Table of Contents

• Learning vehicular dynamics, with application to modeling helicoptersPieter Abbeel, Varun Ganapathi, Andrew Y. Ng. 1-8 [doi]
• Policy-Gradient Methods for PlanningDouglas Aberdeen. 9-16 [doi]
• Kernelized Infomax ClusteringFelix V. Agakov, David Barber. 17-24 [doi]
• Large-scale biophysical parameter estimation in single neurons via constrained linear regressionMisha Ahrens, Quentin Huys, Liam Paninski. 25-32 [doi]
• Margin Semi-Supervised Learning for Structured VariablesYasemin Altun, David A. McAllester, Mikhail Belkin. 33-40 [doi]
• Large scale networks fingerprinting and visualization using the k-core decompositionJ. Ignacio Alvarez-Hamelin, Luca Dall Asta, Alain Barrat, Alessandro Vespignani. 41-50 [doi]
• Fast Information Value for Graphical ModelsBrigham Anderson, Andrew W. Moore. 51-58 [doi]
• A Cortically-Plausible Inverse Problem Solving Method Applied to Recognizing Static and Kinematic 3D ObjectsDavid Arathorn. 59-66 [doi]
• Combining Graph Laplacians for Semi-Supervised LearningAndreas Argyriou, Mark Herbster, Massimiliano Pontil. 67-74 [doi]
• Learning in Silicon: Timing is EverythingJohn V. Arthur, Kwabena Boahen. 75-82 [doi]
• Learning Topology with the Generative Gaussian Graph and the EM AlgorithmMichaël Aupetit. 83-90 [doi]
• On Local Rewards and Scaling Distributed Reinforcement LearningJ. Andrew Bagnell, Andrew Y. Ng. 91-98 [doi]
• Bayesian models of human action understandingChris Baker, Joshua B. Tenenbaum, Rebecca Saxe. 99-106 [doi]
• The Curse of Highly Variable Functions for Local Kernel MachinesYoshua Bengio, Olivier Delalleau, Nicolas Le Roux. 107-114 [doi]
• Non-Local Manifold Parzen WindowsYoshua Bengio, Hugo Larochelle, Pascal Vincent. 115-122 [doi]
• Convex Neural NetworksYoshua Bengio, Nicolas Le Roux, Pascal Vincent, Olivier Delalleau, Patrice Marcotte. 123-130 [doi]
• Non-Gaussian Component Analysis: a Semi-parametric Framework for Linear Dimension ReductionGilles Blanchard, Masashi Sugiyama, Motoaki Kawanabe, Vladimir Spokoiny, Klaus-Robert Müller. 131-138 [doi]
• From Weighted Classification to Policy SearchDoron Blatt, Alfred O. Hero. 139-146 [doi]
• Correlated Topic ModelsDavid M. Blei, John D. Lafferty. 147-154 [doi]
• Saliency Based on Information MaximizationNeil D. B. Bruce, John K. Tsotsos. 155-162 [doi]
• Active Learning For Identifying Function Threshold BoundariesBrent Bryan, Jeff G. Schneider, Robert Nichol, Christopher Miller, Christopher Genovese, Larry A. Wasserman. 163-170 [doi]
• Subsequence Kernels for Relation ExtractionRazvan C. Bunescu, Raymond J. Mooney. 171-178 [doi]
• Faster Rates in Regression via Active LearningRui Castro, Rebecca Willett, Robert Nowak. 179-186 [doi]
• Gradient Flow Independent Component Analysis in Micropower VLSIAbdullah Celik, Milutin Stanacevic, Gert Cauwenberghs. 187-194 [doi]
• Improved risk tail bounds for on-line algorithmsNicolò Cesa-Bianchi, Claudio Gentile. 195-202 [doi]
• Layered Dynamic TexturesAntoni B. Chan, Nuno Vasconcelos. 203-210 [doi]
• Size Regularized Cut for Data ClusteringYixin Chen, Ya Zhang, Xiang Ji. 211-218 [doi]
• Learning from Data of Variable QualityKoby Crammer, Michael S. Kearns, Jennifer Wortman. 219-226 [doi]
• Efficient estimation of hidden state dynamics from spike trainsMárton Danóczy, Richard H. R. Hahnloser. 227-234 [doi]
• Coarse sample complexity bounds for active learningSanjoy Dasgupta. 235-242 [doi]
• Norepinephrine and Neural InterruptsPeter Dayan, Angela J. Yu. 243-250 [doi]
• Fast Krylov Methods for N-Body LearningNando de Freitas, Yang Wang, Maryam Mahdaviani, Dustin Lang. 251-258 [doi]
• The Forgetron: A Kernel-Based Perceptron on a Fixed BudgetOfer Dekel, Shai Shalev-Shwartz, Yoram Singer. 259-266 [doi]
• Data-Driven Online to Batch ConversionsOfer Dekel, Yoram Singer. 267-274 [doi]
• Beyond Gaussian Processes: On the Distributions of Infinite NetworksRicky Der, Daniel Lee. 275-282 [doi]
• Generalized Nonnegative Matrix Approximations with Bregman DivergencesInderjit S. Dhillon, Suvrit Sra. 283-290 [doi]
• An Application of Markov Random Fields to Range SensingJames Diebel, Sebastian Thrun. 291-298 [doi]
• Transfer learning for text classificationChuong B. Do, Andrew Y. Ng. 299-306 [doi]
• A Theoretical Analysis of Robust Coding over Noisy Overcomplete ChannelsEizaburo Doi, Doru-Cristian Balcan, Michael S. Lewicki. 307-314 [doi]
• Optimizing spatio-temporal filters for improving Brain-Computer InterfacingGuido Dornhege, Benjamin Blankertz, Matthias Krauledat, Florian Losch, Gabriel Curio, Klaus-Robert Müller. 315-322 [doi]
• Correcting sample selection bias in maximum entropy density estimationMiroslav Dudík, Robert E. Schapire, Steven J. Phillips. 323-330 [doi]
• Searching for Character ModelsJaety Edwards, David A. Forsyth. 331-338 [doi]
• Hierarchical Linear/Constant Time SLAM Using Particle Filters for Dense MapsAustin I. Eliazar, Ronald Parr. 339-346 [doi]
• Learning to Control an Octopus Arm with Gaussian Process Temporal Difference MethodsYaakov Engel, Peter Szabó, Dmitry Volkinshtein. 347-354 [doi]
• Two view learning: SVM-2K, Theory and PracticeJason D. R. Farquhar, David R. Hardoon, Hongying Meng, John Shawe-Taylor, Sándor Szedmák. 355-362 [doi]
• Robust design of biological experimentsPatrick Flaherty, Michael I. Jordan, Adam P. Arkin. 363-370 [doi]
• Pattern Recognition from One Example by ChoppingFrançois Fleuret, Gilles Blanchard. 371-378 [doi]
• Mixture Modeling by Affinity PropagationBrendan J. Frey, Delbert Dueck. 379-386 [doi]
• Statistical Convergence of Kernel CCAKenji Fukumizu, Francis R. Bach, Arthur Gretton. 387-394 [doi]
• Learning Rankings via Convex Hull SeparationGlenn Fung, Rómer Rosales, Balaji Krishnapuram. 395-402 [doi]
• A Connectionist Model for Constructive Modal ReasoningArtur S. d Avila Garcez, Luís C. Lamb, Dov M. Gabbay. 403-410 [doi]
• Large-Scale Multiclass TransductionThomas Gärtner, Quoc V. Le, Simon Burton, Alex J. Smola, S. V. N. Vishwanathan. 411-418 [doi]
• Products of Edge-pertsPeter V. Gehler, Max Welling. 419-426 [doi]
• Fast biped walking with a reflexive controller and real-time policy searchingTao Geng, Bernd Porr, Florentin Wörgötter. 427-434 [doi]
• Bayesian SetsZoubin Ghahramani, Katherine A. Heller. 435-442 [doi]
• Query by Committee Made RealRan Gilad-Bachrach, Amir Navot, Naftali Tishby. 443-450 [doi]
• Metric Learning by Collapsing ClassesAmir Globerson, Sam T. Roweis. 451-458 [doi]
• Interpolating between types and tokens by estimating power-law generatorsSharon Goldwater, Tom Griffiths, Mark Johnson. 459-466 [doi]
• A Probabilistic Interpretation of SVMs with an Application to Unbalanced ClassificationYves Grandvalet, Johnny Mariéthoz, Samy Bengio. 467-474 [doi]
• Infinite latent feature models and the Indian buffet processTom Griffiths, Zoubin Ghahramani. 475-482 [doi]
• Computing the Solution Path for the Regularized Support Vector RegressionLacey Gunter, Ji Zhu. 483-490 [doi]
• Hot Coupling: A Particle Approach to Inference and Normalization on Pairwise Undirected GraphsFiras Hamze, Nando de Freitas. 491-498 [doi]
• Tensor Subspace AnalysisXiaofei He, Deng Cai, Partha Niyogi. 499-506 [doi]
• Laplacian Score for Feature SelectionXiaofei He, Deng Cai, Partha Niyogi. 507-514 [doi]
• Inferring Motor Programs from Images of Handwritten DigitsGeoffrey E. Hinton, Vinod Nair. 515-522 [doi]
• Response Analysis of Neuronal Population with Synaptic DepressionWentao Huang, Licheng Jiao, Tan Shan, Maoguo Gong. 523-530 [doi]
• Non-iterative Estimation with Perturbed Gaussian Markov ProcessesYunsong Huang, B. Keith Jenkins. 531-538 [doi]
• Learning Cue-Invariant Visual ResponsesJarmo Hurri. 539-546 [doi]
• Bayesian Surprise Attracts Human AttentionLaurent Itti, Pierre Baldi. 547-554 [doi]
• Efficient Estimation of OOMsHerbert Jaeger, Mingjie Zhao, Andreas Kolling. 555-562 [doi]
• Representing Part-Whole Relationships in Recurrent Neural NetworksViren Jain, Valentin P. Zhigulin, H. Sebastian Seung. 563-570 [doi]
• A Probabilistic Approach for Optimizing Spectral ClusteringRong Jin, Chris H. Q. Ding, Feng Kang. 571-578 [doi]
• Walk-Sum Interpretation and Analysis of Gaussian Belief PropagationJason K. Johnson, Dmitry M. Malioutov, Alan S. Willsky. 579-586 [doi]
• Using epitomes to model genetic diversity: Rational design of HIV vaccinesNebojsa Jojic, Vladimir Jojic, Brendan J. Frey, Christopher Meek, David Heckerman. 587-594 [doi]
• Integrate-and-Fire models with adaptation are good enoughRenaud Jolivet, Alexander Rauch, Hans-Rudolf Lüscher, Wulfram Gerstner. 595-602 [doi]
• Generalization Error Bounds for Aggregation by Mirror Descent with AveragingAnatoli Juditsky, Alexander V. Nazin, Alexandre B. Tsybakov, Nicolas Vayatis. 603-610 [doi]
• From Batch to Transductive Online LearningSham M. Kakade, Adam Kalai. 611-618 [doi]
• Worst-Case Bounds for Gaussian Process ModelsSham M. Kakade, Matthias Seeger, Dean P. Foster. 619-626 [doi]
• Hyperparameter and Kernel Learning for Graph Based Semi-Supervised ClassificationAshish Kapoor, Yuan (Alan) Qi, Hyungil Ahn, Rosalind W. Picard. 627-634 [doi]
• Is Early Vision Optimized for Extracting Higher-order Dependencies?Yan Karklin, Michael S. Lewicki. 635-642 [doi]
• A matching pursuit approach to sparse Gaussian process regressionS. Sathiya Keerthi, Wei Chu. 643-650 [doi]
• Benchmarking Non-Parametric Statistical TestsMikaela Keller, Samy Bengio, Siew Yeung Wong. 651-658 [doi]
• Robust Fisher Discriminant AnalysisSeung-Jean Kim, Alessandro Magnani, Stephen P. Boyd. 659-666 [doi]
• Measuring Shared Information and Coordinated Activity in Neuronal NetworksKristina Klinkner, Cosma Rohilla Shalizi, Marcelo Camperi. 667-674 [doi]
• Inference with Minimal Communication: a Decision-Theoretic Variational ApproachO. Patrick Kreidl, Alan S. Willsky. 675-682 [doi]
• Generalization in Clustering with Unobserved FeaturesEyal Krupka, Naftali Tishby. 683-690 [doi]
• Variable KD-Tree Algorithms for Spatial Pattern Search and DiscoveryJeremy Kubica, Joseph Masiero, Andrew W. Moore, Robert Jedicke, Andrew Connolly. 691-698 [doi]
• Assessing Approximations for Gaussian Process ClassificationMalte Kuss, Carl Edward Rasmussen. 699-706 [doi]
• Rodeo: Sparse Nonparametric Regression in High DimensionsJohn D. Lafferty, Larry A. Wasserman. 707-714 [doi]
• Fixing two weaknesses of the Spectral MethodKevin Lang. 715-722 [doi]
• Fusion of Similarity Data in ClusteringTilman Lange, Joachim M. Buhmann. 723-730 [doi]
• A PAC-Bayes approach to the Set Covering MachineFrançois Laviolette, Mario Marchand, Mohak Shah. 731-738 [doi]
• Off-Road Obstacle Avoidance through End-to-End LearningYann LeCun, Urs Muller, Jan Ben, Eric Cosatto, Beat Flepp. 739-746 [doi]
• Dual-Tree Fast Gauss TransformsDongryeol Lee, Alexander G. Gray, Andrew W. Moore. 747-754 [doi]
• CMOL CrossNets: Possible Neuromorphic Nanoelectronic CircuitsJung Hoon Lee, Xiaolong Ma, Konstantin Likharev. 755-762 [doi]
• A Criterion for the Convergence of Learning with Spike Timing Dependent PlasticityRobert A. Legenstein, Wolfgang Maass. 763-770 [doi]
• Dynamical Synapses Give Rise to a Power-Law Distribution of Neuronal AvalanchesAnna Levina, J. Michael Herrmann, Theo Geisel. 771-778 [doi]
• From Lasso regression to Feature vector machineFan Li, Yiming Yang, Eric P. Xing. 779-786 [doi]
• Location-based activity recognitionLin Liao, Dieter Fox, Henry A. Kautz. 787-794 [doi]
• Radial Basis Function Network for Multi-task LearningXuejun Liao, Lawrence Carin. 792-802 [doi]
• Asymptotics of Gaussian Regularized Least SquaresRoss A. Lippert, Ryan M. Rifkin. 803-810 [doi]
• Efficient Unsupervised Learning for Localization and Detection in Object CategoriesNicolas Loeff, Himanshu Arora, Alexander Sorokin, David A. Forsyth. 811-818 [doi]
• Convergence and Consistency of Regularized Boosting Algorithms with Stationary B-Mixing ObservationsAurelie C. Lozano, Sanjeev R. Kulkarni, Robert E. Schapire. 819-826 [doi]
• Ideal Observers for Detecting Motion: Correspondence NoiseHongjing Lu, Alan L. Yuille. 827-834 [doi]
• Principles of real-time computing with feedback applied to cortical microcircuit modelsWolfgang Maass, Prashant Joshi, Eduardo D. Sontag. 835-842 [doi]
• Value Function Approximation with Diffusion Wavelets and Laplacian EigenfunctionsSridhar Mahadevan, Mauro Maggioni. 843-850 [doi]
• Noise and the two-thirds power LawUri Maoz, Elon Portugaly, Tamar Flash, Yair Weiss. 851-858 [doi]
• Modeling Memory Transfer and Saving in Cerebellar Motor LearningNaoki Masuda, Shun-ichi Amari. 859-866 [doi]
• An exploration-exploitation model based on norepinepherine and dopamine activitySamuel McClure, Mark S. Gilzenrat, Jonathan D. Cohen. 867-874 [doi]
• Online Discovery and Learning of Predictive State RepresentationsPeter McCracken, Michael H. Bowling. 875-882 [doi]
• An Alternative Infinite Mixture Of Gaussian Process ExpertsEdward Meeds, Simon Osindero. 883-890 [doi]
• Unbiased Estimator of Shape Parameter for Spiking Irregularities under Changing EnvironmentsKeiji Miura, Masato Okada, Shun-ichi Amari. 891-898 [doi]
• Consensus PropagationCiamac Cyrus Moallemi, Benjamin Van Roy. 899-906 [doi]
• Context as FilteringDaichi Mochihashi, Yuji Matsumoto. 907-914 [doi]
• Spectral Bounds for Sparse PCA: Exact and Greedy AlgorithmsBaback Moghaddam, Yair Weiss, Shai Avidan. 915-922 [doi]
• Top-Down Control of Visual Attention: A Rational AccountMichael Mozer, Michael Shettel, Shaun Vecera. 923-930 [doi]
• Rate Distortion Codes in Sensor NetworksTatsuto Murayama, Peter Davis. 931-938 [doi]
• Gaussian Processes for Multiuser Detection in CDMA receiversJuan José Murillo-Fuentes, Sebatian Caro, Fernando Pérez-Cruz. 939-946 [doi]
• Nested sampling for Potts modelsIain Murray, David J. C. MacKay, Zoubin Ghahramani, John Skilling. 947-954 [doi]
• Diffusion Maps, Spectral Clustering and Eigenfunctions of Fokker-Planck OperatorsBoaz Nadler, Stephane Lafon, Ronald R. Coifman, Ioannis G. Kevrekidis. 955-962 [doi]
• Stimulus Evoked Independent Factor Analysis of MEG Data with Large Background ActivitySrikantan S. Nagarajan, Hagai Attias, Kenneth E. Hild II, Kensuke Sekihara. 963-970 [doi]
• An Analog Visual Pre-Processing ProcessorYusuke Nakashita, Yoshio Mita, Tadashi Shibata. 971-978 [doi]
• Q-ClusteringMukund Narasimhan, Nebojsa Jojic, Jeff Bilmes. 979-986 [doi]
• Optimal cue selection strategyVidhya Navalpakkam, Laurent Itti. 987-994 [doi]
• Nearest Neighbor Based Feature Selection for Regression and its Application to Neural ActivityAmir Navot, Lavi Shpigelman, Naftali Tishby, Eilon Vaadia. 996-1002 [doi]
• A Bayesian Spatial Scan StatisticDaniel B. Neill, Andrew W. Moore, Gregory F. Cooper. 1003-1010 [doi]
• Divergences, surrogate loss functions and experimental designXuanLong Nguyen, Martin J. Wainwright, Michael I. Jordan. 1011-1018 [doi]
• How fast to work: Response vigor, motivation and tonic dopamineYael Niv, Nathaniel D. Daw, Peter Dayan. 1019-1026 [doi]
• Analyzing Coupled Brain Sources: Distinguishing True from Spurious InteractionGuido Nolte, Andreas Ziehe, Frank C. Meinecke, Klaus-Robert Müller. 1027-1034 [doi]
• An Approximate Inference Approach for the PCA Reconstruction ErrorManfred Opper. 1035-1042 [doi]
• Bayesian model learning in human visual perceptionGergo Orbán, József Fiser, Richard N. Aslin, Máté Lengyel. 1043-1050 [doi]
• Spiking Inputs to a Winner-take-all NetworkMatthias Oster, Shih-Chii Liu. 1051-1058 [doi]
• Variational EM Algorithms for Non-Gaussian Latent Variable ModelsJason A. Palmer, David P. Wipf, Kenneth Kreutz-Delgado, Bhaskar D. Rao. 1059-1066 [doi]
• Nonparametric inference of prior probabilities from Bayes-optimal behaviorLiam Paninski. 1067-1074 [doi]
• Neuronal Fiber Delineation in Area of Edema from Diffusion Weighted MRIOfer Pasternak, Nir A. Sochen, Nathan Intrator, Yaniv Assaf. 1075-1080 [doi]
• Beyond Pair-Based STDP: a Phenomenological Rule for Spike Triplet and Frequency EffectsJean-Pascal Pfister, Wulfram Gerstner. 1081-1088 [doi]
• Scaling Laws in Natural Scenes and the Inference of 3D ShapeBrian Potetz, Tai Sing Lee. 1089-1096 [doi]
• Off-policy Learning with Options and RecognizersDoina Precup, Richard S. Sutton, Cosmin Paduraru, Anna Koop, Satinder P. Singh. 1097-1104 [doi]
• Estimation of Intrinsic Dimensionality Using High-Rate Vector QuantizationMaxim Raginsky, Svetlana Lazebnik. 1105-1112 [doi]
• Preconditioner Approximations for Probabilistic Graphical ModelsPradeep D. Ravikumar, John D. Lafferty. 1113-1120 [doi]
• Cue Integration for Figure/Ground LabelingXiaofeng Ren, Charless Fowlkes, Jitendra Malik. 1121-1128 [doi]
• Generalization to Unseen CasesTeemu Roos, Peter Grünwald, Petri Myllymäki, Henry Tirri. 1129-1136 [doi]
• Visual Encoding with Jittering EyesMichele Rucci. 1137-1144 [doi]
• Dynamic Social Network Analysis using Latent Space ModelsPurnamrita Sarkar, Andrew W. Moore. 1145-1152 [doi]
• Logic and MRF Circuitry for Labeling Occluding and Thinline Visual ContoursEric Saund. 1153-1159 [doi]
• Learning Depth from Single Monocular ImagesAshutosh Saxena, Sung H. Chung, Andrew Y. Ng. 1161-1168 [doi]
• Identifying Distributed Object Representations in Human Extrastriate Visual CortexRory Sayres, David Ress, Kalanit Grill Spector. 1169-1176 [doi]
• On the Accuracy of Bounded Rationality: How Far from Optimal Is Fast and Frugal?Michael Schmitt, Laura Martignon. 1177-1184 [doi]
• Fast Online Policy Gradient Learning with SMD Gain Vector AdaptationNicol N. Schraudolph, Douglas Aberdeen, Jin Yu. 1185-1192 [doi]
• The Information-Form Data Association FilterBrad Schumitsch, Sebastian Thrun, Gary R. Bradski, Kunle Olukotun. 1193-1200 [doi]
• A Bayesian Framework for Tilt Perception and ConfidenceOdelia Schwartz, Terrence J. Sejnowski, Peter Dayan. 1201-1208 [doi]
• Learning Minimum Volume SetsClayton Scott, Robert D. Nowak. 1209-1216 [doi]
• AER Building Blocks for Multi-Layer Multi-Chip Neuromorphic Vision SystemsRafael Serrano-Gotarredona, Matthias Oster, Patrick Lichtsteiner, Alejandro Linares-Barranco, Rafael Paz-Vicente, Francisco Gomez-Rodriguez, Håvard Kolle Riis, Tobi Delbrück, Shih-Chii Liu, S. Zahnd, Adrian M. Whatley, Rodney J. Douglas, Philipp Häfliger, Gabriel Jiménez-Moreno, Antón Civit, Teresa Serrano-Gotarredona, Antonio Acosta-Jimenez, Bernabé Linares-Barranco. 1217-1224 [doi]
• Fast Gaussian Process Regression using KD-TreesYirong Shen, Andrew Y. Ng, Matthias Seeger. 1225-1232 [doi]
• Learning Shared Latent Structure for Image Synthesis and Robotic ImitationAaron P. Shon, Keith Grochow, Aaron Hertzmann, Rajesh P. N. Rao. 1233-1240 [doi]
• Selecting Landmark Points for Sparse Manifold LearningJorge Silva, Jorge S. Marques, João Miranda Lemos. 1241-1248 [doi]
• Conditional Visual Tracking in Kernel SpaceCristian Sminchisescu, Atul Kanaujia, Zhiguo Li, Dimitris N. Metaxas. 1249-1256 [doi]
• Sparse Gaussian Processes using Pseudo-inputsEdward Snelson, Zoubin Ghahramani. 1257-1264 [doi]
• Phase Synchrony Rate for the Recognition of Motor Imagery in Brain-Computer InterfaceLe Song, Evian Gordon, Elly Gysels. 1265-1272 [doi]
• A General and Efficient Multiple Kernel Learning AlgorithmSören Sonnenburg, Gunnar Rätsch, Christin Schäfer. 1273-1280 [doi]
• Prediction and Change DetectionMark Steyvers, Scott Brown. 1281-1288 [doi]
• Sensory Adaptation within a Bayesian Framework for PerceptionAlan Stocker, Eero P. Simoncelli. 1289-1296 [doi]
• Describing Visual Scenes using Transformed Dirichlet ProcessesErik B. Sudderth, Antonio B. Torralba, William T. Freeman, Alan S. Willsky. 1297-1304 [doi]
• Active Learning for Misspecified ModelsMasashi Sugiyama. 1305-1312 [doi]
• Temporal Abstraction in Temporal-difference NetworksRichard S. Sutton, Eddie J. Rafols, Anna Koop. 1313-1320 [doi]
• Sequence and Tree Kernels with Statistical Feature MiningJun Suzuki, Hideki Isozaki. 1321-1328 [doi]
• Silicon growth cones map silicon retinaBrian Taba, Kwabena Boahen. 1329-1336 [doi]
• Temporally changing synaptic plasticityMinija Tamosiunaite, Bernd Porr, Florentin Wörgötter. 1337-1344 [doi]
• Structured Prediction via the Extragradient MethodBenjamin Taskar, Simon Lacoste-Julien, Michael I. Jordan. 1345-1352 [doi]
• Affine Structure From SoundSebastian Thrun. 1353-1360 [doi]
• Predicting EMG Data from M1 Neurons with Variational Bayesian Least SquaresJo-Anne Ting, Aaron D Souza, Kenji Yamamoto, Toshinori Yoshioka, Donna L. Hoffman, Lauren Sergio, Shinji Kakei, John Kalaska, Mitsuo Kawato, Peter Strick, Stefan Schaal. 1361-1368 [doi]
• Generalization error bounds for classifiers trained with interdependent dataNicolas Usunier, Massih-Reza Amini, Patrick Gallinari. 1369-1376 [doi]
• TD(0) Leads to Better Policies than Approximate Value IterationBenjamin Van Roy. 1377-1384 [doi]
• An aVLSI Cricket Ear ModelAndré van Schaik, Richard Reeve, Craig T. Jin, Tara Julia Hamilton. 1385-1392 [doi]
• Goal-Based Imitation as Probabilistic Inference over Graphical ModelsDeepak Verma, Rajesh P. N. Rao. 1393-1400 [doi]
• Kernels for gene regulatory regionsJean-Philippe Vert, Robert Thurman, William Stafford Noble. 1401-1408 [doi]
• Consistency of one-class SVM and related algorithmsRégis Vert, Jean-Philippe Vert. 1409-1416 [doi]
• Multiple Instance Boosting for Object DetectionPaul A. Viola, John C. Platt, Cha Zhang. 1417-1424 [doi]
• Estimating the wrong Markov random field: Benefits in the computation-limited settingMartin J. Wainwright. 1425-1432 [doi]
• Recovery of Jointly Sparse Signals from Few Random ProjectionsMichael B. Wakin, Marco F. Duarte, Shriram Sarvotham, Dror Baron, Richard G. Baraniuk. 1433-1440 [doi]
• Gaussian Process Dynamical ModelsJack M. Wang, David J. Fleet, Aaron Hertzmann. 1441-1448 [doi]
• Group and Topic Discovery from Relations and Their AttributesXuerui Wang, Natasha Mohanty, Andrew McCallum. 1449-1456 [doi]
• A Bayes Rule for Density MatricesManfred K. Warmuth. 1457-1464 [doi]
• Variational Bayesian Stochastic Complexity of Mixture ModelsKazuho Watanabe, Sumio Watanabe. 1465-1472 [doi]
• Distance Metric Learning for Large Margin Nearest Neighbor ClassificationKilian Q. Weinberger, John Blitzer, Lawrence K. Saul. 1473-1480 [doi]
• Analyzing Auditory Neurons by Learning Distance FunctionsInna Weiner, Tomer Hertz, Israel Nelken, Daphna Weinshall. 1481-1488 [doi]
• Oblivious Equilibrium: A Mean Field Approximation for Large-Scale Dynamic GamesGabriel Y. Weintraub, C. Lanier Benkard, Benjamin Van Roy. 1489-1496 [doi]
• Active Bidirectional Coupling in a Cochlear ChipBo Wen, Kwabena Boahen. 1497-1504 [doi]
• Neural mechanisms of contrast dependent receptive field size in V1Jim Wielaard, Paul Sajda. 1505-1512 [doi]
• Factorial Switching Kalman Filters for Condition Monitoring in Neonatal Intensive CareChristopher K. I. Williams, John A. Quinn, Neil McIntosh. 1513-1520 [doi]
• Comparing the Effects of Different Weight Distributions on Finding Sparse RepresentationsDavid P. Wipf, Bhaskar D. Rao. 1521-1528 [doi]
• Message passing for task redistribution on sparse graphsK. Y. Michael Wong, David Saad, Zhuo Gao. 1529-1536 [doi]
• Modeling Neural Population Spiking Activity with Gibbs DistributionsFrank Wood, Stefan Roth, Michael J. Black. 1537-1544 [doi]
• Extracting Dynamical Structure Embedded in Neural ActivityByron M. Yu, Afsheen Afshar, Gopal Santhanam, Stephen I. Ryu, Krishna V. Shenoy, Maneesh Sahani. 1545-1552 [doi]
• Soft Clustering on GraphsShipeng Yu, Kai Yu, Volker Tresp. 1553-1560 [doi]
• Augmented Rescorla-Wagner and Maximum Likelihood EstimationAlan L. Yuille. 1561-1568 [doi]
• The Role of Top-down and Bottom-up Processes in Guiding Eye Movements during Visual SearchGregory J. Zelinsky, Wei Zhang 0002, Bing Yu, Xin Chen, Dimitris Samaras. 1569-1576 [doi]
• Learning Influence among Interacting Markov ChainsDong Zhang, Daniel Gatica-Perez, Samy Bengio, Deb Roy. 1577-1584 [doi]
• Learning Multiple Related Tasks using Latent Independent Component AnalysisJian Zhang, Zoubin Ghahramani, Yiming Yang. 1585-1592 [doi]
• Modeling Neuronal Interactivity using Dynamic Bayesian NetworksLei Zhang 0002, Dimitris Samaras, Nelly Alia-Klein, Nora D. Volkow, Rita Goldstein. 1593-1600 [doi]
• Analysis of Spectral Kernel Design based Semi-supervised LearningTong Zhang, Rie Kubota Ando. 1601-1608 [doi]
• A Computational Model of Eye Movements during Object Class DetectionWei Zhang 0002, Hyejin Yang, Dimitris Samaras, Gregory J. Zelinsky. 1609-1616 [doi]
• Separation of Music Signals by Harmonic Structure ModelingYungang Zhang, Changshui Zhang. 1617-1624 [doi]
• A Domain Decomposition Method for Fast Manifold LearningZhenyue Zhang, Hongyuan Zha. 1625-1632 [doi]
• A Hierarchical Compositional System for Rapid Object DetectionLong Zhu, Alan L. Yuille. 1633-1640 [doi]
• Cyclic Equilibria in Markov GamesMartin Zinkevich, Amy R. Greenwald, Michael L. Littman. 1641-1648 [doi]
• On the Convergence of Eigenspaces in Kernel Principal Component AnalysisLaurent Zwald, Gilles Blanchard. 1649-1656 [doi]