0003	Text-Based Information Retrieval Using Exponentiated Gradient Descent, Ron Papka, James P. Callan and Andrew G. Barto
0010	Why did TD-Gammon Work?, Jordan B. Pollack and Alan D. Blair

Part II Neuroscience

0017	Neural Models for Part-Whole Hierarchies, Maximilian Riesenhuber and Peter Dayan
0027	Temporal Low-Order Statistics of Natural Sounds, H. Attias and C. E. Schreiner
0034	Reconstructing Stimulus Velocity from Neuronal Responses in Area MT, Wyeth Bair, James R. Cavanaugh and J. Anthony Movshon
0041	3D Object Recognition: A Model of View-Tuned Neurons, Emanuela Bricolo, Tomaso Poggio and Nikos Logothetis
0048	A Hierarchical Model of Visual Rivalry, Peter Dayan
0055	Neural Network Models of Chemotaxis in the Nematode Caenorhabditis Elegans, Thomas C. Ferree, Ben A. Marcotte and Shawn R. Lockery
0062	Extraction of Temporal Features in the Electrosensory System of Weakly Electric Fish, Fabrizio Gabbiani, Walter Metzner, Ralf Wessel and Christof Koch
0069	A Neural Model of Visual Contour Integration, Zhaoping Li
0076	Learning Exact Patterns of Quasi-synchronization among Spiking Neurons from Data on Multi-unit Recordings, Laura Martignon, Kathryn Laskey, Gustavo Deco and Eilon Vaadia
0083	Complex-Cell Responses Derived from Center-Surround Inputs: The Surprising Power of Intradendritic Computation, Bartlett W. Mel, Daniel L. Ruderman and Kevin A. Archie
0090	Orientation Contrast Sensitivity from Long-range Interactions in Visual Cortex, Klaus R. Pawelzik, Udo Ernst, Fred Wolf and Theo Geisel
0097	Statistically Efficient Estimations Using Cortical Lateral Connections, Alexandre Pouget and Kechen Zhang
0104	An Architectural Mechanism for Direction-tuned Cortical Simple Cells: The Role of Mutual Inhibition, Silvio P. Sabatini, Fabio Solari and Giacomo M. Bisio
0111	Cholinergic Modulation Preserves Spike Timing Under Physiologically Realistic Fluctuating Input, Akaysha C. Tang, Andreas M. Bartels and Terrence J. Sejnowski

Part III Theory

0118	A Model of Recurrent Interactions in Primary Visual Cortex, Emanuel Todorov, Athanassios Siapas and David Somers
0127	Neural Learning in Structured Parameter Spaces - Natural Riemannian Gradient, Shun-ichi Amari
0134	For Valid Generalization, the Size of the Weights is More Important than the Size of the Network, Peter L. Bartlett
0141	Dynamics of Training, Siegfried Bos and Manfred Opper
0148	Multilayer Neural Networks: One or Two Hidden Layers?, G. Brightwell, C. Kenyon and Helene Paugam-Moisy
0155	Support Vector Regression Machines, Harris Drucker, Chris J.C. Burges, Linda Kaufman, Alex Smola and Vladimir Vapnik
0162	Size of Multilayer Networks for Exact Learning: Analytic Approach, Andre Elisseeff and Helene Paugam-Moisy
0169	The Effect of Correlated Input Data on the Dynamics of Learning, Soren Halkjaer and Ole Winther
0176	Practical Confidence and Prediction Intervals, Tom Heskes
0183	Statistical Mechanics of the Mixture of Experts, Kukjin Kang and Jong-Hoon Oh
0190	MLP Can Provably Generalize Much Better than VC-bounds Indicate, A. Kowalczyk and H. Ferra
0197	Radial Basis Function Networks and Complexity Regularization in Function Learning, Adam Krzyzak and Tamas Linder
0204	An Apobayesian Relative of Winnow, Nick Littlestone and Chris Mesterharm
0211	Noisy Spiking Neurons with Temporal Coding have more Computational Power than Sigmoidal Neurons, Wolfgang Maass
0218	On the Effect of Analog Noise in Discrete-Time Analog Computations, Wolfgang Maass and Pekka Orponen
0225	A Mean Field Algorithm for Bayes Learning in Large Feed-forward Neural Networks, Manfred Opper and Ole Winther
0232	Removing Noise in On-Line Search using Adaptive Batch Sizes, Genevieve B. Orr
0239	Are Hopfield Networks Faster than Conventional Computers?, Ian Parberry and Hung-Li Tseng
0246	Hebb Learning of Features based on their Information Content, Ferdinand Peper and Hideki Noda
0253	The Generalisation Cost of RAMnets, Richard Rohwer and Michal Morciniec
0260	Learning with Noise and Regularizers in Multilayer Neural Networks, David Sand and Sara A. Solla
0267	A Variational Principle for Model-based Morphing, Lawrence K. Saul and Michael I. Jordan
0274	Online Learning from Finite Training Sets: An Analytical Case Study, Peter Sollich and David Barber
0281	Support Vector Method for Function Approximation, Regression Estimation, and Signal Processing, Vladimir Vapnik, Steven E. Golowich and Alex Smola
0288	The Learning Dynamcis of a Universal Approximator, Ansgar H. L. West, David Sand and Ian T. Nabney
0295	Computing with Infinite Networks, Christopher K. I. Williams
0302	Microscopic Equations in Rough Energy Landscape for Neural Networks, K. Y. Michael Wong

Part IV Algorithms and Architecture

0309	Time Series Prediction using Mixtures of Experts, Assaf J. Zeevi, Ron Meir and Robert J. Adler
0319	Genetic Algorithms and Explicit Search Statistics, Shumeet Baluja
0326	Consistent Classification, Firm and Soft, Yoram Baram
0333	Bayesian Model Comparison by Monte Carlo Chaining, David Barber and Christopher M. Bishop
0340	Gaussian Processes for Bayesian Classification via Hybrid Monte Carlo, David Barber and Christopher K. I. Williams
0347	Regression with Input-Dependent Noise: A Bayesian Treatment, Christopher M. Bishop and Cazhaow S. Qazaz
0354	GTM: A Principled Alternative to the Self-Organizing Map, Christopher M. Bishop, Markus Svensen and Christopher K. I. Williams
0361	The CONDENSATION Algorithm - Conditional Density Propagation and Applications to Visual Tracking, A. Blake and M. Isard
0368	Clustering via Concave Minimization, P. S. Bradley, O. L. Mangasarian and W. N. Street
0375	Improving the Accuracy and Speed of Support Vector Machines, Chris J.C. Burges and B. Scholkopf
0382	Estimating Equivalent Kernels for Neural Networks: A Data Perturbation Approach, A. Neil Burgess
0389	Promoting Poor Features to Supervisors: Some Inputs Work Better as Outputs, Rich Caruana and Virginia R. de Sa
0396	Self-Organizing and Adaptive Algorithms for Generalized Eigen-Decomposition, Chanchal Chatterjee and Vwani P. Roychowdhury
0403	Representation and Induction of Finite State Machines using Time-Delay Neural Networks, Daniel S. Clouse, C. Lee Giles, Bill G. Home and Garrison W. Cottrell
0410	488 Solutions to the XOR Problem, Frans M. Coetzee and Virginia L. Stonick
0417	Minimizing Statistical Bias with Queries, David A. Cohn
0424	MIMIC: Finding Optima by Estimating Probability Densities, Jeremy S. de Bonet, Charles L. Isbell, Jr. and Paul Viola
0431	On a Modification to the Mean Field EM Algorithm in Factorial Learning, A. P. Dunmur and D. M. Titterington
0438	Softening Discrete Relaxation, Andrew M. Finch, Richard C. Wilson and Edwin R. Hancock
0445	Limitations of Self-organizing Maps for Vector Quantization and Multidimensional Scaling, Arthur Flexer
0452	Continuous Sigmoidal Belief Networks Trained using Slice Sampling, Brendan J. Frey
0459	Adaptively Growing Hierarchical Mixtures of Experts, Juergen Fritsch, Michael Finke and Alex Waibel
0466	Balancing Between Bagging and Bumping, Tom Heskes
0473	LSTM can Solve Hard Long lime Lag Problems, Sepp Hochreiter and Jurgen Schmidhuber
0480	One-unit Learning Rules for Independent Component Analysis, Aapo Hyvarinen and Erkki Oja
0487	Recursive Algorithms for Approximating Probabilities in Graphical Models, Tommi S. Jaakkola and Michael I. Jordan
0494	Combinations of Weak Classifiers, Chuanyi Ji and Sheng Ma
0501	Hidden Markov Decision Trees, Michael I. Jordan, Zoubin Ghahramani and Lawrence K. Saul
0508	Unification of Information Maximization and Minimization, Ryotaro Kamimura
0515	Unsupervised Learning by Convex and Conic Coding, D. D. Lee and H. S. Seung
0522	ARC-LH: A New Adaptive Resampling Algorithm for Improving ANN Classifiers, Friedrich Leisch and Kurt Hornik
0529	Bayesian Unsupervised Learning of Higher Order Structure, Michael S. Lewicki and Terrence J. Sejnowski
0536	Source Separation and Density Estimation by Faithful Equivariant SOM, Juan K. Lin, Jack D. Cowan and David G. Grier
0543	NeuroScale: Novel Topographic Feature Extraction using RBF Networks, David Lowe and Michael E. Tipping
0550	Ordered Classes and Incomplete Examples in Classification, Mark Mathieson
0557	Triangulation by Continuous Embedding, Marina Meila and Michael I. Jordan
0564	Combining Neural Network Regression Estimates with Regularized Linear Weights, Christopher J. Merz and Michael J. Pazzani
0571	A Mixture of Experts Classifier with Learning Based on Both Labelled and Unlabelled Data, David J. Miller and Hasan S. Uyar
0578	Learning Bayesian Belief Networks with Neural Network Estimators, Stefano Monti and Gregory F. Cooper
0585	Smoothing Regularizers for Projective Basis Function Networks, John E. Moody and Thorsteinn S. Rognvaldsson
0592	Competition Among Networks Improves Committee Performance, Paul W. Munro and Bambang Parmanto
0599	Adaptive On-line Learning in Changing Environments, Noboru Murata, Klaus-Robert Muller, Andreas Ziehe and Shun-ichi Amari
0606	Using Curvature Information for Fast Stochastic Search, Genevieve B. Orr and Todd K. Leen
0613	Maximum Likelihood Blind Source Separation: A Context-Sensitive Generalization of ICA, Barak A. Pearlmutter and Lucas C. Parra
0620	A Convergence Prooffor the Softassign Quadratic Assignment Algorithm, Anand Rangarajan, Alan Yuille, Steven Gold and Eric Mjolsness
0627	Second-order Learning Algorithm with Squared Penalty Term, Kazumi Saito and Ryohei Nakano
0634	Monotonicity Hints, Joseph Sill and Yaser S. Abu-Mostafa
0641	Training Algorithms for Hidden Markov Models using Entropy Based Distance Functions, Yoram Singer and Manfred K. Warmuth
0648	Clustering Sequences with Hidden Markov Models, Padhraic Smyth
0655	Fast Network Pruning and Feature Extraction by using the Unit-OBS Algorithm, Achim Stahiberger and Martin Riedmiller
0662	Separating Style and Content, Joshua B. Tenenbaum and William T. Freeman
0669	Early Brain Damage, Volker Tresp, Ralph Neuneier and Hans Georg Zimmermann

Part V Implementation

0676	Probabilistic Interpretation of Population Codes, Richard S. Zemel, Peter Dayan and Alexandre Pouget
0685	VLSI Implementation of Cortical Visual Motion Detection Using an Analog Neural Computer, Ralph Etienne-Cummings, Jan van der Spiegel, Naomi Takahashi, Alyssa Apsel and Paul Mueller
0692	A Spike Based Learning Neuron in Analog VLSI, Philipp Hafliger, Misha Mahowald and Lloyd Watts
0699	An Analog Implementation of the Constant Average Statistics Constraint For Sensor Calibration, John G. Harris and Yu-Ming Chiang
0706	Analog VLSI Circuits for Attention-Based, Visual Tracking, Timothy Horiuchi, Tonia G. Morris, Christof Koch and Stephen P. DeWeerth
0713	Dynamically Adaptable CMOS Winner-Take-All Neural Network, Kunihiko Iizuka, Masayuki Miyamoto and Hirofumi Matsui
0720	An Adaptive WTA using Floating Gate Technology, W. Fritz Kruger, Paul Hasler, Bradley A. Minch and Christof Koch
0727	A Micropower Analog VLSI HMM State Decoder for Wordspotting, John Lazzaro, John Wawrzynek and Richard Lippmann
0734	Bangs, Clicks, Snaps, Thuds and Whacks: An Architecture for Acoustic Transient Processing, Fernando J. Pineda, Gert Cauwenberghs and R. Timothy Edwards

Part VI Speech, Handwriting and Signal Processing

0741	A Silicon Model of Amplitude Modulation Detection in the Auditory Brainstem, Andre van Schaik, Eric Fragniere and Eric Vittoz
0751	Dynamic Features for Visual Speechreading: A Systematic Comparison, Michael S. Gray, Javier R. Movellan and Terrence J. Sejnowski
0758	Blind Separation of Delayed and Convolved Sources, Te-Won Lee, Anthony J. Bell and Russell H. Lambert
0765	A Constructive RBF Network for Writer Adaptation, John C. Platt and Nada P. Matio
0772	A New Approach to Hybrid HMM/ANN Speech Recognition using Mutual Information Neural Networks, G. Rigoll and C. Neukirchen
0779	Neural Network Modeling of Speech and Music Signals, Alex Robel
0786	A Constructive Learning Algorithm for Discriminant Tangent Models, Diego Sona, Alessandro Sperduti and Antonina Starita
0793	Dual Kalman Filtering Methods for Nonlinear Prediction, Smoothing and Estimation, Eric A. Wan and Alex T. Nelson
0800	Ensemble Methods for Phoneme Classification, Steve Waterhouse and Gary Cook

Part VII Visual Processing

0807	Effective Training of a Neural Network Character Classifier for Word Recognition, Larry Yaeger, Richard Lyon and Brandyn Webb
0817	Viewpoint Invariant Face Recognition using Independent Component Analysis and Attractor Networks, Marian Stewart Bartlett and Terrence J. Sejnowski
0824	Learning Temporally Persistent Hierarchical Representations, Suzanna Becker
0831	Edges are the "Independent Components" of Natural Scenes, Anthony J. Bell and Terrence J. Sejnowski
0838	Compositionality, MDL Priors, and Object Recognition, Elie Bienenstock, Stuart Geman and Daniel Potter
0845	Learning Appearance Based Models: Mixtures of Second Moment Experts, Christoph Bregler and Jitendra Malik
0852	Spatial Decorrelation in Orientation Tuned Cortical Cells, Alexander Dimitrov and Jack D. Cowan
0859	Spatiotemporal Coupling and Scaling of Natural Images and Human Visual Sensitivities, Dawei W. Dong
0866	Selective Integration: A Model for Disparity Estimation, Michael S. Gray, Alexandre Pouget, Richard S. Zemel, Steven J. Nowlan and Terrence J. Sejnowski
0873	ARTEX: A Self-organizing Architecture for Classifying Image Regions, Stephen Grossberg and James R. Williamson
0880	Contour Organisation with the EM Algorithm J. A. F Leite and Edwin R. Hancock
0887	Visual Cortex Circuitry and Orientation Tuning, Trevor Mundel, Alexander Dimitrov and Jack D. Cowan
0894	Representing Face Images for Emotion Classification, Curtis Padgett and Garrison W. Cottrell
0901	Rapid Visual Processing using Spike Asynchrony, Simon J. Thorpe and Jacques Gautrais
0908	Interpreting Images by Propagating Bayesian Beliefs, Yair Weiss

Part VIII Applications

0915	Salient Contour Extraction by Temporal Binding in a Cortically-based Network, Shih-Cheng Yen and Leif H. Finkel
0925	An Orientation Selective Neural Network for Pattern Identification in Particle Detectors, Halina Abramowicz, David Horn, Ury Naftaly and Carmit Sahar-Pikielny
0932	Adaptive Access Control Applied to Ethernet Data, Timothy X. Brown
0939	Predicting Lifetimes in Dynamically Allocated Memory, David A. Cohn and Satinder Singh
0946	Multi-Task Learning for Stock Selection, Joumana Ghosn and Yoshua Bengio
0953	The Neurothermostat: Predictive Optimal Control of Residential Heating Systems, Michael C. Mozer, Lucky Vidmar and Robert H. Dodier
0960	Sequential Tracking in Pricing Financial Options using Model Based and Neural Network Approaches, Mahesan Niranjan
0967	A Comparison between Neural Networks and other Statistical Techniques for Modeling the Relationship between Tobacco andAlcohol and Cancer, Tony Plate, Pierre Band, Joel Bert and John Grace
0974	Reinforcement Learning for Dynamic Channel Allocation in Cellular Telephone Systems, Satinder Singh and Dimitri Bertsekas
0981	Spectroscopic Detection of Cervical Pre-Cancer through Radial Basis Function Networks, Kagan Turner, Nirmala Ramanujam, Rebecca Richards-Korturn and Joydeep Ghosh
0988	Interpolating Earth-science Data using RBF Networks and Mixtures of Experts, Ernest Wan and Don Bone

Part IX Control, Navigation and Planning

0995	Multi-effect Decompositions for Financial Data Modeling, Lizhong Wu and John E. Moody
1005	Multidimensional Triangulation and Interpolation for Reinforcement Learning, Scott Davies
1012	Efficient Nonlinear Control with Actor-Tutor Architecture, Kenji Doya
1019	Local Bandit Approximation for Optimal Learning Problems, Michael O. Duff and Andrew G. Barto
1026	Reinforcement Learning for Mixed Open-loop and Closed-loop Control, Eric A. Hansen, Andrew G. Barto and Shiomo Zilberstein
1033	Multi-Grid Methods for Reinforcement Learning in Controlled Diffusion Processes, Stephan Pareigis
1040	Learning from Demonstration, Stefan Schaal
1047	Exploiting Model Uncertainty Estimates for Safe Dynamic Control Learning, Jeff G. Schneider
1054	Analytical Mean Squared Error Curves in Temporal Difference Learning, Satinder Singh and Peter Dayan
1061	Learning Decision Theoretic Utilities through Reinforcement Learning, Magnus Stensmo and Terrence J. Sejnowski
1068	On-line Policy Improvement using Monte-Carlo Search, Gerald Tesauro and Gregory R. Galperin
1075	Analysis of Temporal-Difference Learning with Function Approximation, John N. Tsitsiklis and Benjamin Van Roy
1082	Approximate Solutions to Optimal Stopping Problems, John N. Tsitsiklis and Benjamin Van Roy
1089	Index of Authors
1093	Keyword Index