NeurIPS 1998

151 papers

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

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

A Model for Associative Multiplication G. Bjorn Christianson, Suzanna Becker

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

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

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

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

A Principle for Unsupervised Hierarchical Decomposition of Visual Scenes Michael Mozer

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

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

A Theory of Mean Field Approximation Toshiyuki Tanaka

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

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

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

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

An Entropic Estimator for Structure Discovery Matthew Brand

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

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

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

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

Approximate Learning of Dynamic Models Xavier Boyen, Daphne Koller

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

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

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

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

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

Bayesian Modeling of Human Concept Learning Joshua B. Tenenbaum

Bayesian PCA Christopher M. Bishop

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

Example-Based Image Synthesis of Articulated Figures Trevor Darrell

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

Exploiting Generative Models in Discriminative Classifiers Tommi Jaakkola, David Haussler

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

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

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

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

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

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

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

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

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

General-Purpose Localization of Textured Image Regions Ruth Rosenholtz

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

Gradient Descent for General Reinforcement Learning Leemon C. Baird Iii, Andrew W. Moore

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

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

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

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

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

Information Maximization in Single Neurons Martin Stemmler, Christof Koch

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

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

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

Learning a Hierarchical Belief Network of Independent Factor Analyzers Hagai Attias

Learning Curves for Gaussian Processes Peter Sollich

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

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

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

Learning Macro-Actions in Reinforcement Learning Jette Randlov

Learning Mixture Hierarchies Nuno Vasconcelos, Andrew Lippman

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

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

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

Learning to Find Pictures of People Sergey Ioffe, David A. Forsyth

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

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

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

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

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

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

Mechanisms of Generalization in Perceptual Learning Zili Liu, Daphna Weinshall

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

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

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

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

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

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

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

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

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

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

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

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

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

Perceiving Without Learning: From Spirals to Inside/Outside Relations Ke Chen, DeLiang L. Wang

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

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

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

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

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

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

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

Reinforcement Learning for Trading John E. Moody, Matthew Saffell

Replicator Equations, Maximal Cliques, and Graph Isomorphism Marcello Pelillo

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

Risk Sensitive Reinforcement Learning Ralph Neuneier, Oliver Mihatsch

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

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

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

Semi-Supervised Support Vector Machines Kristin P. Bennett, Ayhan Demiriz

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

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

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

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

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

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

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

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

Support Vector Machines Applied to Face Recognition P. Jonathon Phillips

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

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

The Belief in TAP Yoshiyuki Kabashima, David Saad

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

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

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

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

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

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

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

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

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

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

Utilizing Lime: Asynchronous Binding Bradley C. Love

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

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

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

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

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

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