NIPS 1999 Proceedings

Advances in Neural Information Processing Systems 12 (NIPS 1999)

The papers below appear in Advances in Neural Information Processing Systems 12 edited by S.A. Solla and T.K. Leen and K. Müller.
They are proceedings from the conference, "Neural Information Processing Systems 1999."

Recognizing Evoked Potentials in a Virtual Environment Jessica D. Bayliss, Dana H. Ballard
A Neurodynamical Approach to Visual Attention Gustavo Deco, Josef Zihl
Effects of Spatial and Temporal Contiguity on the Acquisition of Spatial Information Thea B. Ghiselli-Crippa, Paul W. Munro
Acquisition in Autoshaping Sham Kakade, Peter Dayan
Robust Recognition of Noisy and Superimposed Patterns via Selective Attention Soo-Young Lee, Michael C. Mozer
Perceptual Organization Based on Temporal Dynamics Xiuwen Liu, DeLiang L. Wang
Information Factorization in Connectionist Models of Perception Javier R. Movellan, James L. McClelland
Graded Grammaticality in Prediction Fractal Machines Shan Parfitt, Peter Tiño, Georg Dorffner
Rules and Similarity in Concept Learning Joshua B. Tenenbaum
Evolving Learnable Languages Bradley Tonkes, Alan Blair, Janet Wiles
Learning Statistically Neutral Tasks without Expert Guidance Ton Weijters, Antal van den Bosch, Eric O. Postma
A Generative Model for Attractor Dynamics Richard S. Zemel, Michael C. Mozer
Recurrent Cortical Competition: Strengthen or Weaken? Péter Adorján, Lars Schwabe, Christian Piepenbrock, Klaus Obermayer
Effective Learning Requires Neuronal Remodeling of Hebbian Synapses Gal Chechik, Isaac Meilijson, Eytan Ruppin
Wiring Optimization in the Brain Dmitri B. Chklovskii, Charles F. Stevens
Optimal Sizes of Dendritic and Axonal Arbors Dmitri B. Chklovskii
Neural Representation of Multi-Dimensional Stimuli Christian W. Eurich, Stefan D. Wilke, Helmut Schwegler
Spiking Boltzmann Machines Geoffrey E. Hinton, Andrew D. Brown
Distributed Synchrony of Spiking Neurons in a Hebbian Cell Assembly David Horn, Nir Levy, Isaac Meilijson, Eytan Ruppin
Can VI Mechanisms Account for Figure-Ground and Medial Axis Effects? Zhaoping Li
Channel Noise in Excitable Neural Membranes Amit Manwani, Peter N. Steinmetz, Christof Koch
LTD Facilitates Learning in a Noisy Environment Paul W. Munro, Gerardina Hernández
Memory Capacity of Linear vs. Nonlinear Models of Dendritic Integration Panayiota Poirazi, Bartlett W. Mel
Predictive Sequence Learning in Recurrent Neocortical Circuits Rajesh P. N. Rao, Terrence J. Sejnowski
A Recurrent Model of the Interaction Between Prefrontal and Inferotemporal Cortex in Delay Tasks Alfonso Renart, Néstor Parga, Edmund T. Rolls
Information Capacity and Robustness of Stochastic Neuron Models Elad Schneidman, Idan Segev, Naftali Tishby
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, Michael P. Weisend
Population Decoding Based on an Unfaithful Model Si Wu, Hiroyuki Nakahara, Noboru Murata, Shun-ichi Amari
Spike-based Learning Rules and Stabilization of Persistent Neural Activity Xiaohui Xie, H. Sebastian Seung
A Variational Baysian Framework for Graphical Models Hagai Attias
Model Selection in Clustering by Uniform Convergence Bounds Joachim M. Buhmann, Marcus Held
Uniqueness of the SVM Solution Christopher J. C. Burges, David J. Crisp
Model Selection for Support Vector Machines Olivier Chapelle, Vladimir Vapnik
Dynamics of Supervised Learning with Restricted Training Sets and Noisy Teachers Anthony C. C. Coolen, C. W. H. Mace
A Geometric Interpretation of v-SVM Classifiers David J. Crisp, Christopher J. C. Burges
Efficient Approaches to Gaussian Process Classification Lehel Csató, Ernest Fokoué, Manfred Opper, Bernhard Schottky, Ole Winther
Potential Boosters? Nigel Duffy, David P. Helmbold
Bayesian Averaging is Well-Temperated Lars Kai Hansen
Regular and Irregular Gallager-zype Error-Correcting Codes Yoshiyuki Kabashima, Tatsuto Murayama, David Saad, Renato Vicente
Mixture Density Estimation Jonathan Q. Li, Andrew R. Barron
Statistical Dynamics of Batch Learning Song Li, K. Y. Michael Wong
Neural Computation with Winner-Take-All as the Only Nonlinear Operation Wolfgang Maass
Boosting with Multi-Way Branching in Decision Trees Yishay Mansour, David A. McAllester
Inference for the Generalization Error Claude Nadeau, Yoshua Bengio
Resonance in a Stochastic Neuron Model with Delayed Interaction Toru Ohira, Yuzuru Sato, Jack D. Cowan
Understanding Stepwise Generalization of Support Vector Machines: a Toy Model Sebastian Risau-Gusman, Mirta B. Gordon
Lower Bounds on the Complexity of Approximating Continuous Functions by Sigmoidal Neural Networks Michael Schmitt
Noisy Neural Networks and Generalizations Hava T. Siegelmann, Alexander Roitershtein, Asa Ben-Hur
The Entropy Regularization Information Criterion Alex J. Smola, John Shawe-Taylor, Bernhard Schölkopf, Robert C. Williamson
Probabilistic Methods for Support Vector Machines Peter Sollich
Algebraic Analysis for Non-regular Learning Machines Sumio Watanabe
Semiparametric Approach to Multichannel Blind Deconvolution of Nonminimum Phase Systems Liqing Zhang, Shun-ichi Amari, Andrzej Cichocki
Some Theoretical Results Concerning the Convergence of Compositions of Regularized Linear Functions Tong Zhang
Robust Full Bayesian Methods for Neural Networks Christophe Andrieu, João F. G. de Freitas, Arnaud Doucet
Independent Factor Analysis with Temporally Structured Sources Hagai Attias
Gaussian Fields for Approximate Inference in Layered Sigmoid Belief Networks David Barber, Peter Sollich
Modeling High-Dimensional Discrete Data with Multi-Layer Neural Networks Yoshua Bengio, Samy Bengio
Robust Neural Network Regression for Offline and Online Learning Thomas Briegel, Volker Tresp
Reconstruction of Sequential Data with Probabilistic Models and Continuity Constraints Miguel Á. Carreira-Perpiñán
Transductive Inference for Estimating Values of Functions Olivier Chapelle, Vladimir Vapnik, Jason Weston
The Nonnegative Boltzmann Machine Oliver B. Downs, David J. C. MacKay, Daniel D. Lee
Differentiating Functions of the Jacobian with Respect to the Weights Gary William Flake, Barak A. Pearlmutter
Local Probability Propagation for Factor Analysis Brendan J. Frey
Variational Inference for Bayesian Mixtures of Factor Analysers Zoubin Ghahramani, Matthew J. Beal
Bayesian Transduction Thore Graepel, Ralf Herbrich, Klaus Obermayer
Learning to Parse Images Geoffrey E. Hinton, Zoubin Ghahramani, Yee Whye Teh
Maximum Entropy Discrimination Tommi Jaakkola, Marina Meila, Tony Jebara
Topographic Transformation as a Discrete Latent Variable Nebojsa Jojic, Brendan J. Frey
An Improved Decomposition Algorithm for Regression Support Vector Machines Pavel Laskov
Algorithms for Independent Components Analysis and Higher Order Statistics Daniel D. Lee, Uri Rokni, Haim Sompolinsky
The Relaxed Online Maximum Margin Algorithm Yi Li, Philip M. Long
Bayesian Network Induction via Local Neighborhoods Dimitris Margaritis, Sebastian Thrun
Boosting Algorithms as Gradient Descent Llew Mason, Jonathan Baxter, Peter L. Bartlett, Marcus R. Frean
A Multi-class Linear Learning Algorithm Related to Winnow Chris Mesterharm
Invariant Feature Extraction and Classification in Kernel Spaces Sebastian Mika, Gunnar Rätsch, Jason Weston, Bernhard Schölkopf, Alex J. Smola, Klaus-Robert Müller
Approximate Inference A lgorithms for Two-Layer Bayesian Networks Andrew Y. Ng, Michael I. Jordan
Optimal Kernel Shapes for Local Linear Regression Dirk Ormoneit, Trevor Hastie
Large Margin DAGs for Multiclass Classification John C. Platt, Nello Cristianini, John Shawe-Taylor
The Infinite Gaussian Mixture Model Carl Edward Rasmussen
v-Arc: Ensemble Learning in the Presence of Outliers Gunnar Rätsch, Bernhard Schölkopf, Alex J. Smola, Klaus-Robert Müller, Takashi Onoda, Sebastian Mika
Nonlinear Discriminant Analysis Using Kernel Functions Volker Roth, Volker Steinhage
An Analysis of Turbo Decoding with Gaussian Densities Paat Rusmevichientong, Benjamin Van Roy
Support Vector Method for Novelty Detection Bernhard Schölkopf, Robert C. Williamson, Alex J. Smola, John Shawe-Taylor, John C. Platt
Better Generative Models for Sequential Data Problems: Bidirectional Recurrent Mixture Density Networks Mike Schuster
Greedy Importance Sampling Dale Schuurmans
Bayesian Model Selection for Support Vector Machines, Gaussian Processes and Other Kernel Classifiers Matthias Seeger
Leveraged Vector Machines Yoram Singer
Agglomerative Information Bottleneck Noam Slonim, Naftali Tishby
Training Data Selection for Optimal Generalization in Trigonometric Polynomial Networks Masashi Sugiyama, Hidemitsu Ogawa
Predictive App roaches for Choosing Hyperparameters in Gaussian Processes S. Sundararajan, S. Sathiya Keerthi
On Input Selection with Reversible Jump Markov Chain Monte Carlo Sampling Peter Sykacek
Building Predictive Models from Fractal Representations of Symbolic Sequences Peter Tiño, Georg Dorffner
The Relevance Vector Machine Michael E. Tipping
Support Vector Method for Multivariate Density Estimation Vladimir Vapnik, Sayan Mukherjee
Dual Estimation and the Unscented Transformation Eric A. Wan, Rudolph van der Merwe, Alex T. Nelson
Correctness of Belief Propagation in Gaussian Graphical Models of Arbitrary Topology Yair Weiss, William T. Freeman
A MCMC Approach to Hierarchical Mixture Modelling Christopher K. I. Williams
Data Visualization and Feature Selection: New Algorithms for Nongaussian Data Howard Hua Yang, John Moody
Manifold Stochastic Dynamics for Bayesian Learning Mark Zlochin, Yoram Baram
The Parallel Problems Server: an Interactive Tool for Large Scale Machine Learning Charles Lee Isbell Jr., Parry Husbands
An Oculo-Motor System with Multi-Chip Neuromorphic Analog VLSI Control Oliver Landolt, Steve Gyger
A Winner-Take-All Circuit with Controllable Soft Max Property Shih-Chii Liu
A Neuromorphic VLSI System for Modeling the Neural Control of Axial Locomotion Girish N. Patel, Edgar A. Brown, Stephen P. DeWeerth
Bifurcation Analysis of a Silicon Neuron Girish N. Patel, Gennady S. Cymbalyuk, Ronald L. Calabrese, Stephen P. DeWeerth
An Analog VLSI Model of Periodicity Extraction André van Schaik
An Oscillatory Correlation Frame work for Computational Auditory Scene Analysis Guy J. Brown, DeLiang L. Wang
Bayesian Modelling of fMRI lime Series Pedro A. d. F. R. Højen-Sørensen, Lars Kai Hansen, Carl Edward Rasmussen
Neural System Model of Human Sound Localization Craig T. Jin, Simon Carlile
Spectral Cues in Human Sound Localization Craig T. Jin, Anna Corderoy, Simon Carlile, André van Schaik
Broadband Direction-Of-Arrival Estimation Based on Second Order Statistics Justinian P. Rosca, Joseph Ó Ruanaidh, Alexander Jourjine, Scott Rickard
Constrained Hidden Markov Models Sam T. Roweis
Online Independent Component Analysis with Local Learning Rate Adaptation Nicol N. Schraudolph, Xavier Giannakopoulos
Speech Modelling Using Subspace and EM Techniques Gavin Smith, João F. G. de Freitas, Tony Robinson, Mahesan Niranjan
Search for Information Bearing Components in Speech Howard Hua Yang, Hynek Hermansky
Audio Vision: Using Audio-Visual Synchrony to Locate Sounds John R. Hershey, Javier R. Movellan
Bayesian Reconstruction of 3D Human Motion from Single-Camera Video Nicholas R. Howe, Michael E. Leventon, William T. Freeman
Emergence of Topography and Complex Cell Properties from Natural Images using Extensions of ICA Aapo Hyvärinen, Patrik O. Hoyer
An Information-Theoretic Framework for Understanding Saccadic Eye Movements Tai Sing Lee, Stella X. Yu
Learning Sparse Codes with a Mixture-of-Gaussians Prior Bruno A. Olshausen, K. Jarrod Millman
Hierarchical Image Probability (H1P) Models Clay Spence, Lucas C. Parra
Scale Mixtures of Gaussians and the Statistics of Natural Images Martin J. Wainwright, Eero P. Simoncelli
A SNoW-Based Face Detector Ming-Hsuan Yang, Dan Roth, Narendra Ahuja
Managing Uncertainty in Cue Combination Zhiyong Yang, Richard S. Zemel
Robust Learning of Chaotic Attractors Rembrandt Bakker, Jaap C. Schouten, Marc-Olivier Coppens, Floris Takens, C. Lee Giles, Cor M. van den Bleek
Image Representations for Facial Expression Coding Marian Stewart Bartlett, Gianluca Donato, Javier R. Movellan, Joseph C. Hager, Paul Ekman, Terrence J. Sejnowski
Low Power Wireless Communication via Reinforcement Learning Timothy X. Brown
Learning Informative Statistics: A Nonparametnic Approach John W. Fisher III, Alexander T. Ihler, Paul A. Viola
Kirchoff Law Markov Fields for Analog Circuit Design Richard M. Golden
Learning the Similarity of Documents: An Information-Geometric Approach to Document Retrieval and Categorization Thomas Hofmann
Constructing Heterogeneous Committees Using Input Feature Grouping: Application to Economic Forecasting Yuansong Liao, John E. Moody
From Coexpression to Coregulation: An Approach to Inferring Transcriptional Regulation among Gene Classes from Large-Scale Expression Data Eric Mjolsness, Tobias Mann, Rebecca Castaño, Barbara J. Wold
Churn Reduction in the Wireless Industry Michael C. Mozer, Richard H. Wolniewicz, David B. Grimes, Eric Johnson, Howard Kaushansky
Unmixing Hyperspectral Data Lucas C. Parra, Clay Spence, Paul Sajda, Andreas Ziehe, Klaus-Robert Müller
Application of Blind Separation of Sources to Optical Recording of Brain Activity Holger Schoner, Martin Stetter, Ingo Schießl, John E. W. Mayhew, Jennifer S. Lund, Niall McLoughlin, Klaus Obermayer
Reinforcement Learning for Spoken Dialogue Systems Satinder P. Singh, Michael J. Kearns, Diane J. Litman, Marilyn A. Walker
Image Recognition in Context: Application to Microscopic Urinalysis Xubo B. Song, Joseph Sill, Yaser S. Abu-Mostafa, Harvey Kasdan
Generalized Model Selection for Unsupervised Learning in High Dimensions Shivakumar Vaithyanathan, Byron Dom
Learning from User Feedback in Image Retrieval Systems Nuno Vasconcelos, Andrew Lippman
An Environment Model for Nonstationary Reinforcement Learning Samuel P. M. Choi, Dit-Yan Yeung, Nevin Lianwen Zhang
State Abstraction in MAXQ Hierarchical Reinforcement Learning Thomas G. Dietterich
Approximate Planning in Large POMDPs via Reusable Trajectories Michael J. Kearns, Yishay Mansour, Andrew Y. Ng
Actor-Critic Algorithms Vijay R. Konda, John N. Tsitsiklis
Bayesian Map Learning in Dynamic Environments Kevin P. Murphy
Policy Search via Density Estimation Andrew Y. Ng, Ronald Parr, Daphne Koller
Neural Network Based Model Predictive Control Stephen Piche, James D. Keeler, Greg Martin, Gene Boe, Doug Johnson, Mark Gerules
Reinforcement Learning Using Approximate Belief States Andres C. Rodriguez, Ronald Parr, Daphne Koller
Coastal Navigation with Mobile Robots Nicholas Roy, Sebastian Thrun
Learning Factored Representations for Partially Observable Markov Decision Processes Brian Sallans
Policy Gradient Methods for Reinforcement Learning with Function Approximation Richard S. Sutton, David A. McAllester, Satinder P. Singh, Yishay Mansour
Monte Carlo POMDPs Sebastian Thrun