Advances in Neural Information Processing Systems 18: Proceedings of the 2005 Conference (Hardcover)

Yair Weiss, Bernhard Schölkopf, John Platt

  • 出版商: A Bradford Book
  • 出版日期: 2006-05-19
  • 定價: $1,800
  • 售價: 5.0$900
  • 語言: 英文
  • 頁數: 1676
  • 裝訂: Hardcover
  • ISBN: 0262232537
  • ISBN-13: 9780262232531

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The annual Neural Information Processing Systems (NIPS) conference is the flagship meeting on neural computation. It draws a diverse group of attendees--physicists, neuroscientists, mathematicians, statisticians, and computer scientists. The presentations are interdisciplinary, with contributions in algorithms, learning theory, cognitive science, neuroscience, brain imaging, vision, speech and signal processing, reinforcement learning and control, emerging technologies, and applications. Only twenty-five percent of the papers submitted are accepted for presentation at NIPS, so the quality is exceptionally high. This volume contains the papers presented at the December 2005 meeting, held in Vancouver.

Yair Weiss is Senior Lecturer in the School of Computer Science and Engineering at The Hebrew University of Jerusalem.

Bernhard Schölkopf is Professor and Director at the Max Planck Institute for Biological Cybernetics in Tübingen and Program Chair of the 2005 NIPS Conference.

John Platt is a Senior Researcher in the Knowledge Tools Group at Microsoft Research and Publications Chair of the 2005 NIPS Conference.


Table of Contents

Contents v
 Preface xvi
 Donors xvii
 NIPS Foundation xvii
 Committees xviii
 Reviewers xix
 Learning vehicular dynamics, with application to modeling helicopters
Pieter Abbeel, Varun Ganapathi and Andrew Ng 1
 Policy-Gradient Methods for Planning
Douglas Aberdeen 9
 Kernelized Infomax Clustering
Felix Agakov and David Barber 17
 Large-scale biophysical parameter estimation in single neurons via constrained linear regression
Misha Ahrens, Quentin J. M. Huys and Liam Paninski 25
 Maximum Margin Semi-Supervised Learning for Structured Variables
Yasemin Altun, David A. McAllester and Mikhail Belkin 33
 Large scale networks fingerprinting and visualization using the k-core decomposition
J. Ignacio Alvarez-Hamelin, Luca Dall'Asta, Alain Barrat and Alessandro Vespignani 41
 Fast Information Value for Graphical Models
Brigham Anderson and Andrew Moore 51
 A Cortically-Plausible Inverse Problem Solving Method Applied to Recognizing Static and Kinematic 3D Objects
David Arathorn 59
 Combining Graph Laplacians for Semi-Supervised Learning
Andreas Argyriou, Mark Herbster and Massimiliano Pontil 67
 Learning in Silicon: Timing is Everything
Michaël Aupetit and Drew Bagnell 75
 On Local Rewards and Scaling Distributed Reinforcement Learning
Drew Bagnell and Andrew Ng 91
 Bayesian models of human action understanding
Chris Baker, Josh Tenenbaum and Rebecca Saxe 99
 The Curse of Highly Variable Functions for Local Kernel Machines
Yoshua Bengio, Olivier Delalleau and Nicolas Le Roux 107
 Non-Local Manifold Parzen Windows
Yoshua Bengio, Hugo Larochelle and Pascal Vincent 115
 Convex Neural Networks
Yoshua Bengio, Nicolas Le Roux, Pascal Vincent, Olivier Delalleau and Patrice Marcotte 123
 Non-Gaussian Component Analysis: a Semi-parametric Framework for Linear Dimension Reduction
Gilles Blanchard, Masashi Sugiyama, Motoaki Kawanabe, Vladimir Spokoiny and Klaus-Robert Müller 131
 From Weighted Classification to Policy Search
Doron Blatt and Alfred Hero 139
 Correlated Topic Models
David M. Blei and John Lafferty 147
 Saliency Based on Information Maximization
Neil Bruce and John Tsotsos 155
 Active Learning For Identifying Function Threshold Boundaries
Brent Bryan, Jeff Schneider, Robert Nichol, Christopher Miller, Christopher Genovese and Larry Wasserman 163
 Subsequence Kernels for Relation Extraction
Razvan Bunescu and Raymond J. Mooney 171
 Faster Rates in Regression via Active Learning
Rui Castro, Rebecca Willett and Robert Nowak 179
 Gradient Flow Independent Component Analysis in Micropower VLSI
Abdullah Celik, Milutin Stanacevic and Gert Cauwenberghs 187
 Improved risk tail bounds for on-line algorithms
Nicolò Cesa-Bianchi and Claudio Gentile 195
 Layered Dynamic Textures
Antoni Chan and Nuno Vasconcelos 203
 Size Regularized Cut for Data Clustering
Yixin Chen, Ya Zhang and Xiang Ji 211
 Learning from Data of Variable Quality
Koby Crammer, Michael Kearns and Jennifer Wortman 219
 Efficient estimation of hidden state dynamics from spike trains
Márton Danóczy and Richard H. R. Hahnloser 227
 Coarse sample complexity bounds for active learning
Sanjoy Dasgupta 235
 Norepinephrine and Neural Interrupts
Peter Dayan and Angela J. Yu 243
 Fast Krylov Methods fo N-Body Learning
Nando de Freitas, Yang Wang, Maryam Mahdaviani and Dustin Lang 251
 The Forgetron: A Kernel-Based Perceptron on a Fixed Budget
Ofer Dekel, Shai Shalev-Shwartz and Yoram Singer 259
 Data-Driven Online to Batch Conversations
Ofer Dekel and Yoram Singer 267
 Beyond Gaussian Processes: On the Distributions of Infinite Networks
Ricky Der and Daniel Lee 275
 Generalized Nonnegative Matrix Approximations with Bregman
Inderjit S. Dhillon and Suvrit Sra 283
 An Application of Markov Random Fields to Range Sensing
James Diebel and Sebastian Thrun 291
 Transfer Learning for text classification
Chuong Do and Andrew Ng 299
 A Theoretical Analysis of Robust Coding over Noisy Overcomplete
Eizaburo Doi, Doru C. Balcan and Michael S. Lewicki 307
 Optimizing spatio-temporal filters for improving Brain-Computer Interfacing
Guido Dornhege, Benjamin Blankertz, Matthias Krauledat, Florian Losch, Gabriel Curio and Klaus-Robert Müller 315
 Correcting sample selection bias in maximum entropy density estimation
Miroslav Dudík, Robert E. Schapire and Steven Phillips 323
 Searching for Character Models
Jaety Edwards and David Forsyth 331
 Hierarchical Linear/Constant Time SLAM Using Particle Filters for Dense Maps
Austin Eliazar and Parr Ronald 339
 Learning to Control an Octopus Arm with Gaussian Process Temporal Difference Models
Yaakov Engel, Peter Szabo and Dmitry Volkinshtein 347
 Two view learning: SVM-2K, Theory and Practice
Jason D. R. Farquhar, David R. Hardoon, Hongying Meng, John Shawe-Taylor and Sandor Szedmak 355
 Robust design of biological experiments
Patrick Flaherty, Michael Jordan and Adam Arkin 363
 Pattern Recognition from One Example by Chopping
Francois Fleuret and Gilles Blanchard 371
 Mixture Modeling by Affinity Propagation
Brendan J. Frey and Delbert Dueck 379
 Statistical Convergence of Kernel CCA
Kenji Fukumizu, Francis R. Bach and Arthur Gretton 387
 Learning Rankings via Convex Hull Separation
Glenn M. Fung, Romer Rosales and Balaji Krishnapuram 395
 A Connectionist Model for Constructive Modal Reasoning
Artur S. d'Avila Garcez, Luis C. Lamb and Dov Gabbay 403
 Large-Scale Multiclass Transduction
Thomas Gärtner, Quoc V. Le, Simon Burton, Alex Smola and S. V. N. Vishwanathan 411
 Products of "Edge-perts"
Peter Gehler and Max Welling 419
 Fast biped walking with a reflexive controller and real-time policy searching
Tao Geng, Bernd Porr and Florentin Wörgötter 427
 Bayesian Sets
Zoubin Ghahramani and Katherine Heller 435
 Query by Committee Made Real
Ran Gilad-Bachrach, Amir Navot and Naftali Tishby 443
 Metric Learning by Collapsing Classes
Amir Globerson and Sam T. Roweis 451
 Interpolating between types and tokens by estimating power-law generators
Sharon Goldwater, Thomas L. Griffiths and Mark Johnson 459
 A Probabilistic Interpretation of SVMs with an Application to Unbalanced Classification
Yves Grandvalet, Johnny Mariéthoz and Samy Bengio 467
 Infinite latent feature models and the Indian buffet process
Thomas L. Griffiths and Zoubin Ghahramani 475
 Computing the Solution Path for the Regularized Support Vector Regression
Lacey Gunther and Ji Zhu 483
 Hot Coupling: A Particle Approach to Inference and Normalization on Pairwise Undirected Graphs
Firas Hamze and Nando de Freitas 491
 Tensor Subspace Analysis
Xiaofei He, Deng Cai and Partha Niyogi 499
 Laplacian Score for Feature Selection
Xiaofei He, Deng Cai and Partha Niyogi 507
 Inferring Motor Programs from Images of Handwritten Digits
Geoffrey Hinton and Vinod Nair 515
 Response Analysis of Neuronal Population with Synaptic Depression
Wentao Huang, Licheng Jiao, Shan Tan and Maoguo Gong 523
 Non-iterative Estimation with Perturbed Gaussian Markov Processes
Yunsong Huang and B. Keith Jenkins 531
 Learning Cue-Invariant Visual Responses
Jarmo Hurri 539
 Bayesian Surprise Attracts Human Attention
Laurent Itti and Pierre Baldi 547
 Efficient Estimation of OOMs
Herbert Jaeger, Mingjie Zhao and Andreas Kolling 555
 Representing Part-Whole Relationships in Recurent Neural Networks
Viren Jain, Valentin Zhigulin and H. Sebastian Seung 563
 A Probabilistic Approach for Optimizing Spectral Clustering
Rong Jin, Chris Ding and Feng Kang 571
 Walk-Sum Interpretation and Analysis of Gaussian Belief Propagation
Jason Johnson, Dmitry Malioutov and Alan S. Willsky 579
 Using "epitomes" to model genetic diversity: Rational design of HIV vaccine cocktails
Nebojsa Jojic, Vladimir Jojic, Brendan J. Frey, Christopher Meek and David Heckerman 587
 Integrate-and-Fire models with adaptation are good enough
Renaud Jolivet, Alexander Rauch, Hans-Rudolf Lüscher and Wulfram Gerstner 595
 Generalization Error Bounds for Aggregation by Mirror Descent with Averaging
Anatoli Juditsky, Alexander Nazin, Alexandre Tsybakov and Nicolas Vayatis 603
 From Batch to Transductive Online Learning
Sham Kakade and Adam Kalai 611
 Worst-Case Bounds for Gaussian Process Models
Sham Kakade, Matthias Seeger and Dean P. Foster 619
 Hyperparameter and Kernel Learning for Graph Based Semi-Supervised Classification
Ashish Kapoor, Yuan Qi, Hyungil Ahn and Rosalind W. Picard 627
 Is Early Vision Optimized for Extracting Higher-order Dependencies?
Yan Karklin and Michael S. Lewicki 635
 A matching pursuit approach to sparse Gaussian process regression
Sathiya Keerthi and Wei Chu 643
 Benchmarking Non-Parametric Statistical Tests
Mikaela Keller, Samy Bengio and Siew Yeung Wong 651
 Robust Fisher Discriminant Analysis
Seung-Jean Kim, Alessandro Magnani and Stephen Boyd 659
 Measuring Shared Information and Coordinated Activity in Neuronal Networks
Kristina Klinkner, Cosma Shalizi and Marcelo Camperi 667
 Inference with Minimal Communication: a Decision-Theoretic Variational Approach
O. Patrick Kreidl and Alan S. Willsky 675
 Generalization in Clustering with Unobserved Features
Eyal Krupka and Naftali Tishby 683
 Variable KD-Tree Algorithms for Spatial Pattern Search and Discovery
Jeremy Kubica, Joseph Masiero, Andrew Moore, Robert Jedicke and Andrew Connolly 691
 Assessing Approximations for Gaussian Process Classification
Malte Kuss and Carl Edward Rasmussen 699
 Rodeo: Sparse Nonparametric Regression in High Dimensions
John Lafferty and Larry Wasserman 707
 Fixing two weaknesses of the Spectral Method
Kevin Lang 715
 Fusion of Similarity Data in Clustering
Tilman Lange and Joachim M. Buhmann 723
 A PAC-Bayes approach to the Set Covering Machine
Francois Laviolette, Mario Marchand and Mohak Shah 731
 Off-Road Obstacle Avoidance through End-to-End Learning
Yann LeCun, Urs Muller, Jan Ben, Eric Cosatto and Beat Flepp 739
 Dual-Tree Fast Gauss Transforms
Dongryeol Lee, Alexander Gray and Andrew Moore 747
 CMOL CrossNets: Possible Neuromorphic Nanoelectronic Circuits
Jung Hoon Lee, Xiaolong Ma and Konstantin Likharev 755
 A Criterion for the Convergence of Learning with Spike Timing Dependent Plasticity
Robert Legenstein and Wolfgang Maass 763
 Dynamical Synapses Give Rise to a Power-Law Distribution of Neuronal Avalanches
Ann Levina and Michael Herrmann 771
 From Lasso regression to Feature vector machine
Fan Li, Yiming Yang and Eric Xing 779
 Location-based activity recognition
Lin Liao, Dieter Fox and Henry Kautz 787
 Radial Basis Function Network for Multi-task Learning
Xuejun Liao and Lawrence Carin 795
 Asymptotics of Gaussian Regularized Least Squares
Ross Lipert and Ryan Rifkin 803
 Efficient Unsupervised Learning for Localization and Detection in Object Categories
Nicolas Loeff, Himanshu Arora, Alexander Sorokin and David Forsyth 811
 Convergence and Consistency of Regularized Boosting Algorithms with Stationary ß-Mixing Observations
Aurélie Lozano, Sanjeev Kulkarni and Robert E. Schapire 819
 Ideal Observers for Detecting Motion: Correspondence Noise
Hongjing Lu and Alan Yuille 827
 Principles of real-time computing with feedback applied to cortical microcircuit models
Wolfgang Maass, Prashant Joshi and Eduardo D. Sontag 835
 Value Function Approximation with Diffusion Wavelets and Laplacian Eigenfunctions
Sridhar Mahadevan and Mauro Maggioni 843
 Noise and the two-thirds power Law
Uri Maoz, Elon Portugaly, Tamar Flash and Yair Weiss 851
 Modeling Memory Transfer and Saving in Cerebellar Motor Learning
Naoki Masuda and Shun-ichi Amari 859
 An exploration-exploitation model based on norepinepherine and dopamine activity
Samuel McClure, Mark Gilzenrat and Jonathan D. Cohen 867
 Online Discovery and Learning of Predictive State Representations
Peter McCracken and Michael Bowling 875
 An Alternative Infinite Mixture of Gaussian Process Experts
Edward Meeds and Simon Osindero 883
 Unbiased Estimator of Shape Parameter for Spiking Irregularities under Changing Environments
Keiji Miura, Masato Okada and Shun-ichi Amari 891
 Concensus Propagation
Ciamac C. Moallemi and Benjamin Van Roy 899
 Context as Filtering
Daichi Mochihashi and Yuji Matsumoto 907
 Spectral Bounds for Sparse PCA: Exact and Greedy Algorithms
Baback Moghaddam, Yair Weiss and Shai Avidan 915
 Top-Down Control of Visual Attention: A Rational Account
Michael C Mozer, Michael Shettel and Shaun P. Vecera 923
 Rate Distortion Codes in Sensor Networks
Tatsuto Murayama and Peter Davis 931
 Gaussian Processes for Multiuser Detection in CDMA receivers
Juan José Murillo-Fuentes, Sebastian Caro and Fernando Pérez-Cruz 939
 Nested sampling for Potts models
Ian Muray, David MacKay, Zoubin Ghahramani and John Skilling 947
 Diffusion Maps, Spectral Clustering and Eigenfunctions of Fokker-Planck Operators
Boaz Nadler, Stephane Lafon, Ronald Coifman and Ioannis Kevrekidis 955
 Stimulus Evoked Independent Factor Analysis of MEG Data with Large Background Activity
Srikantan Nagarajan, Hagai Attias, Kenneth Hild and Kensuke Sekihara 963
 An Analog Visual Pre-Processing Processor Employing Cyclic Line Access in Only-Nearest-Neighbor-Interconnects Achitecture
Yusuke Nakashita, Yoshio Mita and Tadashi Shibata 971
Mukund Narasimhan, Nebojsa Jojic and Jeff Bilmes 979
 Optimal cue selection strategy
Vidhya Navalpakkam and Laurent Itti 987
 Nearest Neighbor Based Feature Selection for Regression and its Application to Neural Activity
Amir Navot, Lavi Shpigelman, Naftali Tishby and Eilon Vaadia 995
 A Bayesian Spatial Scan Statistic
Daniel B. Neill, Andrew Moore and Gregory F. Cooper 1003
 Divergences, surrogate loss functions and experimental design
AnLong Nguyen, Martin J. Wainwright and Michael Jordan 1011
 How fast to work: Response vigor, motivation and tonic dopamine
Yael Niv, Nathaniel D. Daw and Peter Dayan 1019
 Analyzing Coupled Brain Sources: Distinguishing True from Spurious Interaction
Guido Nolte, Andreas Ziehe, Frank Meinecke and Klaus-Robert Müller 1027
 An Approximate Inference Approach for the PCA Reconstruction Error
Manfred Opper 1035
 Bayesian model learning in human visual perception
Gergo Orban, Jozsef Fiser, Richard Aslin and Máté Lengyel 1043
 Spiking Inputs to a Winner-take-all Network
Matthias Oster and Shih-Chii Liu 1051
 Variational EM Algorithms for Non-Gaussian Latent Variable Models
Jason Palmer, David Wipf, Kenneth Kreutz-Delgado and Bhaskar D. Rao 1059
 Nonparametric inference of prior probabilities from Bayes-optimal behavior
Liam Paninski 1067
 Neuronal Fiber Delineation in Area of Edema from Diffusion Weighted MRI
Ofer Pasternak, Nir Sochen, Nathan Intrator and Yaniv Assaf 1075
 Beyond Pair-Based STDP: a Phenomenological Rule for Spike Triplet and Frequency Effects 1081
 Scaling Laws in Natural Scenes and the Inference of 3D Shape
Jean-Pascal Pfister and Wulfram Gerstner 1089
 Scaling Laws in Natural Scenes and the Inference of 3D Shape
Brian Potetz and Tai Sing Lee 1089
 Off-policy Learning with Options and Recognizers
Richard S. Sutton, Cosmin Paduraru, Anna Koop, Satinder P. Singh and Doina Precup 1097
 Estimation of Intrinsic Dimensionality Using High-Rate Vector Quantization
Maxim Raginsky and Svetlana Lazebnik 1105
 Preconditioner Approximations for Probabilistic Graphical Models
Pradeep Ravikumar and John Lafferty 1113
 Cue Integration for Figure/Ground Labeling
Xiaofeng Ren, Charless Fowlkes and Jitendra Malik 1121
 Generalization to Unseen Cases
Teemu Roos, Peter D. Grünwald, Petri Myllymäki and Henry Tirri 1129
 Visual Encoding with Jittering Eyes
Michele Rucci 1137
 Dynamic Social Network Analysis using Latent Space Models
Purnamrita Sarkar and Andrew Moore 1145
 Logic and MRF Circuitry for Labeling Occluding and Thinline Visual Contours
Eric Saund 1153
 Learning Depth from Single Monocular Images
Ashutosh Saxena, Sung H. Chung and Andrew Ng 1161
 Identifying Distributed Object Representations in Human Extrastriate Visual Cortex
Rory Sayres, David Ress and Kalanit Grill-Spector 1169
 On the Accuracy of Bounded Rationality: How Far from Optimal Is Fast and Frugal?
Michael Schmitt and Laura Martignon 1177
 Fast Online Policy Gradient Learning with SMD Gain Vector Adaptation
Nicol N. Schraudolph, Jin Yu and Douglas Aberdeen 1185
 The Information-Form Data Association Filter
Brad Schumitsch, Sebastian Thrun, Gary Bradski and Kunle Olukotun 1193
 A Bayesian Framework for Tilt Perception and Confidence
Odelia Schwartz, Terrence Sejnowski and Peter Dayan 1201
 Learning Minimum Volume Sets
Clayton Scott and Robert Nowak 1209
 AER Building Blocks for Multi-Layer Multi-Chip Neuromorphic Vision Systems
Rafael Serrano-Gotarredona, Matthias Oster, Patrick Lichtsteiner, Alejandro Linares-Barranco, Rafael Paz-Vicente, Francisco Gómez-Rodríguez, Havard Kolle Riis, Tobias Delbrück, Shih-Chii Liu, Sam Zahnd, Adrian Whatley, Rodney Douglas, Philipp Häfliger, Gabriel Jimenez-Moreno, Antón Civit, Teresa Serrano-Gotarredona, Antonio Acosta-Jiménez and Bernabe Linares-Barranco 1217
 Fast Gaussian Process Regression using KD-Trees
Yirong Shen, Andrew Ng and Matthias Seeger 1225
 Learning Shared Latent Structure for Image Synthesis and Robotic Imitation
Aaron Shon, Keith Grochow, Aaron Hertzmann and Rajesh P. N. Rao 1233
 Selecting Landmark Points for Sparse Manifold Learning
Jorge Silva, Jorge Marques and João Lemos 1241
 Conditional Visual Tracking in Kernel Space
Cristian Sminchisescu, Atul Kanaujia, Zhiguo Li and Dimitri Metaxas 1249
 Sparse Gaussian Processes using Pseudo-inputs
Edward Snelson and Zoubin Ghahramani 1257
 Phase Synchrony Rate for the Recognition of Motor Imagery in Brain-Computer Interface
Le Song, Evian Gordon and Elly Gysels 1265
 A General and Efficient Multiple Kernel Learning Algorithm
Sören Sonnenburg, Gunnar Rätsch and Christin Schäfer 1273
 Prediction and Change Detection
Mark Steyvers and Scott Brown 1281
 Sensory Adaptation within a Bayesian Framework for Perception
Alan Stocker and Eero P. Simoncelli 1289
 Describing Visual Scenes using Transformed Dirichlet Processes
Erik B. Sudderth, Antonio Torralba, William Freeman and Alan S. Willsky 1297
 Active Learning for Misspecified Models
Masashi Sugiyama 1305
 Temporal Abstraction in Temporal-difference Networks
Richard S. Sutton, Eddie Rafols and Anna Koop 1313
 Sequence and Tree Kernels with Statistical Feature Mining
Jun Suzuki and Hideki Isozaki 1321
 Silicon growth cones map silicon retina
Brian Taba and Kwabena Boahen 1329
 Temporally changing synaptic plasticity
Minija Tamosiunaite, Bernd Porr and Florentin Wörgötter 1337
 Structured Prediction via the Extragradient Method
Benjamin Taskar, Simon Lacoste-Julien and Michael Jordan 1345
 Affine Structure From Sound
Sebastian Thrun 1353
 Predicting EMG Data from M1 Neurons with Variational Bayesian Least Squares
Jo-Anne Ting, Aaron D'Souza, Kenji Yamamoto, Toshinori Yoshioka, Donna L. Hoffman, Shinji Kakei, Lauren Sergio, John Kalaska, Mitsuo Kawato, Peter L. Strick and Stefan Schaal 1361
 Generalization error bounds for classifiers trained with interdependent data
Nicolas Usunier, Massih-Reza Amini and Patrick Gallinari 1369
 TD(0) Leads to Better Policies than Approximate Value Iteration
Benjamin Van Roy 1377
 An aVLSI Cricket Ear Model
Andre Van Schaik, Richard Reeve, Craig Jin and Tara Hamilton 1385
 Goal-Based Imitation as Probabilistic Inference over Graphical Models
Deepak Verma and Rajesh P. N. Rao 1393
 Kernels for gene regulatory regions
Jean-Philippe Vert, Robert Thurman and William S. Noble 1401
 Consistency of one-class SVM and related algorithms
Régis Vert and Jean-Philippe Vert 1409
 Multiple Instance Boosting for Object Detection
Paul Viola, John Platt and Cha Zhang 1417
 Estimating the wrong Markov random field: Benefits in the computation-limited setting
Martin J. Wainwright 1425
 Recovery of Jointly Sparse Signals from Few Random Projections
Michael Wakin, Marco Duarte, Shriram Sarvotham, Dror Baron and Richard Baraniuk 1433
 Gaussian Pocess Dynamical Models
Jack Wang, David Fleet and Aaron Hertzmann 1441
 Group and Topic Discovery from Relations and Their Attributes
Xuerui Wang, Natasha Mohanty and Andrew McCallum 1449
 A Bayes Rule for Density Matrices
Manfred K. Warmuth 1457
 Variational Bayesian Stochastic Complexity of Mixture Models
Kazuho Watanabe and Sumio Watanabe 1465
 Distance Metric Learning for Large Margin Nearest Neighbor Classification
Kilian Weinberger, John Blitzer and Lawrence Saul 1473
 Analyzing Auditory Neurons by Learning Distance Functions
Inna Weiner, Tomer Hertz, Israel Nelken and Daphna Weinshall 1481
 Oblivious Equilibrium: A Mean Field Approximation for Large-Scale Dynamic Games
Gabriel Y. Weintraub, C. Lanier Benkard and Benjamin Van Roy 1489
 Active Bidirectional Coupling in a Cochlear Chip
Bo Wen and Kwabena Boahen 1497
 Neural mechanisms of contrast dependent receptive field size in V1
Jim Wielaard and Paul Sajda 1505
 Factorial Switching Kalman Filters for Condition Monitoring in Neonatal Intensive Care
Christopher K. I. Williams, John Quinn and Neil McIntosh 1513
 Comparing the Effects of Different Weight Distributions on Finding Sparse Representations
David Wipf and Bhaskar D. Rao 1521
 Message passing for task redistribution on sparse graphs
K. Y. M. Wong, David Saad and Zhuo Gao 1529
 Modeling Neural Population Spiking Activity with Gibbs Distributions
Frank Wood, Stefan Roth and Michael Block 1537
 Extracting Dynamical Structure Embedded in Neural Activity
Byron Yu, Afsheen Afshar, Gopal Santhanam, Stephen I. Ryu, Krishna V. Shenoy and Maneesh Sahani 1545
 Soft Clustering on Graphs
Kai Yu, Shipeng Yu and Volker Tresp 1553
 Augmented Rescorla-Wagner and Maximum Likelihood Estimation
Alan Yuille 1561
 The Role of Top-down and Bottom-up Processes in Guiding Eye Movements during Visual Search
Gregory Zelinsky, Wei Zhang, Bing Yu, Xin Chen and Dimitris Samaras 1569
 Learning Influence among Interacting Markov Chains
Dong Zhang, Samy Bengio, Deb Roy and Daniel Gatica-Perez 1577
 Learning Multiple Related Tasks using Latent Independent Component Analysis
Jian Zhang, Zoubin Ghahramani and Yiming Yang 1585
 Modeling Neuronal Interactivity using Dynamic Bayesian Networks
Lei Zhang, Dimitris Samaras, Nelly Alia-Klein, Nora Volkow and Rita Goldstein 1593
 Analysis of Spectral Kernel Design based Semi-supervised Learning
Tong Zhang and Rie Ando 1601
 A Computational Model of Eye Movements during Object Class Detection
Wei Zhang, Hyejin Yang, Dimitris Samaras and Gregory Zelinsky 1609
 Separation of Music Signals by Harmonic Structure Modeling
Yun-Gang Zhang and Chang-Shui Zhang 1617
 A Domain Decomposition Method for Fast Manifold Learning
Zhenyue Zhang and Hongyuan Zha 1625
 A Hierarchical Compositional System for Rapid Object Detection
Long Zhu and Alan Yuille 1633
 Cyclic Equilibria in Markov Games
Martin Zinkevich, Amy Greenwald and Michael L. Littman 1641
 On the Convergence of Eigenspacesin Kernel Principal Component Analysis
Laurent Zwald and Gilles Blanchard 1649
 Subject Index 1657
 Author Index 1664