Recognizing Evoked Potentials in a Virtual Environment,
Jessica D. Bayliss and Dana H. Ballard 
 3 

A Neurodynamical Approach to Visual Attention,
 Gustavo Deco and Josef Zihl. 
10 

Effects of Spatial and Temporal Contiguity on the Acquisition of Spatial Information, 
Thea B. Ghiselli-Crippa and Paul W. Munro 
 17 

Acquisition in Autoshaping,
 Sham Kakade and Peter Dayan 
 24 

Robust Recognition of Noisy and Superimposed Patterns via Selective Attention, 
Soo-Young Lee and Michael C. Mozer 
 31 

Perceptual Organization Based on Temporal Dynamics,
Xiuwen Liu and DeLiang L. Wang 
 38 

Information Factorization in Connectionist Models of Perception,
Javier R. Movellan and James L. McClelland 
 45 

Graded GrammaticaIity in Prediction FractaI Machines,
Shan Parfitt, Peter Tifio and Georg Dorffner 
 52 

Rules and Similarity in Concept Learning,
 Joshua B. Tenenbaum 
 59 

Evolving Learnable Languages,
 Bradley Tonkes, Alan Blair and Janet Wiles 
 66 

Learning Statistically Neutral Tasks without Expert Guidance,
Ton Weijters, Antal van den Bosch and Eric Postma 
 73 

A Generative Model for Attractor Dynamics,
Richard S. Zemel and Michael C. Mozer 
 80 

Recurrent Cortical Competition: Strengthen or Weaken?,
Peter Adorjfin, Lars Schwabe, Christian Piepenbrock and Klaus Obermayer 
 89

Effective Learning Requires NeuronaI Remodeling of Hebbian Synapses,
Gal Chechik, Isaac Meilijson and Eytan Ruppin 
 96

Wiring Optimization in the Brain,
 Dmitri B. Chklovskii and Charles F. Stevens 
 103

Optimal Sizes of Dendritic and AxonaI Arbors,
 Dmitri B. Chklovskii 
 108

Neural Representation of Multi-Dimensional Stimuli,
Christian W. Eurich, Stefan D. Wilke and Helmut Schwegler 
 115 

Spiking Boltzmann Machines,
 Geoffrey E. Hinton and Andrew D. Brown 
 122 

Distributed Synchrony of Spiking Neurons in a Hebbian Ceil Assembly,
David Horn, Nir Levy, Isaac Meilijson and Eytan Ruppin 
 129 

Can V1 Mechanisms Account for Figure-Ground and Medial Axis Effects ?,
Zhaoping Li 
 136 

Channel Noise in Excitable Neural Membranes,
Amit Manwani, Peter N. Steinmetz and Christof Koch 
 143 

LTD Facilitates Learning in a Noisy Environment,
Paul W. Munro and Gerardina Hernandez 
 150 

Memory Capacity of Linear vs. Nonlinear Models of Dendritic Integration,
Panayiota Poirazi and Bartlett W. Mel 
 157 

Predictive Sequence Learning in Recurrent Neocortical Circuits,
Rajesh P. N. Rao and Terrence J. Sejnowski 
 164 

A Recurrent Model of the Interaction Between Prefrontal and lnferotemporal  Cortex in Delay Tasks,
 Alfonso Renart, Nestor Parga and Edmund T. Rolls 
 171 

Information Capacity and Robustness of Stochastic Neuron Models, 
Elad Schneidman, Idan Segev and Naftali Tishby 
 178

An MEG Study of Response Latency and Variability in the Human Visual System During a Visual-Motor Integration Task,
 Akaysha C. Tang, Barak A. Pearlmutter, Tim A. Hely, Michael Zibulevsky and Michael P. Weisend 
 185

Population Decoding Based on an Unfaithful Model, 
Si Wu, Hiroyuki Nakahara, Noboru Murata and Shun-ichi Amari 
 192

Spike-based Learning Rules and Stabilization of Persistent Neural Activity,
Xiaohui Xie and H. Sebastian Seung 
 199 

A VariationaI Baysian Framework for Graphical Models,
 Hagai Attias 
 209 

Model Selection in Clustering by Uniform Convergence Bounds,
Joachim M. Buhmann and Marcus Held 
 216 

Uniqueness of the SVM Solution,
 Christopher J. C. Burges and David J. Crisp 
 223 

Model Selection for Support Vector Machines,
Olivier Chapelle and Vladimir N. Vapnik 
 230 

Dynamics of Supervised Learning with Restricted Training Sets and Noisy Teachers,
 A. C. C. Coolen and C. W. H. Mace 
 237 

A Geometric Interpretation of t/-SVM Classifiers,
David J. Crisp and Christopher J. C. Burges 
 244 

Efficient Approaches to Gaussian Process Classification,
Lehel Csat6, Ernest Fokoue, Manfred Opper, Bernhard Schottky and Ole Winther 
 251 

Potential Boosters?,
 Nigel Duffy and David Helmbold 
 258 

Bayesian Averaging is Well-Temperated,
 Lars Kai Hansen 
 265 

Regular and Irregular GaIIager-type Error-Correcting Codes, 
Yoshiyuki Kabashima, Tatsuto Murayama, David Saad and Renato Vicente 
 272 

Mixture Density Estimation,
 Jonathan Q. Li and Andrew R. Barron 
 279 

Statistical Dynamics of Batch Learning,
 Song Li and K. Y. Michael Wong 
 286 

Neural Computation with Winner-Take-All as the Only Nonlinear Operation,
Wolfgang Maass 
 293 

Boosting with Multi-Way Branching in Decision Trees,
Yishay Mansour and David McAllester 
 300 

Inference for the Generalization Error,
 Claude Nadeau and Yoshua Bengio 
 307 

Resonance in a Stochastic Neuron Model with Delayed Interaction,
Toru Ohira, Yuzuru Sato and Jack D. Cowan 
 314 

Understanding Stepwise Generalization of Support Vector Machines: a Toy Model,
 Sebastian Risau-Gusman and Mirta B. Gordon 
 321 

Lower Bounds on the Complexity of Approximating Continuous Functions by SigmoidaI Neural Networks,
 Michael Schmitt 
 328 

Noisy Neural Networks and Generalizations,
Hava T. Siegelmann, Alexander Roitershtein and Asa Ben-Hur 
 335 

The Entropy Regularization Information Criterion,
 Alexander J. Smola, John Shawe-Taylor, Bernhard Sch61kopf and Robert C. Williamson 
 342 

Probabilistic Methods for Support Vector Machines,
 Peter Sollich 
 349 

Algebraic Analysis for Non-regular Learning Machines,
 Sumio Watanabe 
 356 

Semiparametric Approach to Multichannel Blind Deconvolution of Nonminimum Phase Systems,
 L.-Q. Zhang, Shun-ichi Amari and A. Cichocki 
 363 

Some Theoretical Results Concerning the Convergence of Compositions of ReguIarized Linear Functions,
 Tong Zhang 
 370 

Robust Full Bayesian Methods for Neural Networks, 
Christophe Andrieu, Joao F. G. de Freitas and Arnaud Doucet 
 379 

Independent Factor Analysis with Temporally Structured Sources,
 Hagai Attias 
 386 

Gaussian Fields for Approximate Inference in Layered Sigmoid Belief Networks,
David Barber and Peter Sollich 
 393 

Modeling High-Dimensional Discrete Data with Multi-Layer Neural Networks,
Yoshua Bengio and Samy Bengio 
 400 

Robust Neural Network Regression for Offiine and Online Learning,
Thomas Briegel and Volker Tresp 
 407 

Reconstruction of Sequential Data with Probabilistic Models and Continuity Constraints,
 Miguel A. Carreira-Perpififin 
 414 

Transductive Inference for Estimating Values of Functions, 
Olivier Chapelle, Vladimir N. Vapnik and Jason Weston 
 421 

The Nonnegative Boltzmann Machine,
Oliver B. Downs, David J.C. MacKay and Daniel D. Lee 
 428 

Differentiating Functions of the Jacobian with Respect to the Weights,
Gary William Flake and Barak A. Pearlmutter 
 435 

Local Probability Propagation for Factor Analysis,
 Brendan J. Frey 
 442 

Variational Inference for Bayesian Mixtures of Factor AnaIysers,
Zoubin Ghahramani and Matthew J. Beal 
 449 

Bayesian Transduction,
 Thore Graepel, Ralf Herbrich and Klaus Obermayer 
 456 

Learning to Parse Images,
Geoffrey E. Hinton, Zoubin Ghahramani and Yee Whye Teh 
 463 

Maximum Entropy Discrimination,
 Tommi Jaakkola, Marina Meila and Tony Jebara 
 470 

Topographic Transformation as a Discrete Latent Variable,
Nebojsa Jojic and Brendan J. Frey 
 477 

An Improved Decomposition Algorithm for Regression Support Vector Machines,
Pavel Laskov 
 484 

Algorithms for Independent Components Analysis and Higher Order Statistics,
Daniel D. Lee, Uri Rokni and Haim Sompolinsky 
 491 

The Relaxed Online Maximum Margin Algorithm,
 Yi Li and Philip M. Long 
 498 

Bayesian Network Induction via Local Neighborhoods,
Dimitris Margaritis and Sebastian Thrun 
 505 

Boosting Algorithms as Gradient Descent,
Llew Mason, Jonathan Baxter, Peter Bartlett and Marcus Frean 
 512 

A Multi-class Linear Learning Algorithm Related to Winnow,
 Chris Mesterharm 
 519 

Invariant Feature Extraction and Classification in Kernel Spaces,
Sebastian Mika, Gunnar Ratsch, Jason Weston, Bernhard Sch61kopf, Alexander J. Smola and Klaus-Robert Miiller 
 526 

Approximate Inference Algorithms for Two-Layer Bayesian Networks,
Andrew Y. Ng and Michael I. Jordan 
 533 

Optimal Kernel Shapes for Local Linear Regression,
Dirk Ormoneit and Trevor Hastie 
 540 

Large Margin DAGs for Multiclass Classification,
John C. Platt, Nello Cristianini and John Shawe-Taylor 
 547 

The Infinite Gaussian Mixture Model,
 Carl Edward Rasmussen 
 554 

v-Arc: Ensemble Learning in the Presence of Outliers,
 Gunnar Ratsch, Bernhard Sch61kopf, Alexander J. Smola, Klaus-Robert Miiller, Takashi Onoda and Sebastian Mika 
 561 

Nonlinear Discriminant Analysis Using Kernel Functions,
Volker Roth and Volker Steinhage 
 568 

An Analysis of Turbo Decoding with Gaussian Densities,
Paat Rusmevichientong and Benjamin Van Roy 
 575 

Support Vector Method for Novelty Detection,
 Bernhard Sch61kopf, Robert C. Williamson, Alexander J. Smola, John Shawe-Taylor and John C. Platt 
 582 

Better Generatire Models for Sequential Data Problems: Bidirectional Recurrent Mixture Density Networks,
 Mike Schuster 
 589 

Greedy Importance Sampling,
 Dale Schuurmans 
 596 

Bayesian Model Selection for Support Vector Machines, Gaussian Processes and Other Kernel Classifiers, 
Matthias Seeger 
 603 

Leveraged Vector Machines,
 Yoram Singer 
 610 

AggIomerative Information Bottleneck,
 Noam Slonim and Naftali Tishby 
 617 

Training Data Selection for Optimal Generalization in Trigonometric Polynomial Networks,
 Masashi Sugiyama and Hidemitsu Ogawa 
 624 

Predictive Approaches for Choosing Hyperparameters in Gaussian Processes,
S. Sundararajan and S. Sathiya Keerthi 
 631 

On Input Selection with Reversible Jump Markov Chain Monte Carlo Sampling,
Peter Sykacek 
 638 

Building Predictive Models from FractaI Representations of Symbolic Sequences,
Peter Tifio and Georg Dorffner 
 645 

The Relevance Vector Machine,
 Michael E. Tipping 
 652 

Support Vector Method for Multivariate Density Estimation,
Vladimir N. Vapnik and Sayan Mukherjee 
 659 

Dual Estimation and the Unscented Transformation,
Eric A. Wan, Rudolph van der Merwe and Alex T. Nelson 
 666 

Correctness of Belief Propagation in Gaussian Graphical Models of Arbitrary Topology,
 Yair Weiss and William T. Freeman 
 673 

A MCMC Approach to Hierarchical Mixture Modelling,
 Christopher K. I. Williams 
680 

Data Visualization and Feature Selection: New Algorithms for Nongaussian Data, 
Howard Hua Yang and John Moody 
 687 

ManifoM Stochastic Dynamics for Bayesian Learning, 
Mark Zlochin and Yoram Baram 
 694 

The Parallel Problems Server: an Interactive Tool for Large Scale Machine Learning,
 Charles Lee Isbell, Jr. and Parry Husbands 
 703 

An Oculo-Motor System with Multi-Chip Neuromorphic Analog VLSI Control, 
Oliver Landolt and Steve Gyger 
 710 

A Winner-Take-All Circuit with Controllable Soft Max Property,
 Shih-Chii Liu.
 717 

A Neuromorphic VLSI System for Modeling the Neural Control of Axial Locomotion, 
Girish N. Patel, Edgar A. Brown and Stephen P. DeWeerth 
 724 

Bifurcation Analysis of a Silicon Neuron,
 Girish N. Patel, Germady S. Cymbalyuk, Ronald L. Calabrese and Stephen P. DeWeerth 
 731 

An Analog VLSI Model of Periodicity Extraction,
 Andr6 van Schaik 
 738 

An Oscillatory Correlation Framework for Computational Auditory Scene Analysis,
 Guy J. Brown and DeLiang L. Wang 
 747 

Bayesian Modelling of fMR[ Time Series, 
Pedro A.d. F. R. Hojen-Sorensen, Lars Kai Hansen and Carl Edward Rasmussen 
754 

Neural System Model of Human Sound Localization, 
Craig T. Jin and Simon Carlile 
 761 

Spectral Cues in Human Sound Localization, 
Craig T. Jin, Anna Corderoy, Simon Carllie and Andr6 van Schaik 
 768 

Broadband Direction-Of-Arrival Estimation Based on Second Order Statistics,
Justinian Rosca, Joseph 6 Ruanaidh, Alexander Jourjine and Scott Rickard 
 775 

Constrained Hidden Markov Models,
 Sam Rowels 
 782 

Online Independent Component Analysis with Local Learning Rate Adaptation,
Nicol N. Schraudolph and Xavier Giannakopoulos 
 789 

Speech Modelling Using Subspace and EM Techniques, 
Gavin Smith, Jo5o F. G. de Freitas, Tony Robinson and Mahesan Niranjan 
 796 

Search for Information Bearing Components in Speech, 
Howard Hua Yang and Hynek Hermansky 
 803 

Audio Vision: Using Audio- Visual Synchrony to Locate Sounds,
John Hershey and Javier R. Movellan 
 813 

Bayesian Reconstruction of 3D Human Motion from Single-Camera Video, 
Nicholas R. Howe, Michael E. Leventon and William T. Freeman 
 820 

Emergence of Topography and Complex Cell Properties from Natural Images using Extensions oflCA,
 Aapo Hyvarinen and Patrik Hoyer 
 827 

An Information-Theoretic Framework for Understanding Saccadic Eye Movements,
 Tai Sing Lee and Stella X. Yu 
 834 

Learning Sparse Codes with a Mixture-of-Gaussians Prior, 
Bruno A. Olshausen and K. Jarrod Millman 
 841 

Hierarchical Image Probability (HIP) Models,
 Clay D. Spence and Lucas Parra 
848 

Scale Mixtures of Gaussians and the Statistics of Natural Images, 
Martin J. Wainwright and Eero P. Simoncelli 
 855 

A SNoW-Based Face Detector,
 Ming-Hsuan Yang, Dan Roth and Narendra Ahuja 
862 

Managing Uncertainty in Cue Combination, 
Zhiyong Yang and Richard S. Zemel 
869 

Robust Learning of Chaotic Attractors, 
Rembrandt Bakker, Jaap C. Schouten, Marc-Olivier Coppens, Floris Takens, C. Lee Giles and Cor M. van den Bleek . 
879 

Image Representations for Facial Expression Coding, 
Marian Stewart Bartlett, Gianluca Donato, Javier R. Movellan, Joseph C. Hager, Paul Ekman and Terrence J. Sejnowski 
 886 

Low Power Wireless Communication via Reinforcement Learning,
Timothy X. Brown 
 893 

Learning Informative Statistics: A Nonparametric Approach,
John W. Fisher III, Alexander T. Ihler and Paul A. Viola 
 900

Kirchoff Law Markov Fields for Analog Circuit Design,
 Richard M. Golden 
 907

Learning the Similarity of Documents: An Information-Geometric Approach to Document Retrieval and Categorization,
 Thomas Hofmann 
 914

Constructing Heterogeneous Committees Using Input Feature Grouping: Application to Economic Forecasting,
 Yuansong Liao and John Moody 
 921

From Coexpression to Coregulation: An Approach to Inferring Transcriptional Regulation among Gene Classes from Large-Scale Expression Data,
Eric Mjolsness, Tobias Mann, Rebecca Castafio and Barbara Wold 
 928

Churn Reduction in the Wireless Industry,
 Michael C. Mozer, Richard Wolniewicz, David B. Grimes, Eric Johnson and Howard Kaushansky 
 935

Unmixing Hyperspectral Data,
Lucas Parra, Clay D. Spence, Paul Sajda, Andreas Ziehe and Klaus-Robert Miiller 
 942

Application of Blind Separation of Sources to Optical Recording of Brain Activity,
 Holger Schoner, Martin Stetter, Ingo Schiebl, John E.W. Mayhew, Jennifer Lund, Niall McLoughlin and Klaus Obermayer 
 949

Reinforcement Learning for Spoken Dialogue Systems,
Satinder Singh, Michael Kearns, Diane Litman and Marilyn Walker 
 956

Image Recognition in Context: Application to Microscopic Urinalysis,
Xubo B. Song, Joseph Sill, Yaser Abu-Mostafa and Harvey Kasdan 
 963

Generalized Model Selection for Unsupervised Learning in High Dimensions,
Shivakumar Vaithyanathan and Byron Dom 
 970 

Learning from User Feedback in Image Retrieval Systems,
Nuno Vasconcelos and Andrew Lippman 
 977 

An Environment Model for Nonstationary Reinforcement Learning,
Samuel P.M. Choi, Dit-Yan Yeung and Nevin L. Zhang 
 987 

State Abstraction in MAXQ Hierarchical Reinforcement Learning,
Thomas G. Dieuerich 
 994 

Approximate Planning in Large POMDPs via Reusable Trajectories,
Michael Kearns, Yishay Mansour and Andrew Y. Ng 
 1001 

Actor-Critic Algorithms,
 Vijay R. Konda and John N. Tsitsiklis 
 1008 

Bayesian Map Learning in Dynamic Environments,
 Kevin P. Murphy 
 1015 

Policy Search via Density Estimation, 
Andrew Y. Ng, Ronald Parr and Daphne Koller 
 1022 

Neural Network Based Model Predictive Control,
 Stephen Pich6, Jim Keeler, Greg Martin, Gene Boe, Doug Johnson and Mark Gerules 
 1029 

Reinforcement Learning Using Approximate Belief States,
Andr6s Rodriguez, Ronald Parr and Daphne Koller 
 1036 

Coastal Navigation with Mobile Robots,
 Nicholas Roy and Sebastian Thrun 
 1043 

Learning Factored Representations for Partially Observable Markov Decision Processes,
 Brian Sallans 
 1050 

Policy Gradient Methods for Reinforcement Learning with Function Approximation,
Richard S. Sutton, David McAllester, Satinder Singh and Yishay Mansour 
 1057 

Monte Carlo POMDPs,
 Sebastian Thrun 
 1064 

