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9780262112451

Advances in Neural Information Processing Systems 11

by
  • ISBN13:

    9780262112451

  • ISBN10:

    0262112450

  • Format: Hardcover
  • Copyright: 1999-06-04
  • Publisher: Bradford Books
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List Price: $20.75

Summary

The annual conference on Neural Information Processing Systems (NIPS) is the flagship conference on neural computation. It draws preeminent academic researchers from around the world and is widely considered to be a showcase conference for new developments in network algorithms and architectures. The broad range of interdisciplinary research areas represented includes computer science, neuroscience, statistics, physics, cognitive science, and many branches of engineering, including signal processing and control theory. Only about 30 percent of the papers submitted are accepted for presentation at NIPS, so the quality is exceptionally high. These proceedings contain all of the papers that were presented.

Table of Contents

Preface xv
NIPS Committees xvii
Reviewers xix
Part I Cognitive Science
Evidence for a Forward Dynamics Model in Human Adaptive Motor Control
3(7)
Nikhil Bhushan
Reza Shadmehr
Perceiving without Learning: From Spirals to Inside/Outside Relations
10(7)
Ke Chen
DeLiang L. Wang
A Model for Associative Multiplication
17(7)
G. Bjorn Christianson
Suzanna Becker
Facial Memory Is Kernel Density Estimation (Almost)
24(7)
Matthew N. Dailey
Garrison W. Cottrell
Thomas A. Busey
Multiple Paired Forward-Inverse Models for Human Motor Learning and Control
31(7)
Masahiko Haruno
Daniel M. Wolpert
Mitsuo Kawato
Utilizing Time: Asynchronous Binding
38(7)
Bradley C. Love
Mechanisms of Generalization in Perceptual Learning
45(7)
Zili Liu
Daphna Weinshall
A Principle for Unsupervised Hierarchical Decomposition of Visual Scenes
52(7)
Michael C. Mozer
Bayesian Modeling of Human Concept Learning
59(10)
Joshua B. Tenenbaum
Part II Neuroscience
Temporally Asymmetric Hebbian Learning, Spike Timing and Neural Response Variability
69(7)
L. F. Abbott
Sen Song
Contrast Adaptation in Simple Cells by Changing the Transmitter Release Probability
76(7)
Peter Adorjan
Klaus Obermayer
Where Does the Population Vector of Motor Cortical Cells Point during Reaching Movements?
83(7)
Pierre Baraduc
Emmanuel Guigon
Yves Burnod
Recurrent Cortical Amplification Produces Complex Cell Responses
90(7)
Frances S. Chance
Sacha B. Nelson
L. F. Abbott
Neuronal Regulation Implements Efficient Synaptic Pruning
97(7)
Gal Chechik
Isaac Meilijson
Eytan Ruppin
Divisive Normalization, Line Attractor Networks and Ideal Observers
104(7)
Sophie Deneve
Alexandre Pouget
Peter E. Latham
Synergy and Redundancy among Brain Cells of Behaving Monkeys
111(7)
Itay Gat
Naftali Tishby
Analyzing and Visualizing Single-Trial Event-Related Potentials
118(7)
Tzyy-Ping Jung
Scott Makeig
Marissa Westerfield
Jeanne Townsend
Eric Courchesne
Terrence J. Sejnowski
Spike-Based Compared to Rate-Based Hebbian Learning
125(7)
Richard Kempter
Wulfram Gerstner
J. Leo van Hemmen
Signal Detection in Noisy Weakly-Active Dendrites
132(7)
Amit Manwani
Christof Koch
The Role of Lateral Cortical Competition in Ocular Dominance Development
139(7)
Christian Piepenbrock
Klaus Obermayer
Multi-Electrode Spike Sorting by Clustering Transfer Functions
146(7)
Dmitry Rinberg
Hanan Davidowitz
Naftali Tishby
Modeling Surround Suppression in VI Neurons with a Statistically Derived Normalization Model
153(7)
Eero P. Simoncelli
Odelia Schwartz
Information Maximization in Single Neurons
160(7)
Martin Stemmler
Christof Koch
The Effect of Correlations on the Fisher Information of Population Codes
167(7)
Hyoungsoo Yoon
Haim Sompolinsky
Distributional Population Codes and Multiple Motion Models
174(9)
Richard S. Zemel
Peter Dayan
Part III Theory
Tractable Variational Structures for Approximating Graphical Models
183(7)
David Barber
Wim Wiegerinck
Almost Linear VC Dimension Bounds for Piecewise Polynomial Networks
190(7)
Peter L. Bartlett
Vitaly Maiorov
Ron Meir
Dynamics of Supervised Learning with Restricted Training Sets
197(7)
A. C. C. Coolen
David Saad
Dynamically Adapting Kernels in Support Vector Machines
204(7)
Nello Cristianini
Colin Campbell
John Shawe-Taylor
Phase Diagram and Storage Capacity of Sequence-Storing Neural Networks
211(7)
A. During
A. C. C. Coolen
D. Sherrington
Finite-Dimensional Approximation of Gaussian Processes
218(7)
Giancarlo Ferrari-Trecate
Christopher K. I. Williams
Manfred Opper
Linear Hinge Loss and Average Margin
225(7)
Claudio Gentile
Manfred K. Warmuth
Unsupervised and Supervised Clustering: The Mutual Information between Parameters and Observations
232(7)
Didier Herschkowitz
Jean-Pierre Nadal
Convergence of the Wake-Sleep Algorithm
239(7)
Shiro Ikeda
Shun-ichi Amari
Hiroyuki Nakahara
The Belief in TAP
246(7)
Yoshiyuki Kabashima
David Saad
Optimizing Classifers for Imbalanced Training Sets
253(7)
Grigoris Karakoulas
John Shawe-Taylor
Inference in Multilayer Networks via Large Deviation Bounds
260(7)
Michael Kearns
Lawrence Saul
Stationarity and Stability of Autoregressive Neural Network Processes
267(7)
Friedrich Leisch
Adrian Trapletti
Kurt Hornik
Computational Differences between Asymmetrical and Symmetrical Networks
274(7)
Zhaoping Li
Peter Dayan
A Precise Characterization of the Class of Languages Recognized by Neural Nets under Gaussian and Other Common Noise Distributions
281(7)
Wolfgang Maass
Eduardo D. Sontag
Direct Optimization of Margins Improves Generalization in Combined Classifiers
288(7)
Llew Mason
Peter L. Bartlett
Jonathan Baxter
On the Optimality of Incremental Neural Network Algorithms
295(7)
Ron Meir
Vitaly Maiorov
General Bounds on Bayes Errors for Regression with Gaussian Processes
302(7)
Manfred Opper
Francesco Vivarelli
Mean Field Methods for Classification with Gaussian Processes
309(7)
Manfred Opper
Ole Winther
On-Line Learning with Restricted Training Sets: Exact Solution as Benchmark for General Theories
316(7)
H. C. Rae
Peter Sollich
A. C. C. Coolen
Tight Bounds for the VC-Dimension of Piecewise Polynomial Networks
323(7)
Akito Sakurai
Shrinking the Tube: A New Support Vector Regression Algorithm
330(7)
Bernhard Scholkopf
Peter L. Bartlett
Alex J. Smola
Robert Williamson
Discontinuous Recall Transitions Induced by Competition Between Short-and Long-Range Interactions in Recurrent Networks
337(7)
N.S. Skantzos
C.F. Beckmann
A.C.C. Coolen
Learning Curves for Gaussian Processes
344(7)
Peter Sollich
A Theory of Mean Field Approximation
351(10)
Toshiyuki Tanaka
Part IV Algorithms and Architecture
Learning a Hierarchical Belief Network of Independent Factor Analyzers
361(7)
Hagai Attias
Semi-Supervised Support Vector Machines
368(7)
Kristin Bennett
Ayhan Demiriz
Lazy Learning Meets the Recursive Least Squares Algorithm
375(7)
Mauro Birattari
Gianluca Bontempi
Hugues Bersini
Bayesian PCA
382(7)
Christopher M. Bishop
Learning Multi-Class Dynamics
389(7)
Andrew Blake
Ben North
Michael Isard
Approximate Learning of Dynamic Models
396(7)
Xavier Boyen
Daphne Koller
Fisher Scoring and a Mixture of Modes Approach for Approximate Inference and Learning in Nonlinear State Space Models
403(7)
Thomas Briegel
Volker Tresp
Global Optimisation of Neural Network Models via Sequential Sampling
410(7)
Joao F. G. de Freitas
Mahesan Niranjan
Arnaud Doucet
Andrew H. Gee
Efficient Bayesian Parameter Estimation in Large Discrete Domains
417(7)
Nir Friedman
Yoram Singer
A Randomized Algorithm for Pairwise Clustering
424(7)
Yoram Gdalyahu
Daphna Weinshall
Michael Werman
Learning Nonlinear Dynamical Systems Using an EM Algorithm
431(7)
Zoubin Ghahramani
Sam T. Roweis
Classification on Pairwise Proximity Data
438(7)
Thore Graepel
Ralf Herbrich
Peter Bollmann-Sdorra
Klaus Obermayer
Outcomes of the Equivalence of Adaptive Ridge with Least Absolute Shrinkage
445(7)
Yves Grandvalet
Stephane Canu
Visualizing Group Structure
452(7)
Marcus Held
Jan Puzicha
Joachim M. Buhmann
Source Separation as a By-Product of Regularization
459(7)
Sepp Hochreiter
Jurgen Schmidhuber
Learning from Dyadic Data
466(7)
Thomas Hofmann
Jan Puzicha
Michael I. Jordan
Sparse Code Shrinkage: Denoising by Nonlinear Maximum Likelihood Estimation
473(7)
Aapo Hyvarinen
Patrik Hoyer
Erkki Oja
Restructuring Sparse High Dimensional Data for Effective Retrieval
480(7)
Charles Lee Isbell Jr.
Paul Viola
Exploiting Generative Models in Discriminative Classifiers
487(7)
Tommi S. Jaakkola
David Haussler
Maximum Conditional Likelihood via Bound Maximization and the CEM Algorithm
494(7)
Tony Jebara
Alex Pentland
A Polygonal Line Algorithm for Constructing Principal Curves
501(7)
Balazs Kegl
Adam Krzyzak
Tamas Linder
Kenneth Zeger
Unsupervised Classification with Non-Gaussian Mixture Models Using ICA
508(7)
Te-Won Lee
Michael S. Lewicki
Terrence J. Sejnowski
Learning a Continuous Hidden Variable Model for Binary Data
515(7)
Daniel D. Lee
Haim Sompolinsky
Neural Networks for Density Estimation
522(7)
Malik Magdon-Ismail
Amir Atiya
Exploratory Data Analysis Using Radial Basis Function Latent Variable Models
529(7)
Alan D. Marrs
Andrew R. Webb
Kernel PCA and De-Noising in Feature Spaces, Sebastian Mika
536(7)
Bernhard Scholkopf
Alex J. Smola
Klaus-Robert Muller
Matthias Scholz
Gunnar Ratsch
Very Fast EM-Based Mixture Model Clustering Using Multiresolution Kd-Trees
543(7)
Andrew W. Moore
Replicator Equations, Maximal Cliques, and Graph Isomorphism
550(7)
Marcello Pelillo
Using Analytic QP and Sparseness to Speed Training of Support Vector
557(7)
Machines
John C. Platt
Regularizing AdaBoost
564(7)
Gunnar Ratsch
Takashi Onoda
Klaus-Robert Muller
Boxlets: A Fast Convolution Algorithm for Signal Processing and Neural Network
571(7)
Patrice Y. Simard
Leon Bottou
Patrick Haffner
Yann Le Cun
Batch and On-Line Parameter Estimation of Gaussian Mixtures Based on the Joint Entropy
578(7)
Yoram Singer
Manfred K. Warmuth
Semiparametric Support Vector and Linear Programming Machines
585(7)
Alex J. Smola
Thilo T. Frieβ
Bernhard Scholkopf
Probabilistic Visualisation of High-Dimensional Binary Data
592(7)
Michael E. Tipping
SMEM Algorithm for Mixture Models
599(7)
Naonori Ueda
Ryohei Nakano
Zoubin Ghahramani
Geoffrey E. Hinton
Learning Mixture Hierachies
606(7)
Nuno Vasconcelos
Andrew Lippman
Discovering Hidden Features with Gaussian Processes Regression
613(7)
Francesco Vivarelli
Christopher K. I. Williams
The Bias-Variance Tradeoff and the Randomized GACV, Grace Wahba
620(7)
Xiwu Lin
Fangyu Gao
Dong Xiang
Ronald Klein
Barbara Klein
Basis Selection for Wavelet Regression
627(7)
Kevin R. Wheeler
Atam P. Dhawan
DTs: Dynamic Trees
634(7)
Christopher K. I. Williams
Nicholas J. Adams
Convergence Rates of Algorithms for Visual Search: Detecting Visual Contours
641(7)
A. L. Yuille
James M. Coughlan
Blind Separation of Filtered Sources Using State-Space Approach
648(9)
Liqing Zhang
Andrzej Cichocki
Part V Implementation
Analog VLSI Cellular Implementation of the Boundary Contour System
657(7)
Gert Cauwenberghs
James Waskiewicz
Active Noise Canceling Using Analog Neuro-Chip with On-Chip Learning Capability
664(7)
Jung-Wook Cho
Soo-Young Lee
A Micropower CMOS Adaptive Amplitude and Shift Invariant Vector Quantiser
671(7)
Richard J. Coggins
Raymond J. W. Wang
Marwan A. Jabri
Optimizing Correlation Algorithms for Hardware-Based Transient Classification
678(7)
R. Timothy Edwards
Gert Cauwenberghs
Fernando J. Pineda
VLSI Implementation of Motion Centroid Localization for Autonomous Navigation
685(7)
Ralph Etienne-Cummings
Viktor Gruev
Mohammed Abdel Ghani
A Neuromorphic Monaural Sound Localizer
692(7)
John G. Harris
Chiang-Jung Pu
Jose C. Principe
An Integrated Vision Sensor for the Computation of Optical Flow Singular Points
699(7)
Charles M. Higgins
Christof Koch
Computation of Smooth Optical Flow in a Feedback Connected Analog Network
706(7)
Alan Stocker
Rodney Douglas
A High Performance k-NN Classifier Using a Binary Correlation Matrix Memory
713(10)
Ping Zhou
Jim Austin
John Kennedy
Part VI Speech, Handwriting and Signal Processing
An Entropic Estimator for Structure Discovery
723(7)
Matthew Brand
Coding Time-Varying Signals Using Sparse, Shift-Invariant Representations
730(7)
Michael S. Lewicki
Terrence J. Sejnowski
Controlling the Complexity of HMM Systems by Regularization
737(7)
Christoph Neukirchen
Gerhard Rigoll
Maximum-Likelihood Continuity Mapping (MALCOM): An Alternative to HMMs
744(7)
David A. Nix
John E. Hogden
Markov Processes on Curves for Automatic Speech Recognition
751(10)
Lawrence Saul
Mazin Rahim
Part VII Visual Processing
A Phase Space Approach to Minimax Entropy Learning and the Minutemax Approximations
761(7)
James M. Coughlan
A. L. Yuille
Example-Based Image Synthesis of Articulated Figures
768(7)
Trevor Darrell
Learning to Estimate Scenes from Images
775(7)
William T. Freeman
Egon C. Pasztor
Learning to Find Pictures of People
782(7)
Sergey Ioffe
David Forsyth
Attentional Modulation of Human Pattern Discrimination Psychophysics Reproduced by a Quantitative Model
789(7)
Laurent Itti
Jochen Braun
Dale K. Lee
Christof Koch
A VI Model of Pop Out and Asymmetry in Visual Search
796(7)
Zhaoping Li
Support Vector Machines Applied to Face Recognition
803(7)
P. Jonathon Phillips
Learning Lie Groups for Invariant Visual Perception
810(7)
Rajesh P.N. Rao
Daniel L. Ruderman
General-Purpose Localization of Textured Image Regions
817(7)
Ruth Rosenholtz
Probabilistic Image Sensor Fusion
824(7)
Ravi K. Sharma
Todd K. Leen
Misha Pavel
Orientation, Scale, and Discontinuity as Emergent Properties of Illusory Contour
831(7)
Shape
Karvel K. Thornber
Lance R. Williams
Classification in Non-Metric Spaces
838(9)
Daphna Weinshall
David W. Jacobs
Yoram Gdalyahu
Part VIII Applications
Making Templates Rotationally Invariant: An Application to Rotated Digit Recognition
847(7)
Shumeet Baluja
Probabilistic Modeling for Face Orientation Discrimination: Learning from Labeled and Unlabeled Data
854(7)
Shumeet Baljua
Adding Constrained Discontinuities to Gaussian Process Models of Wind Fields
861(7)
Dan Cornford
Ian T. Nabney
Christopher K.I. Williams
Vertex Identification in High Energy Physics Experiments
868(7)
Gideon Dror
Halina Abramowicz
David Horn
Familiarity Discrimination of Radar Pulses
875(7)
Eric Granger
Stephen Grossberg
Mark A. Rubin
William W. Streilein
Fast Neural Network Emulation of Dynamical Systems for Computer Animation
882(7)
Radek Grzeszczuk
Demetri Terzopoulos
Geoffrey E. Hinton
Call-Based Fraud Detection in Mobile Communication Networks Using a Hierarchical Regime-Switching Model
889(7)
Jaakko Hollmen
Volker Tresp
Graph Matching for Shape Retrieval
896(7)
Benoit Huet
Andrew D. J. Cross
Edwin R. Hancock
Scheduling Straight-Line Code Using Reinforcement Learning and Rollouts
903(7)
Amy McGovern
Eliot Moss
Bayesian Modeling of Facial Similarity
910(7)
Baback Moghaddam
Tony Jebara
Alex Pentland
Reinforcement Learning for Trading
917(7)
John Moody
Matthew Saffell
Graphical Models for Recognizing Human Interactions
924(7)
Nuria M. Oliver
Barbara Rosario
Alex Pentland
Independent Component Analysis of Intracellular Calcium Spike Data
931(7)
Klaus Prank
Julia Borger
Alexander von zur Muhlen
Georg Brabant
Christof Schofl
Applications of Multi-Resolution Neural Networks to Mammography
938(7)
Clay D. Spence
Paul Sajda
Robot Docking Using Mixtures of Gaussians
945(7)
Matthew M. Williamson
Roderick Murray-Smith
Volker Hansen
Using Collective Intelligence to Route Internet Traffic
952(9)
David H. Wolpert
Kagan Tumer
Jeremy Frank
Part IX Control, Navigation and Planning
Robust, Efficient, Globally-Optimized Reinforcement Learning with the Parti-Game Algorithm
961(7)
Mohammad A. Al-Ansari
Ronald J. Williams
Gradient Descent for General Reinforcement Learning
968(7)
Leemon Baird
Andrew W. Moore
Non-Linear PI Control Inspired by Biological Control Systems
975(7)
Lyndon J. Brown
Gregory E. Gonye
James S. Schwaber
Optimizing Admission Control while Ensuring Quality of Service in Multimedia Networks via Reinforcement Learning
982(7)
Timothy X. Brown
Hui Tong
Satinder Singh
Viewing Classifier Systems as Model Free Learning in POMDPs
989(7)
Akira Hayashi
Nobuo Suematsu
Finite-Sample Convergence Rates for Q-Learning and Indirect Algorithms
996(7)
Michael Kearns
Satinder Singh
Exploring Unknown Environments with Real-Time Search or Reinforcement Learning
1003(7)
Sven Koenig
The Effect of Eligibility Traces on Finding Optimal Memoryless Policies in Partially Observable Markov Decision Processes
1010(7)
John Loch
Learning Instance-Independent Value Functions to Enhance Local Search
1017(7)
Robert Moll
Andrew G. Barto
Theodore J. Perkins
Richard S. Sutton
Barycentric Interpolators for Continuous Space and Time Reinforcement Learning
1024(7)
Remi Munos
Andrew W. Moore
Risk Sensitive Reinforcement Learning
1031(7)
Ralph Neuneier
Oliver Mihatsch
Coordinate Transformation Learning of Hand Position Feedback Controller by Using Change of Position Error Norm
1038(7)
Eimei Oyama
Susumu Tachi
Learning Macro-Actions in Reinforcement Learning
1045(7)
Jette Randlov
Reinforcement Learning Based on On-Line EM Algorithm
1052(7)
Masa-aki Sato
Shin Ishii
A Reinforcement Learning Algorithm in Partially Observable Environments Using Short-Term Memory
1059(7)
Nobuo Suematsu
Akira Hayashi
Improved Switching among Temporally Abstract Actions
1066(7)
Richard S. Sutton
Satinder Singh
Doina Precup
Balaraman Ravindran
Experimental Results on Learning Stochastic Memoryless Policies for Partially Observable Markov Decision Processes
1073(8)
John K. Williams
Satinder Singh
Index of Authors 1081(4)
Keyword Index 1085

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