Book

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

A Randomized Algorithm for Pairwise Clustering Yoram Gdalyahu, Daphna Weinshall, Michael Werman

Risk Sensitive Reinforcement Learning Ralph Neuneier, Oliver Mihatsch

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

Mean Field Methods for Classification with Gaussian Processes Manfred Opper, Ole Winther

Learning from Dyadic Data Thomas Hofmann, Jan Puzicha, Michael Jordan

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

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

Learning Nonlinear Dynamical Systems Using an EM Algorithm Zoubin Ghahramani, Sam Roweis

Replicator Equations, Maximal Cliques, and Graph Isomorphism Marcello Pelillo

Orientation, Scale, and Discontinuity as Emergent Properties of Illusory Contour Shape Karvel Thornber, Lance Williams

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

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

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

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

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

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

A Neuromorphic Monaural Sound Localizer John Harris, Chiang-Jung Pu, José Príncipe

Boxlets: A Fast Convolution Algorithm for Signal Processing and Neural Networks Patrice Simard, Léon Bottou, Patrick Haffner, Yann LeCun

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

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

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

Kernel PCA and De-Noising in Feature Spaces Sebastian Mika, Bernhard Schölkopf, Alex Smola, Klaus-Robert Müller, Matthias Scholz, Gunnar Rätsch

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

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

Learning Lie Groups for Invariant Visual Perception Rajesh Rao, Daniel Ruderman

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

A Micropower CMOS Adaptive Amplitude and Shift Invariant Vector Quantiser Richard Coggins, Raymond Wang, Marwan Jabri

Convergence Rates of Algorithms for Visual Search: Detecting Visual Contours Alan L. Yuille, James Coughlan

Learning to Find Pictures of People Sergey Ioffe, David Forsyth

Visualizing Group Structure Marcus Held, Jan Puzicha, Joachim Buhmann

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

Familiarity Discrimination of Radar Pulses Eric Granger, Stephen Grossberg, Mark Rubin, William Streilein

Graphical Models for Recognizing Human Interactions Nuria Oliver, Barbara Rosario, Alex Pentland

An Entropic Estimator for Structure Discovery Matthew Brand

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

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

Contrast Adaptation in Simple Cells by Changing the Transmitter Release Probability Péter Adorján, Klaus Obermayer

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

Information Maximization in Single Neurons Martin Stemmler, Christof Koch

Mechanisms of Generalization in Perceptual Learning Zili Liu, Daphna Weinshall

Probabilistic Image Sensor Fusion Ravi Sharma, Todd Leen, Misha Pavel

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

Phase Diagram and Storage Capacity of Sequence-Storing Neural Networks A. Düring, Anthony Coolen, D. Sherrington

Example-Based Image Synthesis of Articulated Figures Trevor Darrell

Shrinking the Tube: A New Support Vector Regression Algorithm Bernhard Schölkopf, Peter Bartlett, Alex Smola, Robert C. Williamson

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

Reinforcement Learning for Trading John Moody, Matthew Saffell

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

Using Collective Intelligence to Route Internet Traffic David Wolpert, Kagan Tumer, Jeremy Frank

Sparse Code Shrinkage: Denoising by Nonlinear Maximum Likelihood Estimation Aapo Hyvärinen, Patrik Hoyer, Erkki Oja

Finite-Dimensional Approximation of Gaussian Processes Giancarlo Ferrari-Trecate, Christopher Williams, Manfred Opper

Controlling the Complexity of HMM Systems by Regularization Christoph Neukirchen, Gerhard Rigoll

Scheduling Straight-Line Code Using Reinforcement Learning and Rollouts Amy McGovern, J. Moss

Learning to Estimate Scenes from Images William Freeman, Egon Pasztor

Learning Curves for Gaussian Processes Peter Sollich

Facial Memory Is Kernel Density Estimation (Almost) Matthew Dailey, Garrison Cottrell, Thomas Busey

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

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

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

Robust, Efficient, Globally-Optimized Reinforcement Learning with the Parti-Game Algorithm Mohammad Al-Ansari, Ronald Williams

Learning a Hierarchical Belief Network of Independent Factor Analyzers Hagai Attias

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

Maximum-Likelihood Continuity Mapping (MALCOM): An Alternative to HMMs David Nix, John Hogden

Semiparametric Support Vector and Linear Programming Machines Alex Smola, Thilo-Thomas Frieß, Bernhard Schölkopf

Regularizing AdaBoost Gunnar Rätsch, Takashi Onoda, Klaus R. Müller

Graph Matching for Shape Retrieval Benoit Huet, Andrew Cross, Edwin Hancock

DTs: Dynamic Trees Christopher Williams, Nicholas Adams

Adding Constrained Discontinuities to Gaussian Process Models of Wind Fields Dan Cornford, Ian Nabney, Christopher Williams

The Belief in TAP Yoshiyuki Kabashima, David Saad

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

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

Using Analytic QP and Sparseness to Speed Training of Support Vector Machines John Platt

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

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

Learning Mixture Hierarchies Nuno Vasconcelos, Andrew Lippman

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

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

Coding Time-Varying Signals Using Sparse, Shift-Invariant Representations Michael Lewicki, Terrence J. Sejnowski

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

Restructuring Sparse High Dimensional Data for Effective Retrieval Charles Isbell, Paul Viola

Classification in Non-Metric Spaces Daphna Weinshall, David Jacobs, Yoram Gdalyahu

Approximate Learning of Dynamic Models Xavier Boyen, Daphne Koller

Independent Component Analysis of Intracellular Calcium Spike Data Klaus Prank, Julia Börger, Alexander von zur Mühlen, Georg Brabant, Christof Schöfl

A Model for Associative Multiplication G. Christianson, Suzanna Becker

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

Learning Macro-Actions in Reinforcement Learning Jette Randlov

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

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

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

Dynamics of Supervised Learning with Restricted Training Sets Anthony Coolen, David Saad

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

A Polygonal Line Algorithm for Constructing Principal Curves Balázs Kégl, Adam Krzyzak, Tamás Linder, Kenneth Zeger

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

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

Global Optimisation of Neural Network Models via Sequential Sampling João de Freitas, Mahesan Niranjan, Arnaud Doucet, Andrew Gee

Non-Linear PI Control Inspired by Biological Control Systems Lyndon Brown, Gregory Gonye, James Schwaber

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

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

Support Vector Machines Applied to Face Recognition P. Phillips

A Theory of Mean Field Approximation Toshiyuki Tanaka

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

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

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

Gradient Descent for General Reinforcement Learning Leemon Baird, Andrew Moore

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

Probabilistic Visualisation of High-Dimensional Binary Data Michael Tipping

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

Applications of Multi-Resolution Neural Networks to Mammography Clay Spence, Paul Sajda

Divisive Normalization, Line Attractor Networks and Ideal Observers Sophie Denève, Alexandre Pouget, Peter Latham

Robot Docking Using Mixtures of Gaussians Matthew Williamson, Roderick Murray-Smith, Volker Hansen

Semi-Supervised Support Vector Machines Kristin Bennett, Ayhan Demiriz

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

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

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

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

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

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

Bayesian PCA Christopher Bishop

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

General-Purpose Localization of Textured Image Regions Ruth Rosenholtz

Making Templates Rotationally Invariant. An Application to Rotated Digit Recognition Shumeet Baluja

Outcomes of the Equivalence of Adaptive Ridge with Least Absolute Shrinkage Yves Grandvalet, Stéphane Canu

Bayesian Modeling of Human Concept Learning Joshua Tenenbaum

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

Source Separation as a By-Product of Regularization Sepp Hochreiter, Jürgen Schmidhuber

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

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

Barycentric Interpolators for Continuous Space and Time Reinforcement Learning Rémi Munos, Andrew Moore

Exploiting Generative Models in Discriminative Classifiers Tommi Jaakkola, David Haussler

Learning a Continuous Hidden Variable Model for Binary Data Daniel Lee, Haim Sompolinsky

Perceiving without Learning: From Spirals to Inside/Outside Relations Ke Chen, DeLiang Wang

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

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

Recurrent Cortical Amplification Produces Complex Cell Responses Frances Chance, Sacha Nelson, L. Abbott

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

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

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

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

Discovering Hidden Features with Gaussian Processes Regression Francesco Vivarelli, Christopher Williams

Utilizing lime: Asynchronous Binding Bradley C. Love

Very Fast EM-Based Mixture Model Clustering Using Multiresolution Kd-Trees Andrew Moore

Tight Bounds for the VC-Dimension of Piecewise Polynomial Networks Akito Sakurai

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

Exploratory Data Analysis Using Radial Basis Function Latent Variable Models Alan Marrs, Andrew Webb

A V1 Model of Pop Out and Asymmetty in Visual Search Zhaoping Li

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

Exploring Unknown Environments with Real-Time Search or Reinforcement Learning Sven Koenig

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

Basis Selection for Wavelet Regression Kevin Wheeler, Atam Dhawan

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

Advances in Neural Information Processing Systems 11 (NIPS 1998)

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