doi]
• Learning to combine foveal glimpses with a third-order Boltzmann machineHugo Larochelle, Geoffrey E. Hinton. 1243-1251 [doi]
• Categories and Functional Units: An Infinite Hierarchical Model for Brain ActivationsDanial Lashkari, Ramesh Sridharan, Polina Golland. 1252-1260 [doi]
• Identifying Dendritic ProcessingAurel A. Lazar, Yevgeniy B. Slutskiy. 1261-1269 [doi]
• Cross Species Expression Analysis using a Dirichlet Process Mixture Model with Latent MatchingsHai-son Le, Ziv Bar-Joseph. 1270-1278 [doi]
• Tiled convolutional neural networksQuoc V. Le, Jiquan Ngiam, Zhenghao Chen, Daniel Jin hao Chia, Pang Wei Koh, Andrew Y. Ng. 1279-1287 [doi]
• Estimating Spatial Layout of Rooms using Volumetric Reasoning about Objects and SurfacesDavid C. Lee, Abhinav Gupta, Martial Hebert, Takeo Kanade. 1288-1296 [doi]
• Practical Large-Scale Optimization for Max-norm RegularizationJason D. Lee, Ben Recht, Ruslan Salakhutdinov, Nathan Srebro, Joel A. Tropp. 1297-1305 [doi]
• Adaptive Multi-Task Lasso: with Application to eQTL DetectionSeunghak Lee, Jun Zhu, Eric P. Xing. 1306-1314 [doi]
• Joint Cascade Optimization Using A Product Of Boosted ClassifiersLeonidas Lefakis, François Fleuret. 1315-1323 [doi]
• Learning To Count Objects in ImagesVictor S. Lempitsky, Andrew Zisserman. 1324-1332 [doi]
• Optimal Web-Scale Tiering as a Flow ProblemGilbert Leung, Novi Quadrianto, Alexander J. Smola, Kostas Tsioutsiouliklis. 1333-1341 [doi]
• Feature Construction for Inverse Reinforcement LearningSergey Levine, Zoran Popovic, Vladlen Koltun. 1342-1350 [doi]
• Towards Holistic Scene Understanding: Feedback Enabled Cascaded Classification ModelsCongcong Li, Adarsh Kowdle, Ashutosh Saxena, Tsuhan Chen. 1351-1359 [doi]
• Convex Multiple-Instance Learning by Estimating Likelihood RatioFuxin Li, Cristian Sminchisescu. 1360-1368 [doi]
• Individualized ROI Optimization via Maximization of Group-wise Consistency of Structural and Functional ProfilesKaiming Li, Lei Guo, Carlos Faraco, Dajiang Zhu, Fan Deng, Tuo Zhang, Xi Jiang, Degang Zhang, Hanbo Chen, Xintao Hu, Steve Miller, Tianming Liu. 1369-1377 [doi]
• Object Bank: A High-Level Image Representation for Scene Classification & Semantic Feature SparsificationLi-Jia Li, Hao Su, Eric P. Xing, Fei-Fei Li. 1378-1386 [doi]
• b-Bit Minwise Hashing for Estimating Three-Way SimilaritiesPing Li 0001, Arnd Christian König, Wenhao Gui. 1387-1395 [doi]
• Construction of Dependent Dirichlet Processes based on Poisson ProcessesDahua Lin, Eric Grimson, John W. Fisher III. 1396-1404 [doi]
• Deep Coding NetworkYuanqing Lin, Tong Zhang 0001, Shenghuo Zhu, Kai Yu. 1405-1413 [doi]
• Robust Clustering as Ensembles of Affinity RelationsHairong Liu, Longin Jan Latecki, Shuicheng Yan. 1414-1422 [doi]
• Graph-Valued RegressionHan Liu, Xi Chen, John D. Lafferty, Larry A. Wasserman. 1423-1431 [doi]
• Stability Approach to Regularization Selection (StARS) for High Dimensional Graphical ModelsHan Liu, Kathryn Roeder, Larry A. Wasserman. 1432-1440 [doi]
• Multivariate Dyadic Regression Trees for Sparse Learning ProblemsHan Liu, Xi Chen. 1441-1449 [doi]
• Multi-Stage Dantzig SelectorJi Liu 0002, Peter Wonka, Jieping Ye. 1450-1458 [doi]
• Moreau-Yosida Regularization for Grouped Tree Structure LearningJun Liu, Jieping Ye. 1459-1467 [doi]
• Decoding Ipsilateral Finger Movements from ECoG Signals in HumansYuzong Liu, Mohit Sharma, Charles M. Gaona, Jonathan Breshears, Jarod Roland, Zachary Freudenburg, Kilian Q. Weinberger, Eric Leuthardt. 1468-1476 [doi]
• Approximate Inference by Compilation to Arithmetic CircuitsDaniel Lowd, Pedro Domingos. 1477-1485 [doi]
• Block Variable Selection in Multivariate Regression and High-dimensional Causal InferenceAurelie C. Lozano, Vikas Sindhwani. 1486-1494 [doi]
• Functional form of motion priors in human motion perceptionHongjing Lu, Tungyou Lin, Alan L. F. Lee, Luminita A. Vese, Alan L. Yuille. 1495-1503 [doi]
• Learning from Candidate Labeling SetsJie Luo, Francesco Orabona. 1504-1512 [doi]
• Decomposing Isotonic Regression for Efficiently Solving Large ProblemsRonny Luss, Saharon Rosset, Moni Shahar. 1513-1521 [doi]
• Divisive Normalization: Justification and Effectiveness as Efficient Coding TransformSiwei Lyu. 1522-1530 [doi]
• Permutation Complexity Bound on Out-Sample ErrorMalik Magdon-Ismail. 1531-1539 [doi]
• Basis Construction from Power Series Expansions of Value FunctionsSridhar Mahadevan, Bo Liu. 1540-1548 [doi]
• Scrambled Objects for Least-Squares RegressionOdalric-Ambrym Maillard, Rémi Munos. 1549-1557 [doi]
• Network Flow Algorithms for Structured SparsityJulien Mairal, Rodolphe Jenatton, Guillaume Obozinski, Francis R. Bach. 1558-1566 [doi]
• Sphere Embedding: An Application to Part-of-Speech InductionYariv Maron, Michael Lamar, Elie Bienenstock. 1567-1575 [doi]
• Variable margin losses for classifier designHamed Masnadi-Shirazi, Nuno Vasconcelos. 1576-1584 [doi]
• Why are some word orders more common than others? A uniform information density accountLuke Maurits, Daniel J. Navarro, Amy Perfors. 1585-1593 [doi]
• Direct Loss Minimization for Structured PredictionDavid A. McAllester, Tamir Hazan, Joseph Keshet. 1594-1602 [doi]
• Gated Softmax ClassificationRoland Memisevic, Christopher Zach, Geoffrey E. Hinton, Marc Pollefeys. 1603-1611 [doi]
• A Family of Penalty Functions for Structured SparsityCharles A. Micchelli, Jean Morales, Massimiliano Pontil. 1612-1623 [doi]
• PAC-Bayesian Model Selection for Reinforcement LearningMahdi Milani Fard, Joelle Pineau. 1624-1632 [doi]
• Subgraph Detection Using Eigenvector L1 NormsBenjamin A. Miller, Nadya T. Bliss, Patrick J. Wolfe. 1633-1641 [doi]
• A VLSI Implementation of the Adaptive Exponential Integrate-and-Fire Neuron ModelSebastian Millner, Andreas Grübl, Karlheinz Meier, Johannes Schemmel, Marc-Olivier Schwartz. 1642-1650 [doi]
• Large-Scale Matrix Factorization with Missing Data under Additional ConstraintsKaushik Mitra, Sameer Sheorey, Rama Chellappa. 1651-1659 [doi]
• Natural Policy Gradient Methods with Parameter-based Exploration for Control TasksAtsushi Miyamae, Yuichi Nagata, Isao Ono, Shigenobu Kobayashi. 1660-1668 [doi]
• An analysis on negative curvature induced by singularity in multi-layer neural-network learningEiji Mizutani, Stuart Dreyfus. 1669-1677 [doi]
• Layer-wise analysis of deep networks with Gaussian kernelsGrégoire Montavon, Mikio L. Braun, Klaus-Robert Müller. 1678-1686 [doi]
• Probabilistic latent variable models for distinguishing between cause and effectJoris M. Mooij, Oliver Stegle, Dominik Janzing, Kun Zhang, Bernhard Schölkopf. 1687-1695 [doi]
• Epitome driven 3-D Diffusion Tensor image segmentation: on extracting specific structuresKamiya Motwani, Nagesh Adluru, Chris Hinrichs, Andrew L. Alexander, Vikas Singh. 1696-1704 [doi]
• Improving Human Judgments by Decontaminating Sequential DependenciesMichael Mozer, Harold Pashler, Matthew H. Wilder, Robert A. Lindsey, Matt Jones, Michael Jones. 1705-1713 [doi]
• A Theory of Multiclass BoostingIndraneel Mukherjee, Robert E. Schapire. 1714-1722 [doi]
• A biologically plausible network for the computation of orientation dominanceKritika Muralidharan, Nuno Vasconcelos. 1723-1731 [doi]
• Slice sampling covariance hyperparameters of latent Gaussian modelsIain Murray, Ryan Prescott Adams. 1732-1740 [doi]
• On the Convexity of Latent Social Network InferenceSeth A. Myers, Jure Leskovec. 1741-1749 [doi]
• Infinite Relational Modeling of Functional Connectivity in Resting State fMRIMorten Mørup, Kristoffer Hougaard Madsen, Anne-Marie Dogonowski, Hartwig Siebner, Lars Kai Hansen. 1750-1758 [doi]
• Minimum Average Cost ClusteringKiyohito Nagano, Yoshinobu Kawahara, Satoru Iwata. 1759-1767 [doi]
• Global Analytic Solution for Variational Bayesian Matrix FactorizationShinichi Nakajima, Masashi Sugiyama, Ryota Tomioka. 1768-1776 [doi]
• Random Walk Approach to Regret MinimizationHariharan Narayanan, Alexander Rakhlin. 1777-1785 [doi]
• Sample Complexity of Testing the Manifold HypothesisHariharan Narayanan, Sanjoy K. Mitter. 1786-1794 [doi]
• Learning the context of a categoryDaniel J. Navarro. 1795-1803 [doi]
• Online Markov Decision Processes under Bandit FeedbackGergely Neu, András György, Csaba Szepesvári, András Antos. 1804-1812 [doi]
• Efficient and Robust Feature Selection via Joint ℓ2, 1-Norms MinimizationFeiping Nie, Heng Huang, Xiao Cai, Chris H. Q. Ding. 1813-1821 [doi]
• Generative Local Metric Learning for Nearest Neighbor ClassificationYung-Kyun Noh, Byoung-Tak Zhang, Daniel D. Lee. 1822-1830 [doi]
• Approximate inference in continuous time Gaussian-Jump processesManfred Opper, Andreas Ruttor, Guido Sanguinetti. 1831-1839 [doi]
• New Adaptive Algorithms for Online ClassificationFrancesco Orabona, Koby Crammer. 1840-1848 [doi]
• Estimation of Renyi Entropy and Mutual Information Based on Generalized Nearest-Neighbor GraphsDávid Pál, Barnabás Póczos, Csaba Szepesvári. 1849-1857 [doi]
• Gaussian sampling by local perturbationsGeorge Papandreou, Alan L. Yuille. 1858-1866 [doi]
• Large Margin Multi-Task Metric LearningShibin Parameswaran, Kilian Q. Weinberger. 1867-1875 [doi]
• Multiparty Differential Privacy via Aggregation of Locally Trained ClassifiersManas A. Pathak, Shantanu Rane, Bhiksha Raj. 1876-1884 [doi]
• (RF)^2 - Random Forest Random FieldNadia Payet, Sinisa Todorovic. 1885-1893 [doi]
• On the Theory of Learnining with Privileged InformationDmitry Pechyony, Vladimir Vapnik. 1894-1902 [doi]
• Empirical Bernstein Inequalities for U-StatisticsThomas Peel, Sandrine Anthoine, Liva Ralaivola. 1903-1911 [doi]
• Reverse Multi-Label LearningJames Petterson, Tibério S. Caetano. 1912-1920 [doi]
• Word Features for Latent Dirichlet AllocationJames Petterson, Alexander J. Smola, Tibério S. Caetano, Wray L. Buntine, Shravan M. Narayanamurthy. 1921-1929 [doi]
• Probabilistic Deterministic Infinite AutomataDavid Pfau, Nicholas Bartlett, Frank Wood. 1930-1938 [doi]
• The Maximal Causes of Natural Scenes are Edge FiltersGervasio Puertas, Jörg Bornschein, Jörg Lücke. 1939-1947 [doi]
• A New Probabilistic Model for Rank AggregationTao Qin, Xiubo Geng, Tie-Yan Liu. 1948-1956 [doi]
• Multitask Learning without Label CorrespondencesNovi Quadrianto, Alexander J. Smola, Tibério S. Caetano, S. V. N. Vishwanathan, James Petterson. 1957-1965 [doi]
• Link Discovery using Graph Feature TrackingEmile Richard, Nicolas Baskiotis, Theodoros Evgeniou, Nicolas Vayatis. 1966-1974 [doi]
• Inferring Stimulus Selectivity from the Spatial Structure of Neural Network DynamicsKanaka Rajan, L. Abbott, Haim Sompolinsky. 1975-1983 [doi]
• Online Learning: Random Averages, Combinatorial Parameters, and LearnabilityAlexander Rakhlin, Karthik Sridharan, Ambuj Tewari. 1984-1992 [doi]
• Evaluating neuronal codes for inference using Fisher informationHaefner Ralf, Matthias Bethge. 1993-2001 [doi]
• Generating more realistic images using gated MRF'sMarc'Aurelio Ranzato, Volodymyr Mnih, Geoffrey E. Hinton. 2002-2010 [doi]
• An Approximate Inference Approach to Temporal Optimization in Optimal ControlKonrad Rawlik, Marc Toussaint, Sethu Vijayakumar. 2011-2019 [doi]
• Hallucinations in Charles Bonnet Syndrome Induced by Homeostasis: a Deep Boltzmann Machine ModelDavid P. Reichert, Peggy Seriès, Amos J. Storkey. 2020-2028 [doi]
• An Alternative to Low-level-Sychrony-Based Methods for Speech DetectionPaul Ruvolo, Javier R. Movellan. 2029-2037 [doi]
• Tight Sample Complexity of Large-Margin LearningSivan Sabato, Nathan Srebro, Naftali Tishby. 2038-2046 [doi]
• Boosting Classifier CascadesMohammad J. Saberian, Nuno Vasconcelos. 2047-2055 [doi]
• Collaborative Filtering in a Non-Uniform World: Learning with the Weighted Trace NormRuslan Salakhutdinov, Nathan Srebro. 2056-2064 [doi]
• Implicitly Constrained Gaussian Process Regression for Monocular Non-Rigid Pose EstimationMathieu Salzmann, Raquel Urtasun. 2065-2073 [doi]
• Deterministic Single-Pass Algorithm for LDAIssei Sato, Kenichi Kurihara, Hiroshi Nakagawa. 2074-2082 [doi]
• Active Estimation of F-MeasuresChristoph Sawade, Niels Landwehr, Tobias Scheffer. 2083-2091 [doi]
• Trading off Mistakes and Don't-Know PredictionsAmin Sayedi, Morteza Zadimoghaddam, Avrim Blum. 2092-2100 [doi]
• Sparse Inverse Covariance Selection via Alternating Linearization MethodsKatya Scheinberg, Shiqian Ma, Donald Goldfarb. 2101-2109 [doi]
• Spike timing-dependent plasticity as dynamic filterJoscha Schmiedt, Christian Albers, Klaus Pawelzik. 2110-2118 [doi]
• A novel family of non-parametric cumulative based divergences for point processesSohan Seth, Il Memming Park, Austin J. Brockmeier, Mulugeta Semework, John Choi, Joseph Francis, José Carlos Príncipe. 2119-2127 [doi]
• Online Learning in The Manifold of Low-Rank MatricesUri Shalit, Daphna Weinshall, Gal Chechik. 2128-2136 [doi]
• Identifying graph-structured activation patterns in networksJames Sharpnack, Aarti Singh. 2137-2145 [doi]
• A rational decision making framework for inhibitory controlPradeep Shenoy, Rajesh P. N. Rao, Angela J. Yu. 2146-2154 [doi]
• Penalized Principal Component Regression on Graphs for Analysis of SubnetworksAli Shojaie, George Michailidis. 2155-2163 [doi]
• Monte-Carlo Planning in Large POMDPsDavid Silver, Joel Veness. 2164-2172 [doi]
• Sodium entry efficiency during action potentials: A novel single-parameter family of Hodgkin-Huxley modelsAnand Singh, Renaud Jolivet, Pierre J. Magistretti, Bruno Weber. 2173-2180 [doi]
• More data means less inference: A pseudo-max approach to structured learningDavid Sontag, Ofer Meshi, Tommi Jaakkola, Amir Globerson. 2181-2189 [doi]
• Reward Design via Online Gradient AscentJonathan Sorg, Satinder P. Singh, Richard L. Lewis. 2190-2198 [doi]
• Smoothness, Low Noise and Fast RatesNathan Srebro, Karthik Sridharan, Ambuj Tewari. 2199-2207 [doi]
• Efficient Minimization of Decomposable Submodular FunctionsPeter Stobbe, Andreas Krause. 2208-2216 [doi]
• Learning from Logged Implicit Exploration DataAlexander L. Strehl, John Langford, Lihong Li, Sham Kakade. 2217-2225 [doi]
• Layered image motion with explicit occlusions, temporal consistency, and depth orderingDeqing Sun, Erik B. Sudderth, Michael J. Black. 2226-2234 [doi]
• Improving the Asymptotic Performance of Markov Chain Monte-Carlo by Inserting VorticesYi Sun, Faustino J. Gomez, Jürgen Schmidhuber. 2235-2243 [doi]
• Semi-Supervised Learning with Adversarially Missing Label InformationUmar Syed, Ben Taskar. 2244-2252 [doi]
• A Reduction from Apprenticeship Learning to ClassificationUmar Syed, Robert E. Schapire. 2253-2261 [doi]
• Identifying Patients at Risk of Major Adverse Cardiovascular Events Using Symbolic MismatchZeeshan Syed, John V. Guttag. 2262-2270 [doi]
• Switching state space model for simultaneously estimating state transitions and nonstationary firing ratesKen Takiyama, Masato Okada. 2271-2279 [doi]
• Pose-Sensitive Embedding by Nonlinear NCA RegressionGraham W. Taylor, Rob Fergus, George Williams, Ian Spiro, Christoph Bregler. 2280-2288 [doi]
• Fast Large-scale Mixture Modeling with Component-specific Data PartitionsBo Thiesson, Chong Wang. 2289-2297 [doi]
• Policy gradients in linearly-solvable MDPsEmanuel Todorov. 2298-2306 [doi]
• Phoneme Recognition with Large Hierarchical ReservoirsFabian Triefenbach, Azarakhsh Jalalvand, Benjamin Schrauwen, Jean-Pierre Martens. 2307-2315 [doi]
• Exact learning curves for Gaussian process regression on large random graphsMatthew Urry, Peter Sollich. 2316-2324 [doi]
• Worst-case bounds on the quality of max-product fixed-pointsMeritxell Vinyals, Jesús Cerquides, Alessandro Farinelli, Juan A. Rodríguez-Aguilar. 2325-2333 [doi]
• Brain covariance selection: better individual functional connectivity models using population priorGaël Varoquaux, Alexandre Gramfort, Jean-Baptiste Poline, Bertrand Thirion. 2334-2342 [doi]
• Fast detection of multiple change-points shared by many signals using group LARSJean-Philippe Vert, Kevin Bleakley. 2343-2351 [doi]
• Optimal Bayesian Recommendation Sets and Myopically Optimal Choice Query SetsPaolo Viappiani, Craig Boutilier. 2352-2360 [doi]
• Multiple Kernel Learning and the SMO AlgorithmS. V. N. Vishwanathan, Zhaonan Sun, Nawanol Ampornpunt, Manik Varma. 2361-2369 [doi]
• Joint Analysis of Time-Evolving Binary Matrices and Associated DocumentsEric Wang, Dehong Liu, Jorge Silva, David B. Dunson, Lawrence Carin. 2370-2378 [doi]
• Unsupervised Kernel Dimension ReductionMeihong Wang, Fei Sha, Michael I. Jordan. 2379-2387 [doi]
• Multi-View Active Learning in the Non-Realizable CaseWei Wang 0028, Zhi-Hua Zhou. 2388-2396 [doi]
• A Discriminative Latent Model of Image Region and Object Tag CorrespondenceYang Wang 0003, Greg Mori. 2397-2405 [doi]
• Heavy-Tailed Process Priors for Selective ShrinkageFabian L. Wauthier, Michael I. Jordan. 2406-2414 [doi]
• Sidestepping Intractable Inference with Structured Ensemble CascadesDavid Weiss, Benjamin Sapp, Ben Taskar. 2415-2423 [doi]
• The Multidimensional Wisdom of CrowdsPeter Welinder, Steve Branson, Serge Belongie, Pietro Perona. 2424-2432 [doi]
• Interval Estimation for Reinforcement-Learning Algorithms in Continuous-State DomainsMartha White, Adam M. White. 2433-2441 [doi]
• Active Learning Applied to Patient-Adaptive Heartbeat ClassificationJenna Wiens, John V. Guttag. 2442-2450 [doi]
• Probabilistic Inference and Differential PrivacyOliver Williams, Frank McSherry. 2451-2459 [doi]
• Copula ProcessesAndrew Gordon Wilson, Zoubin Ghahramani. 2460-2468 [doi]
• Linear readout from a neural population with partial correlation dataAdrien Wohrer, Ranulfo Romo, Christian K. Machens. 2469-2477 [doi]
• A unified model of short-range and long-range motion perceptionShuang Wu, Xuming He, Hongjing Lu, Alan L. Yuille. 2478-2486 [doi]
• A Log-Domain Implementation of the Diffusion Network in Very Large Scale IntegrationYi-Da Wu, Shi-Jie Lin, Hsin Chen. 2487-2495 [doi]
• Robust PCA via Outlier PursuitHuan Xu, Constantine Caramanis, Sujay Sanghavi. 2496-2504 [doi]
• Distributionally Robust Markov Decision ProcessesHuan Xu, Shie Mannor. 2505-2513 [doi]
• Inference and communication in the game of PasswordYang Xu, Charles Kemp. 2514-2522 [doi]
• Feature Transitions with Saccadic Search: Size, Color, and Orientation Are Not AlikeStella X. Yu. 2523-2531 [doi]
• Relaxed Clipping: A Global Training Method for Robust Regression and ClassificationYaoliang Yu, Min Yang, Linli Xu, Martha White, Dale Schuurmans. 2532-2540 [doi]
• Lower Bounds on Rate of Convergence of Cutting Plane MethodsXinhua Zhang, Ankan Saha, S. V. N. Vishwanathan. 2541-2549 [doi]
• Learning Multiple Tasks with a Sparse Matrix-Normal PenaltyYi Zhang 0010, Jeff G. Schneider. 2550-2558 [doi]
• Probabilistic Multi-Task Feature SelectionYu Zhang, Dit-Yan Yeung, Qian Xu. 2559-2567 [doi]
• Worst-Case Linear Discriminant AnalysisYu Zhang, Dit-Yan Yeung. 2568-2576 [doi]
• Sufficient Conditions for Generating Group Level Sparsity in a Robust Minimax FrameworkHongbo Zhou, Qiang Cheng. 2577-2585 [doi]
• Large Margin Learning of Upstream Scene Understanding ModelsJun Zhu, Li-Jia Li, Fei-Fei Li, Eric P. Xing. 2586-2594 [doi]
• Parallelized Stochastic Gradient DescentMartin Zinkevich, Markus Weimer, Alexander J. Smola, Lihong Li. 2595-2603 [doi]
• A Primal-Dual Algorithm for Group Sparse Regularization with Overlapping GroupsSofia Mosci, Silvia Villa, Alessandro Verri, Lorenzo Rosasco. 2604-2612 [doi]
• Double Q-learningHado van Hasselt. 2613-2621 [doi]
• Getting lost in space: Large sample analysis of the resistance distanceUlrike von Luxburg, Agnes Radl, Matthias Hein. 2622-2630 [doi]