Evidence for a Forward Dynamics Model in Human Adaptive Motor Control 
Nikhil Bhushan and Reza Shadmehr 
3 

Perceiving without Learning.' From Spirals to Inside/Outside Relations
Ke Chen and DeLiang L. Wang 
 10 

A Model for Associative Multiplication
G. Bjorn Christianson and Suzanna Becker 
 17 

Facial Memory Is Kernel Density Estimation (Almost) 
Matthew N. Dailey, Garrison W. Cottrell and Thomas A. Busey 
 24 

Multiple Paired Forward-Inverse Models for Human Motor Learning and Control
Masahiko Hamno, Daniel M. Wolpert and Mitsuo Kawato 
 31 

Utilizing lime: Asynchronous Binding,
Bradley C. Love 
 38 

Mechanisms of Generalization in Perceptual Learning,
Zili Liu and Daphna Weinshall 
 45 

A Principle for Unsupervised Hierarchical Decomposition of Visual Scenes,
Michael C. Mozer 
 52 

Bayesian Modeling of Human Concept Learning,
 Joshua B. Tenenbaum 
 59 

Temporally Asymmetric Hebbian Learning, Spike liming and Neural Response 
Variability, L. F. Abbott and Sen Song 
 69 

Contrast Adaptation in Simple Cells by Changing the Transmitter Release Probability,
 Peter Adorjtin and Klaus Obermayer 
 76 

Where Does the Population Vector of Motor Cortical Cells Point during Reaching Movements?,
 Pierre Baraduc, Emmanuel Guigon and Yves Burnod
83 

Recurrent Cortical Amplification Produces Complex Cell Responses, 
Frances S. Chance, Sacha B. Nelson and L. F. Abbott 
 90 

Neuronal Regulation Implements Efficient Synaptic Pruning, 
Gal Chechik, Isaac Meilijson and Eytan Ruppin 
 97 

Divisive Normalization, Line Attractor Networks and Ideal Observers, 
Sophie Deneve, Alexandre Pouget and Peter E. Latham 
 104 

Synergy and Redundancy among Brain Cells of Behaving Monkeys,
Itay Gat and Naftali Tishby 
 111 

Analyzing and Visualizing Single-Trial Event-Related Potentials,
Tzyy-Ping Jung, Scott Makeig, Marissa Westerfield, Jeanne Townsend, Eric Courchesne and Terrence J. Sejnowski 
 118 

Spike-Based Compared to Rate-Based Hebbian Learning,
Richard Kempter, Wulfram Gerstner and J. Leo van Hemmen 
 125 

Signal Detection in Noisy Weakly-Active Dendrites,
Amit Manwani and Christof Koch 
 132 

The Role of Lateral Cortical Competition in Ocular Dominance Development,
Christian Piepenbrock and Klaus Obermayer 
 139 

Multi-Electrode Spike Sorting by Clustering Transfer Functions, 
Dmitry Rinberg, Hanan Davidowitz and Naftali Tishby 
 146 

Modeling Surround Suppression in V1 Neurons with a Statistically Derived Normalization Model,
 Eero P. Simoncelli and Odelia Schwartz 
 153 

Information Maximization in Single Neurons,
Martin Stemmler and Christof Koch 
 160 

The Effect of Correlations on the Fisher Information of Population Codes,
 Hyoungsoo Yoon and Haim Sompolinsky 
 167 

Distributional Population Codes and Multiple Motion Models,
Richard S. Zemel and Peter Dayan 
 174 

Tractable Variational Structures for Approximating Graphical Models,
David Barber and Wim Wiegerinck 
 183 

Almost Linear VC Dimension Bounds for Piecewise Polynomial Networks,
Peter L. Bartlett, Vitaly Maiorov and Ron Meir 
 190 

Dynamics of Supervised Learning with Restricted Training Sets,
A. C. C. Coolen and David Saad 
 197 

Dynamically Adapting Kernels in Support Vector Machines,
Nello Cristianini, Colin Campbell and John Shawe-Taylor 
 204 

Phase Diagram and Storage Capacity of Sequence-Storing Neural Networks,
A. Daring, A. C. C. Coolen and D. Sherrington 
 211 

Finite-Dimensional Approximation of Gaussian Processes,
Giancarlo Ferrari-Trecate, Christopher K. I. Williams and Manfred  Opper 
 218 

Linear Hinge Loss and Average Margin, 
Claudio Gentile and Manfred K. Warrnuth 
 225 

Unsupervised and Supervised Clustering.' The Mutual Information between Parameters and Observations,
 Didier Herschkowitz and Jean-Pierre Nadal 
 232

Convergence of the Wake-Sleep Algorithm, 
Shiro Ikeda, Shun-ichi Amari and Hiroyuki Nakahara 
 239 

The Belief in TAP,
 Yoshiyuki Kabashima and David Saad 
 246 

Optimizing Classifers for Imbalanced Training Sets, 
Grigoris Karakoulas and John Shawe-Taylor 
 253 

Inference in Multilayer Networks via Large Deviation Bounds, 
Michael Kearns and Lawrence Saul 
 260 

Stationarity and Stability of Autoregressive Neural Network Processes,
Friedrich Leisch, Adrian Trapletti and Kurt Hornik 
 267 

Computational Differences between Asymmetrical and Symmetrical Networks,
Zhaoping Li and Peter Dayan 
 274 

A Precise Characterization of the Class of Languages Recognized by Neural Nets under Gaussian and Other Common Noise Distributions 
Wolfgang Maass and Eduardo D. Sontag
281 

Direct Optimization of Margins Improves Generalization in Combined Classifiers,
 Llew Mason, Peter L. Bartlett and Jonathan Baxter 
 288 

On the Optimality of Incremental Neural Network Algorithms, 
Ron Meir and Vitaly Maiorov 
 295 

General Bounds on Bayes Errors for Regression with Gaussian Processes,
Manfred Opper and Francesco Vivarelli 
 302 

Mean FieM Methods for Classification with Gaussian Processes,
Manfred Opper and Ole Winther 
 309 

On-Line Learning with Restricted Training Sets: Exact Solution as Benchmark for General Theories,
 H. C. Rae, Peter Sollich and A. C. C. Coolen 
 316 

Tight Bounds for the VC-Dimension of Piecewise Polynomial_Networks,
Akito Sakurai 
 323 

Shrinking the Tube: A New Support Vector Regression Algorithm, 
Bernhard SchOlkopf, Peter L. Bartlett, Alex J. Smola and Robert Williamson 
330 

Discontinuous Recall Transitions Induced by Competition Between Short- and Long-Range Interactions in Recurrent Networks, 
N. S. Skantzos, C. F. Beckmann and A. C. C. Coolen 
 337 

Learning Curves for Gaussian Processes,
 Peter Sollich 
 344 

A Theory of Mean Field Approximation,
 Toshiyuki Tanaka 
 351 

Learning a Hierarchical Belief Network of Independent Factor Analyzers,
Hagai Attias 
 361 

Semi-Supervised Support Vector Machines,
 Kristin Bennett and Ayhan Demiriz 
368 

Lazy Learning Meets the Recursive Least Squares Algorithm,
Mauro Birattari, Gianluca Bontempi and Hugues Bersini 
375 

Bayesian PCA,
 Christopher M. Bishop 
 382 

Learning Multi-Class Dynamics,
 Andrew Blake, Ben North and Michael Isard 
389 

Approximate Learning of Dynamic Models, 
Xavier Boyen and Daphne Koller 
396 

Fisher Scoring and a Mixture of Modes Approach for Approximate Inference and  Learning in Nonlinear State Space Models, 
Thomas Briegel and Volker Tresp 
403 

Global Optimisation of Neural Network Models via Sequential Sampling 
Joao F. G. de Freitas, Mahesan Niranjan, Amaud Doucet and Andrew H. Gee 
410 

Efficient Bayesian Parameter Estimation in Large Discrete Domains, 
Nir Friedman and Yoram Singer 
 417 

A Randomized Algorithm for Pairwise Clustering 
Yoram Gdalyahu, Daphna Weinshall and Michael Werrnan 
 424 

Learning Nonlinear Dynamical Systems Using an EM Algorithm,
 Zoubin Ghahramani and Sam T. Roweis 
 431 

Classification on Pairwise Proximity Data, 
Thore Graepel, Ralf Herbrich, Peter Bollmann-Sdorra and Klaus Obermayer 
438 

Outcomes of the Equivalence of Adaptive Ridge with Least Absolute Shrinkage, 
Yves Grandvalet and Stephane Canu 
 445 

Visualizing Group Structure,
Marcus Held, Jan Puzicha and Joachim M. Buhmann 
 452 

Source Separation as a By-Product of Regularization,
Sepp Hochreiter and Jtirgen Schmidhuber 
459 

Learning from Dyadic Data, 
Thomas Holmann, Jan Puzicha and Michael I. Jordan 
 466 

Sparse Code Shrinkage.' Denoising by Nonlinear Maximum Likelihood Estimation,
 Aapo Hyvfirinen, Patrik Hoyer and Erkki Oja 
 473 

Restructuring Sparse High Dimensional Data for Effective Retrieval, 
Charles Lee Isbell, Jr. and Paul Viola 
 480 

Exploiting Generative Models in Discriminative Classifiers,
Tommi S. Jaakkola and David Haussler 
 487 

Maximum Conditional Likelihood via Bound Maximization and the CEM Algorithm,
 Tony Jebara and Alex Pentland 
 494 

A PolygonalLine Algorithm for Constructing Principal Curves, 
Balfizs K6gl, Adam Krzyiak, Tamils Linder and Kenneth Zeger 
 501 

Unsupervised Classification with Non-Gaussian Mixture Models Using ICA,
Te-Won Lee, Michael S. Lewicki and Terrence J. Sejnowski 
 508 

Learning a Continuous Hidden Variable Model for Binary Data, 
Daniel D. Lee and Haim Sompolinsky 
 515 

Neural Networks for Density Estimation,
 Malik Magdon-Ismail and Amir Atiya 
522 

Exploratory Data Analysis Using Radial Basis Function Latent Variable Models, 
Alan D. Marrs and Andrew R. Webb 
 529 

Kernel PCA and De-Noising in Feature Spaces,
 Sebastian Mika, Bernhard Sch61kopf, Alex J. Smola, Klaus-Robert MOller, Matthias Scholz and Gunnar Ratsch 
 536 

Very Fast EM-Based Mixture Model Clustering Using Multiresolution Kd-Trees,
 Andrew W. Moore 
 543 

Replicator Equations, Maximal Cliques, and Graph Isomorphism, 
Marcello Pelillo 
 550 

Using Analytic QP and Sparseness to Speed Training of Support Vector Machines,
 John C. Platt 
 557 

Regularizing AdaBoost,
 Gunnar Ratsch, Takashi Onoda and Klaus-Robert Muller 
564 

Boxlets: A Fast Convolution Algorithm for Signal Processing and Neural Networks, 
Patrice Y. Simard, Leon Bottou, Patrick Haffner and Yann Le Cun
571 

Batch and On-Line Parameter Estimation of Gaussian Mixtures Based on the Joint Entropy, 
Yoram Singer and Manfred K. Warmuth 
 578 

Semiparametric Support Vector and Linear Programming Machines, 
Alex J. Smola, Thilo T. Frie13 and Bernhard Sch61kopf 
 585 

Probabilistic Visualisation of High-Dimensional Binary Data,
 Michael E. Tipping 
592 

SMEM Algorithm for Mixture Models, 
Naonori Ueda, Ryohei Nakano, Zoubin Ghahramani and Geoffrey E. Hinton 
599 

Learning Mixture Hierarchies, 
Nuno Vasconcelos and Andrew Lippman 
 606 

Discovering Hidden Features with Gaussian Processes Regression, 
Francesco Vivarelli and Christopher K. I. Williams 
 613 

The Bias-Variance Tradeoff and the Randomized GACV,
 Grace Wahba, Xiwu Lin, Fangyu Gao, Dong Xiang, Ronald Klein and Barbara Klein
 620 

Basis Selection for Wavelet Regression,
 Kevin R. Wheeler and Atam P. Dhawan
627 

DTs: Dynamic Trees, 
Christopher K. I. Williams and Nicholas J. Adams
 634 

Convergence Rates of Algorithms for Visual Search: Detecting Visual Contours,
A. L. Yuille and James M. Coughlan 
 641 

Blind Separation of Filtered Sources Using State-Space Approach,
Liqing Zhang and Andrzej Cichocki 
 648 

Analog VLSI Cellular Implementation of the Boundary Contour System,
Gert Cauwenberghs and James Waskiewicz 
  657 

Active Noise Canceling Using Analog Neuro-Chip with On-Chip Learning  Capability,
 Jung-Wook Cho and Soo-Young Lee 
 664 

A Micropower CMOSAdaptive Amplitude and Shift Invariant Vector Quantiser,
Richard J. Coggins, Raymond J. W. Wang and Marwan A. Jabri 
 671 

Optimizing Correlation Algorithms for Hardware-Based Transient Classification,
R. Timothy Edwards, Gert Cauwenberghs and Fernando J. Pineda 
 678 

VLSI Implementation of Motion Centroid Localization for Autonomous  Navigation,
Ralph Etienne-Cummings, Viktor Gruev and Mohammed Abdel Ghani 
 685 

A Neuromorphic Monaural Sound Localizer, 
John G. Harris, Chiang-Jung Pu and Jose C. Principe 
 692 

An Integrated Vision Sensor for the Computation of Optical Flow Singular  Points,
 Charles M. Higgins and Christof Koch 
 699 

Computation of Smooth Optical Flow in a Feedback Connected Analog Network, 
Alan Stocker and Rodney Douglas 
 706 

High Performance k-NN Classifier Using a Binary Correlation Matrix Memory, 
Ping Zhou, Jim Austin and John Kennedy 
 713 

An Entropic Estimator for Structure Discovery,
 Matthew Brand 
 723 

Coding lime- Varying Signals Using Sparse,  Shift-Invariant Representations, 
Michael S. Lewicki and Terrence J. Sejnowski 
730  

Controlling the Complexity of HMM Systems by Regularization, 
Christoph Neukirchen and Gerhard Rigoil 
737 

Maximum-Likelihood Continuity Mapping (MALCOM) : An Alternative to HMMs,
 David A. Nix and John E. Hogden 
 744 

Markov Processes on Curves for Automatic Speech Recognition, 
Lawrence Saul and Mazin Rahim 
 751 

Phase Space Approach to Minimax Entropy Learning and the Minutemax Approximations,
 James M. Coughlan and A. L. Yuille 
 761 

Example-Based Image Synthesis of Articulated Figures,
 Trevor Darrell 
 768 

Learning to Estimate Scenes from Images, 
William T. Freeman and Egon C. Pasztor 
 775 

Learning to Find Pictures of People,
 Sergey Ioffe and David Forsyth 
 782 

Attentional Modulation of Human Pattern Discrimination Psychophysics Reproduced by a Quantitative Model,
Laurent Itti, Jochen Braun, Dale K. Lee and Christof Koch 
 789 

A V1 Model of Pop Out and Asymmetry in Visual Search,
 Zhaoping Li 
 796 

Support Vector Machines Applied to Face Recognition,
 P. Jonathon Phillips 
 803 

Learning Lie Groups for Invariant Visual Perception,
Rajesh P. N. Rao and Daniel L. Ruderman 
 810 

General-Purpose Localization of Textured Image Regions,
 Ruth Rosenholtz 
 817 

Probabilistic Image Sensor Fusion, 
Ravi K. Sharma, Todd K. Leen and Misha Pavel 
 824 

Orientation, Scale, and Discontinuity as Emergent Properties of Illusory Contour Shape, 
Karvel K. Thomber and Lance R. Williams 
 831 

Classification in Non-Metric Spaces, 
Daphna Weinshall, David W. Jacobs and Yoram Gdalyahu 
 838 

Making Templates Rotationally Invariant: An Application to Rotated Digit Recognition,
 Shumeet Baluja 
 847 

Probabilistic Modeling for Face Orientation Discrimination: Learning from Labeled and Unlabeled Data,
 Shumeet Baluja 
 854 

Adding Constrained Discontinuities to Gaussian Process Models of Wind Fields,
 Dan Cornford, Ian T. Nabney and Christopher K. I. Williams 
 861 

Vertex Identification in High Energy Physics Experiments, 
Gideon Dror, Halina Abramowicz and David Horn 
 868 

Familiarity Discrimination of Radar Pulses,
Eric Granger, Stephen Grossberg, Mark A. Rubin and William  W. Streilein 
 875 

Fast Neural Network Emulation of Dynamical Systems for Computer Animation,
Radek Grzeszczuk, Demetri Terzopoulos and Geoffrey E. Hinton 
 882 

Call-Based Fraud Detection in Mobile Communication Networks Using a Hierarchical Regime-Switching Model,
 Jaakko Hollm6n and Volker Tresp 
 889 

Graph Matching for Shape Retrieval,
Benoit Huet, Andrew D. J. Cross and Edwin R. Hancock 
 896 

Scheduling Straight-Line Code Using Reinforcement Learning and Rollouts,
Amy McGovern and Eliot Moss 
 903 

Bayesian Modeling of Facial Similarity,
Baback Moghaddam, Tony Jebara and Alex Pentland 
 910 

Reinforcement Learning for Trading,
 John Moody and Matthew SalTell 
 917 

Graphical Models for Recognizing Human Interactions,
Nuria M. Oliver, Barbara Rosario and Alex Pentland 
 924 

Independent Component Analysis of lntracellular Calcium Spike Data,
Klaus Prank, Julia B6rger, Alexander von zur Miihlen, Georg Brabant and Christof Sch6fl 
 931 

Applications of Multi-Resolution Neural Networks to Mammography,
Clay D. Spence and Paul Sajda 
 938 

Robot Docking Using Mixtures of Gaussians,
Matthew M. Williamson, Roderick Murray-Smith and Volker Hansen 
 945 

Using Collective Intelligence to Route Internet Traffic,
David H. Wolpert, Kagan Tumer and Jeremy Frank 
 952 

Robust, Efficient, Globally-Optimized Reinforcement Learning with the Parti-Game Algorithm, 
Mohammad A. A1-Ansari and Ronald J. Williams 
 961 

Gradient Descent for General Reinforcement Learning,
Leemon Baird and Andrew W. Moore 
 968 

Non-Linear PI Control Inspired by Biological Control Systems,
Lyndon J. Brown, Gregory E. Gonye and James S. Schwaber 
 975 

Optimizing Admission Control while Ensuring Quality of Service in Multimedia Networks via Reinforcement Learning,
Timothy X. Brown, Hui Tong and Satinder Singh 
 982 

Viewing Classifier Systems as Model Free Learning in POMDPs,
Akira Hayashi and Nobuo Suematsu 
 989 

Finite-Sample Convergence Rates for Q-Learning and Indirect Algorithms,
 Michael Kearns and Satinder Singh 
 996 

Exploring Unknown Environments with Real-71me Search or Reinforcement Learning,
 Sven Koenig 
 1003 

The Effect of Eligibility Traces on Finding Optimal Memoryless Policies in Partially Observable Markov Decision Processes,
 John Loch 
 1010 

Learning Instance-Independent Value Functions to Enhance Local Search,
Robert Moll, Andrew G. Barto, Theodore J. Perkins and Richard S. Sutton 
 1017 

Barycentric Interpolators for Continuous Space and 71me Reinforcement Learning,
 R6mi Munos and Andrew W. Moore 
 1024 

Risk Sensitive Reinforcement Learning,
 Ralph Neuneier and Oliver Mihatsch 
1031 

Coordinate Transformation Learning of Hand Position Feedback Controller by Using Change of Position Error Norm, 
Eimei Oyama and Susumu Tachi
 1038 

Learning Macro-Actions in Reinforcement Learning,
 Jette Randlov 
 1045 

Reinforcement Learning Based on On-Line EM Algorithm, 
Masa-aki Sato and Shin Ishii 
 1052 

A Reinforcement Learning Algorithm in Partially Observable Environments Using Short-Term Memory,
 Nobuo Suematsu and Akira Hayashi 
 1059 

Improved Switching among Temporally Abstract Actions,
Richard S. Sutton, Satinder Singh, Doina Precup and Balaraman Ravindran 
 1066 

Experimental Results on Learning Stochastic Memoryless Policies for Partially Observable Markov Decision Processes,
 John K. Williams and Satinder Singh 
1073 

