NIPS Online: Table of Contents Vol. 0-13

Jump to:
Volume 0
NIPS 1987
Volume 1
NIPS 1988
Volume 2
NIPS 1989
Volume 3
NIPS 1990
Volume 4
NIPS 1991
Volume 5
NIPS 1992
Volume 6
NIPS 1993
Volume 7
NIPS 1994
Volume 8
NIPS 1995
Volume 9
NIPS 1996
Volume 10
NIPS 1997
Volume 11
NIPS 1998
Volume 12
NIPS 1999
Volume 12
NIPS 2000
 

NIPS'1987 Volume 0 - Table of Contents
Dana Anderson (ed), American Institute of Physics (1988)
i Title Pages
v Introduction
vii Table of Contents
0001 Connectivity Versus Entropy
Yaser S. Abu-Mostafa
0009 Stochastic Learning Networks and their Electronic Implementation
Joshua Alspector, Robert B. Allen, Victor Hu, and Srinagesh Satyanarayana
0022 Learning on a General Network
Amir F. Atiya
0031 An Artificial Neural Network for Spatio-Temporal Bipolar Patterns: Application to Phoneme Classification
Les E. Atlas, Toshiteru Homma, and Robert J. Marks II
0041 On Properties of Networks of Neuron-Like Elements
Pierre Baldi and Santosh S. Venkatesh
0052 Supervised Learning of Probability Distributions by Neural Networks
Eric B. Baum and Frank Wilczek
0062 Centric Models of the Orientation Map in Primary Visual Cortex
William Baxter and Bruce Dow
0072 Analysis and Comparison of Different Learning Algorithms for Pattern Association Problems
J. Bernasconi
0082 Simulations Suggest Information Processing Roles for the Diverse Currents in Hippocampal Neurons
Lyle J. Borg-Graham
0095 Optimal Neural Spike Classification
James M. Bower and Amir F. Atiya
0103 Neural Networks for Template Matching: Application to Real-Time Classification of the Action Potentials of Real Neurons
James M. Bower, Yiu-fai Wong, and Jashojiban Banik
0114 A Computer Simulation of Olfactory Cortex with Functional Implications for Storage and Retrieval of Olfactory Information
James M. Bower and Matthew A. Wilson
0127 Neural Network Implementation Approaches for the Connection Machine
Nathan H. Brown, Jr.
0137 On the Power of Neural Networks for Solving Hard Problems
Jehoshua Bruck and Joseph W. Goodman
0144 Speech Recognition Experiments with Perceptrons
David J. Burr
0154 Presynaptic Neural Information Processing
L. Richard Carley
0164 Mathematical Analysis of Learning Behavior of Neuronal Models
John Y. Cheung and Massoud Omidvar
0174 A Neural Network Classifier Based on Coding Theory
Tzi-Dar Chiueh and Rodney Goodman
0184 The Capacity of the Kanerva Associative Memory is Exponential
P. A. Chou
0192 Phase Transitions in Neural Networks
Joshua Chover
0201 New Hardware for Massive Neural Networks
D. D. Coon and A. G. U. Perera
0211 High Density Associative Memories
Amir Dembo and Ofer Zeitouni
0219 Network Generality, Training Required, and Precision Required
John S. Denker and Ben S. Wittner
0223 'Ensemble' Boltzmann Units have Collective Computational Properties like those of Hopfield and Tank Neurons
Mark Derthick and Joe Tebelskis
0233 High Order Neural Networks for Efficient Associative Memory Design
G. Dreyfus, I. Guyon, J. P. Nadal, and L. Personnaz
0242 The Sigmoid Nonlinearity in Prepyriform Cortex
Frank H. Eeckman
0249 Hierarchical Learning Control--An Approach with Neuron-Like Associative Memories
E. Ersu and H. Tolle
0262 On Tropistic Processing and Its Applications
Manuel F. Fernández
0270 Correlational Strength and Computational Algebra of Synaptic Connections Between Neurons
Eberhard E. Fetz
0278 The Hopfield Model with Multi-Level Neurons
Michael Fleisher
0290 Cycles: A Simulation Tool for Studying Cyclic Neural Networks
MichaelT. Gately
0297 Temporal Patterns of Activity in Neural Networks
Paolo Gaudiano
0301 Encoding Geometric Invariances in Higher-Order Neural Networks
C. Lee Giles, R. D. Griffin, and T. Maxwell
0310 Probabilistic Characterization of Neural Model Computations
Richard M. Golden
0317 Partitioning of Sensory Data by a Cortical Network
Richard Granger, Jose Ambros-Ingerson, Howard Henry, and Gary Lynch
0338 The Connectivity Analysis of Simple Association
Dan Hammerstrom
0348 Minkowski-r Back-Propagation: Learning in Connectionist Models with Non-Euclidian Error Signals
Stephen J. Hanson and David J. Burr
0358 Learning Representations by Recirculation
Geoffrey E. Hinton and James L. McClelland
0367 Schema for Motor Control Utilizing a Network Model of the Cerebellum
James C. Houk
0377 Experimental Demonstrations of Optical Neural Computers
Ken Hsu, David Brady, and Demetri Psaltis
0387 Neural Net and Traditional Classifiers
William Y. Huang and Richard P. Lippmann
0397 An Optimization Network for Matrix Inversion
Ju-Seog Jang, Soo-Young Lee, and Sang-Yung Shin
0402 How the Catfish Tracks Its Prey: An Interactive 'Pipelined' Processing System May Direct Foraging via Reticulospinal Neurons
Jagmeet S. Kanwal
0412 Capacity for Patterns and Sequences in Kanerva's SDM as Compared to Other Associative Memory Models
James D. Keeler
0422 Computing Motion Using Resistive Networks
Christof Koch, Jin Luo, Carver Mead, and James Hutchinson
0432 Performance Measures for Associative Memories that Learn and Forget
Anthony Kuh
0442 How Neural Nets Work
Alan Lapedes and Robert Farber
0457 Distributed Neural Information Processing in the Vestibulo-Ocular System
Clifford Lau and Vicente Honrubia
0467 Spontaneous and Information-Triggered Segments of Series of Human Brain Electric Field Maps
Dietrich Lehmann, D. Brandeis, A. Horst, H. Ozaki, and I. Pal
0474 Optimization with Artificial Neural Network Systems: A Mapping Principle and a Comparison to Gradient Based Methods
Harrison MonFook Leong
0485 Towards an Organizing Principle for a Layered Perceptual Network
Ralph Linsker
0495 Reflexive Associative Memories
Hendricus G. Loos
0505 Connecting to the Past
Bruce MacDonald
0515 Microelectronic Implementations of Connectionist Neural Networks
Stuart Mackie, Hans P. Graf, Daniel B. Schwartz, and John S. Denker
0524 Basins of Attraction for Electronic Neural Networks
Charles M. Marcus and R. M. Westervelt
0534 The Performance of Convex Set Projection Based Neural Networks
Robert J. Marks II, Les E. Atlas, Seho Oh, and James A. Ritcey
0544 MURPHY: A Robot that Learns by Doing
Bartlett W. Mel
0554 Stability Results for Neural Networks
A. N. Michel, J. A. Farrell, and W. Porod
0564 Programmable Synaptic Chip for Electronic Neural Networks
Alexander Moopenn, H. Langenbacher, A. P. Thakoor, and S. K. Khanna
0573 Bit-Serial Neural Networks
Alan F. Murray, Anthony V. W. Smith, and Zoe F. Butler
0584 Phasor Neural Networks
Andre J. Noest
0592 A Trellis-Structured Neural Network
Thomas Petsche and Bradley W. Dickinson
0602 Generalization of Back propagation to Recurrent and Higher Order Neural Networks
Fernando J. Pineda
0612 Constrained Differential Optimization
John C. Platt and Alan H. Barr
0622 Learning a Color Algorithm from Examples
Tomaso A. Poggio and Anya C. Huribert
0632 Static and Dynamic Error Propagation Networks with Application to Speech Coding
A. J. Robinson and F. Failside
0642 Learning by State Recurrence Detection
Bruce E. Rosen, James M. Goodwin, and Jacques J. Vidal
0652 Scaling Properties of Coarse-Coded Symbol Memories
Ronald Rosenfeld and David S. Touretzky
0662 An Adaptive and Heterodyne Filtering Procedure for the Imaging of Moving Objects
F. H. Schuling, H. A. K. Mastebroek, and W. H. Zaagman
0674 Pattern Class Degeneracy in an Unrestricted Storage Density Memory
Christopher L. Scofield, Douglas L. Reilly, Charles Elbaum, and Leon N. Cooper
0683 A Mean Field Theory of Layer IV of Visual Cortex and Its Application to Artificial Neural Networks
Christopher L. Scofield
0693 Teaching Artificial Neural Systems to Drive: Manual Training Techniques for Autonomous Systems
J. F. Shepanski and S. A. Macy
0701 Discovering Structure from Motion in Monkey, Man and Machine
Ralph M. Siegel
0709 Time-Sequential Self-Organization of Hierarchical Neural Networks
Ronald H. Silverman and Andrew S. Noetzel
0715 A Computer Simulation of Cerebral Neocortex: Computational Capabilities of Nonlinear Neural Networks
Alexander Singer and John P. Donoghue
0730 Analysis of Distributed Representation of Constituent Structure in Connectionist Systems
Paul Smolensky
0740 Spatial Organization of Neural Networks: A Probabilistic Modeling Approach
Andreas Stafylopatis, M. Dikaiakos, and D. Kontoravdis
0750 A Dynamical Approach to Temporal Pattern Processing
W. Scott Stornetta, Tad Hogg, and Bernardo A. Huberman
0760 A Novel Net that Learns Sequential Decision Process
G. Z. Sun, Y. C. Lee, and H. H. Chen
0767 Self-Organization of Associative Database and Its Applications
Hisashi Suzuji and Suguru Arimoto
0775 A Neural-Network Solution to the Concentrator Assignment Problem
Gene A. Tagliarini and Edward W. Page
0783 Using Neural Networks to Improve Cochlear Implant Speech Perception
Manoel F. Tenorio
0794 A 'Neural' Network that Learns to Play Backgammon
Gerald Tesauro and T. J. Sejnowski
0804 Introduction to a System for Implementing Neural Net Connections on SIMD Architectures
Sherryl Tomboulian
0814 Neuromorphic Networks Based on Sparse Optical Orthogonal Codes
Mario P. Vecchi and Jawad A. Salehi
0824 Synchronization in Neural Nets
Jacques J. Vidal and John Haggerty
0830 Invariant Object Recognition Using a Distributed Associative Memory
Harry Wechsler and George Lee Zimmerman
0840 Learning in Networks of Nondeterministic Adaptive Logic Elements
Richard C. Windecker
0850 Strategies for Teaching Layered Networks Classification Tasks
Ben S. Wittner and John S. Denker
0860 A Method for the Design of Stable Lateral Inhibition Networks that is Robust in the Presence of Circuit Parasitics
John L. Wyatt, Jr. and D. L. Standley
0869 Author Index

NIPS'1988 Volume 1 : Table of Contents
David Touretzky (ed), Morgan-Kaufmann (1989)
i Preface
iii Table of Contents

PART I: LEARNING AND GENERALIZATION

0002 Constraints on Adaptive Networks for Modeling Human Generalization
Mark A. Gluck, M. Pavel and Van Henkle
0011 An Optimality Principle for Unsupervised Learning
Terence D. Sanger
0020 Associative Learning via Inhibitory Search
David H. Ackley
0029 Fast Learning in Multi-Resolution Hierarchies
John Moody
0040 Efficient Parallel Learning Algorithms for Neural Networks
Alan H. Kramer and A. Sangiovanni-Vincentelli
0049 Mapping Classifier Systems Into Neural Networks
Lawrence Davis
0057 Self Organizing Neural Networks for the Identification Problem
Manoel Fernando Tenorio and Wei-Tsih Lee
0065 Linear Learning: Landscapes and Algorithms
Pierre Baldi
0073 Learning by Choice of Internal Representations
Tal Grossman, Ronny Meir and Eytan Domany
0081 What Size Net Gives Valid Generalization?
Eric B. Baum and David Haussler
0091 Optimization by Mean Field Annealing
GriffBilbro, Reinhold Mann, Thomas K Miller, Wesley E. Snyder, David E. Van den Bout and Mark Whita
0099 Connectionist Learning of Expert Preferences by Comparison Training
Gerald Tesauro
0107 Skeletonization: A Technique for Trimming the Fat from a Network via Relevance Assessment
Michael C. Mozer and Paul Smolensky
0116 The Boltzmann Perceptron Network: A Multi-Layered Feed-Forward Network Equivalent to the Boltzmann Machine
Eyal Yair and Allen Gersho
0124 Adaptive Neural Net Preprocessing for Signal Detection in Non-Gaussian Noise
Richard P. Lippmann and Paul Beckman
0133 Training Multilayer Perceptrons with the Extended Kalman Algorithm
Sizarad Singhal and Lance Wu
0141 GEMINI: Gradient Estimation Through Matrix Inversion After Noise Injection
Yann Le Cun, Conrad C. Galland and Geoffrey E. Hinton
0149 Fixed Point Analysis for Recurrent Networks
Patrice Y. Simard, Mary B. Ottaway and Dana H. Ballard
0160 Scaling and Generalization in Neural Networks: A Case Study
Subutai Ahmad and Gerald Tesauro
0169 Does the Neuron "Learn" Like the Synapse?
Raoul Tawel
0177 Comparing Biases for Minimal Network Construction with Back-Propagation
Stephen Jose Hanson and Lorien Y. Pratt
0186 An Application of the Principle of Maximum Information Preservation to Linear Systems
Ralph Linsker

PART II: APPLICATION

0195 Learning with Temporal Derivatives in Pulse-Coded Neuronal Systems
David B. Parker, Mark Gluck and Eric S. Reifsnider
0206 Applications of Error Back-Propagation to Phonetic Classification
Hong C. Leung and Victor W. Zue
0215 Consonant Recognition by Modular Construction of Large Phonemic Time-Delay Neural Networks
Alex Waibel
0224 Use of Multi-Layered Networks for Coding Speech with Phonetic Features
Yoshua Bengio, Regis Cardin, Renato De Mori and Piero Cosi
0232 Speech Production Using A Neural Network with a Cooperative Learning Mechanism
Mitsuo Komura and Akio Tanaka
0240 Temporal Representations in a Connectionist Speech System
Erich J. Smythe
0248 A Connectionist Expert System that Actually Works
Richard Fozzard, Gary Bradshaw and Louis Ceci
0256 An Information Theoretic Approach to Rule-Based Connectionist Expert Systems
Rodney M. Goodman, John W. Miller and Padhraic Smyth
0264 Neural Approach for TV Image Compression Using a Hopfleld Type Network
Martine Naillon and Jean-Bernard Theeten
0272 Neural Net Receivers in Multiple-Access Communications
Bernd-Peter Paris, Geoffrey Orsak, Mahesh Varanasi and Behnaam Aazhang
0281 Performance of Synthetic Neural Network Classification of Noisy Radar Signals
S. C. Ahalt, F. D. Garber, I. Jouny and A. K. Krishnamurthy
0289 Neural Analog Diffusion-Enhancement Layer and Spatio-Temporal Grouping in Early Vision
Allen M. Waxman, Michael Seibert, Robert Cunningham and Jian Wu
0297 A Network for Image Segmentation Using Color
Anya Hurlbert and Tomaso Poggio
0305 ALVINN: An Autonomous Land Vehicle in a Neural Network
Dean A. Pomerleau
0314 Neural Network Star Pattern Recognition for Spacecraft Attitude Determination and Control
Phillip Alvelda, A. Miguel San Martin
0323 Neural Network Recognizer for Hand-Written Zip Code Digits
J. S. Denker, W. R. Gardner, H. P. Graf, D. Henderson, R. E. Howard, W. Hubbard, L. D. Jackel, H. S. Baird and I. Guyon
0332 Neural Networks that Learn to Discriminate Similar Kanji Characters
Yoshihiro Mori and Kazuhiko Yokosawa
0340 Backpropagation and Its Application to Handwritten Signature Verification
Timothy S. Wilkinson, Dorothy A. Mighell and Joseph W. Goodman
0348 Further Explorations in Visually-Guided Reaching: Making MURPHY Smarter
Bartlett W. Mel

PART III: NEUROBIOLOGY

0356 Using Backpropagation with Temporal Windows to Learn the Dynamics of the CMU Direct-Drive Arm II
K. Y. Goldberg and B. A. Pearlmutter
0366 Neuronal Maps for Sensory-Motor Control in the Barn Owl
C. D. Spence, J. C. Pearson, J. J. Gelfand, R. M. Peterson and W. E. Sullivan
0375 Models of Ocular Dominance Column Formation: Analytical and Computational Results
Kenneth D. Miller, Joseph B. Keller and Michael P. Stryker
0384 Modeling Small Oscillating Biological Networks in Analog VLSI
Sylvie Ryckebusch, James M. Bower, and Carver Mead
0394 Storing Covariance by the Associative Long-Term Potentiation and Depression of Synaptic Strengths in the Hippocampus
Patric K Stanton and Terrence J. Sejnowski
0402 Modeling the Olfactory Bulb-Coupled Nonlinear Oscillators
Zhaoping Li and J. J. Hopfield
0410 Neural Control of Sensory Acquisition: The Vestibulo-Ocular Reflex
Michael G. Paulin, Mark E. Nelson and James M. Bower
0419 Computer Modeling of Associative Learning
Daniel L. Alkon, Francis Quek and Thomas P. Vogl
0436 Simulation and Measurement of the Electric Fields Generated by Weakly Electric Fish
Brian Rasnow, Christopher Assad, Mark E. Nelson and James M. Bower
0444 A Model for Resolution Enhancement (Hyperacuity) in Sensory Representation
Jun Zhang and John P. Miller
0451 Theory of Self-Organization of Cortical Maps
Shigeru Tanaka
0459 A Bifurcation Theory Approach to the Programming of Periodic Attractors in Network Models of Olfactory Cortex
Bill Baird
0468 Learning the Solution to the Aperture Problem for Pattern Motion with a Hebb Rule
Martin L Sereno
0477 A Computationally Robust Anatomical Model for Retinal Directional Selectivity
Norberto M. Grzywacz and Franklin R. Amthor

PART IV: STRUCTURED NETWORKS

0485 GENESIS: A System for Simulating Neural Networks
Matthew A Wilson, Upinder S. Bhalla, John D. Uhley and James M. Bower
0494 Training a 3-Node Neural Network is NP-Complete
Avrim Blum and Ronald L. Rivest
0502 Links Between Markov Models and Multilayer Perceptrons
H. Bourlard and C. J. Wellekens
0511 Convergence and Pattern-Stabilization in the Boltzmann Machine
Moshe Kam and Roger Cheng
0519 A Back-Propagation Algorithm with Optimal Use of Hidden Units
Yves Chauvin
0527 Implications of Recursive Distributed Representations
Jordan B. Pollack
0537 A Massively Parallel Self-Tuning Context-Free Parser
Eugene Santos Jr
0545 Dynamic, Non-Local Role Bindings and Inferencing in a Localist Network for Natural Language Understanding
Trent E. Lange and Michael G. Dyer
0553 Spreading Activation over Distributed Microfeatures
James Hendler
0560 A Model of Neural Oscillator for a Unified Submodule
A. B. Kirillov, G. N. Borisyuk, R. M. Borisyuk, Ye. I. Kovalenko, V. I. Makarenko, V. A. Chulaevsky and V. I. Kryukov
0568 Dynamics of Analog Neural Networks with Time Delay
C. M. Marcus and R. M. Westervelt
0577 Heterogeneous Neural Networks for Adaptive Behavior in Dynamic Environments
Randall D. Beer, Hillel J. Chiel and Leon S. Sterling
0586 Statistical Prediction with Kanerva's Sparse Distributed Memory
David Rogers
0594 Range Image Restoration Using Mean Field Annealing
Gniff L. Bilbro and Wesley E. Snyder
0602 Automatic Local Annealing
Jared Leinbach
0610 "Neurolocator", A Model of Attention
V. I. Kryukov
0618 Neural Networks for Model Matching and Perceptual Organization
Eric Mjolsness, Gene Gindi and P. Anandan
0626 Analyzing the Energy Landscapes of Distributed Winner-Take-All Networks
David S. Touretzky
0634 On the K-Winners-Take-All Network
E. Majani, R. Erlanson and Y. Abu-Mostafa
0643 Learning Sequential Structure in Simple Recurrent Networks
David Servan-Schreiber, Axel Cleeremans and James L. McClelland

PART V: IMPLEMENTATION

0653 An Adaptive Network That Learns Sequences of Transitions
C. L. Winter
0662 A Passive Shared Element Analog Electrical Cochlea
David Feld, Joe Eisenberg and Edwin Lewis
0671 Programmable Analog Pulse-Firing Neural Networks
Alister Hamilton, Alan F. Murray and Lionel Tarassenko
0678 A Low-Power CMOS Circuit Which Emulates Temporal Electrical Properties of Neurons
Jack L. Meador and Clint S. Cole
0687 An Analog VLSI Chip for Thin-Plate Surface Interpolation
John G. Harris
0695 Analog Implementation of Shunting Neural Networks
Bahram Nabet, Robert B. Darling and Robert B. Pinter
0703 Winner-Take-All Networks of O(N) Complexity
J. Lazzaro, S. Ryckebusch, M. A Mahowald and C. A. Mead
0712 A Programmable Analog Neural Computer and Simulator
Paul Mueller, Jan Van den Spiegel, David Blackman, Timothy Chiu, Thomas Clare, Joseph Dao, Christopher Donham, Tzu-pu Hsieh and Marc Loinaz
0720 An Electronic Photoreceptor Sensitive to Small Changes in Intensity
T. Delbruck and C. A. Mead
0728 Digital Realisation of Self-Organising Maps
Martin J. Johnson, Nigel M. Allinson and Kevin J. Moon
0739 An Analog Self-Organizing Neural Network Chip
James R. Mann and Sheldon Gilbert
0748 Performance of a Stochastic Learning Microchip
Joshua Alspector, Bhusan Gupta and Robert B. Allen
0761 Adaptive Neural Networks Using MOS Charge Storage
D. B. Schwartz, R. E. Howard and W. E. Hubbard
0769 A Self-Learning Neural Network
A Hartstein and R. H. Koch
0777 Training a Limited-Interconnect, Synthetic Neural IC
M. R. Walker, S. Haghighi, A Afghan and L. A Akers

APPENDIX: SUMMARIES OF INVITED TALKS

0785 Electronic Receptors for Tactile/Haptic Sensing
Andreas G. Andreou
0794 Neural Architecture
Valentino Braitenbeng
0795 Song Learning in Birds
M. Konishi
0796 Speech Recognition: Statistical and Neural Information Processing Approaches
John S. Bridle
0802 Cricket Wind Detection
John P. Miller
0809 Author Index
0813 Subject Index

NIPS'1989 Volume 2 : Table of Contents
David Touretzky (ed), Morgan-Kaufmann (1990)
i Title Pages
v Table of Contents
xiii Preface

PART I: NEUROSCIENCE

0002 Acoustic-Imaging Computations by Echolocating Bats: Unification of Diversely-Represented Stimulus Features into Whole Images
James A. Simmons (Invited Talk)
0010 The Computation of Sound Source Elevation in the Barn Owl
Clay D. Spence and John C. Pearson
0018 Mechanisms for Neuromodulation of Biological Neural Networks
Ronald M. Harris-Warrick
0028 Neural Network Analysis of Distributed Representations of Dynamical Sensory-Motor Transformations in the Leech
Shawn R. Lockery, Yan Fang and Terrence J. Sejnowski
0036 Reading a Neural Code
William Bialek, Fred Rieke, R. R. de Ruyter van Steveninck and David Warland
0044 Neural Implementation of Motivated Behavior: Feeding in an Artificial Insect
Randall D. Beer and Hillel J. Chiel
0052 Neural Network Simulation of Somatosensory Representational Plasticity
Kamil A. Grajski and Michael M. Merzenich
0060 Computational Efficiency: A Common Organizing Principle for Parallel Computer Maps and Brain Maps?
Mark E. Nelson and James M. Bower
0068 Associative Memory in a Simple Model of Oscillating Cortex
Bill Baird
0076 Collective Oscillations in the Visual Cortex
Daniel Kammen, Christof Koch and Philip J. Holmes
0084 Computer Simulation of Oscillatory Behavior in Cerebral Cortical Networks
Matthew A. Wilson and James M. Bower
0092 Development and Regeneration of Eye-Brain Maps: A Computational Model
J.D. Cowan and A.E. Friedman
0100 The Effect of Catecholamines on Performance: From Unit to System Behavior
David Servan-Schreiber, Harry Printz and Jonathan D. Cohen
0109 Non-Boltzmann Dynamics in Networks of Spiking Neurons
Michael C. Crair and William Bialek
0117 A Computer Modeling Approach to Understanding the Inferior Olive and Its Relationships to the Cerebellar Cortex in Rats
Maurice Lee and James M. Bower
0125 Can Simple Cells Learn Curves? A Hebbian Model in a Structured Environment
William R. Softky and Daniel M. Kammen
0133 Note on Development of Modularity in Simple Cortical Models
Alex Chernjavsky and John Moody
0141 Effects of Firing Synchrony on Signal Propagation in Layered Networks
G.T. Kenyon, E.E. Fetz and R.D. Puff
0149 A Systematic Study of the Input/Output Properties of a 2 Compartment Model Neuron With Active Membranes
Paul Rhodes

PART II: SPEECH AND SIGNAL PROCESSING

0160 Analytic Solutions to the Formation of Feature-Analysing Cells of a Three-Layer Feedforward Visual Information Processing Neural Net
D.S. Tang
0168 Practical Characteristics of Neural Network and Conventional Pattern Classifiers on Artificial and Speech Problems
Yuchun Lee and Richard P. Lippmann
0178 Dimensionality Reduction and Prior Knowledge in E-Set Recognition
Kevin J. Lang and Geoffrey E. Hinton
0186 A Continuous Speech Recognition System Embedding MLP into HMM
Herve Bourlard and Nelson Morgan
0194 HMM Speech Recognition with Neural Net Discrimination
William Y. Huang and Richard P. Lippmann
0203 Connectionist Architectures for Multi-Speaker Phoneme Recognition
John B. Hampshire II and Alex Waibel
0211 Training Stochastic Model Recognition Algorithms as Networks can Lead to Maximum Mutual Information Estimation of Parameters
John S. Bridle
0218 Speaker Independent Speech Recognition with Neural Networks and Speech Knowledge
Yoshua Bengio, Renato De Mori and Regis Cardin
0226 The Effects of Circuit Integration on a Feature Map Vector Quantizer
Jim Mann
0232 Combining Visual and Acoustic Speech Signals with a Neural Network Improves Intelligibility
T.J. Sejnowski, B.P. Yuhas, M.H. Goldstein, Jr. and R.E. Jenkins
0240 Using A Translation-Invariant Neural Network to Diagnose Heart Arrhythmia
Susan Ciarrocca Lee

PART III: VISION

0248 A Neural Network for Real-Time Signal Processing
Donald B. Malkoff
0258 Learning Aspect Graph Representations from View Sequences
Michael Seibert and Allen M. Waxman
0266 TRAFFIC: Recognizing Objects Using Hierarchical Reference Frame Transformations
Richard S. Zemel, Michael C. Mozer and Geoffrey E. Hinton
0274 A Self-Organizing Multiple-View Representation of 3D Objects
Daphna Weinshall, Shimon Edelman and Heinrich H. Bulthoff
0282 Contour-Map Encoding of Shape for Early Vision
Pentri Kanerva
0290 Neurally Inspired Plasticity in Oculomotor Processes
PaulA. Viola

PART IV: OPTIMIZATION AND CONTROL

0298 Model Based Image Compression and Adaptive Data Representation by Interacting Filter Banks
Toshiaki Okamoto, Mitsuo Kawato, Toshio Inui and Sei Miyake
0308 Neuronal Group Selection Theory: A Grounding in Robotics
Jim Donnett and Tim Smithers
0316 Using Local Models to Control Movement
Christopher G. Atkeson
0324 Learning to Control an Unstable System with Forward Modeling
Michael I. Jordan and Robert A. Jacobs
0332 A Self-organizing Associative Memory System for Control Applications
Michael Hormel
0340 Operational Fault Tolerance of CMAC Networks
Michael J. Carter, Franklin J. Rudolph and Adam J. Nucci
0348 Neural Network Weight Matrix Synthesis Using Optimal Control Techniques
O. Farotimi, A. Dembo and T. Kailath

PART V: OTHER APPLICATIONS

0355 Generalized Hopfield Networks and Nonlinear Optimization
Gintaras V. Reklaitis, Athanasios G. Tsirukis and Manoel F. Tenorio
0364 Incremental Parsing by Modular Recurrent Connectionist Networks
Ajay N. Jain and Alex H. Waibel
0372 A Computational Basis for Phonology
David S. Touretzky and Deirdre W. Wheeler
0380 Higher Order Recurrent Networks and Grammatical Inference
C.L. Giles, G.Z. Sun, H.H. Chen, Y.C. Lee and D. Chen
0388 Bayesian Inference of Regular Grammar and Markov Source Models
Kurt R. Smith and Michael I. Miller
0396 Handwritten Digit Recognition with a Back-Propagation Network
Y. Le Cun, B. Boser, J.S. Denker, D. Henderson, R.E. Howard, W. Hubbard and L.D. Jackel
0405 Recognizing Hand-Printed Letters and Digits
Gale L. Martin and James A. Pittman
0415 A Large-Scale Neural Network Which Recognizes Handwritten Kanji Characters
Yoshihiro Mori and Kazuki Joe
0423 A Neural Network to Detect Homologies in Proteins
Yoshua Bengio, Samy Bengio, Yannick Pouliot and Patrick Agin
0431 Rule Representations in a Connectionist Chunker
David S. Touretzky and Gillette Elvgren III
0439 Discovering the Structure of a Reactive Environment by Exploration
Michael C. Mozer and Jonathan Bachrach
0447 Designing Application-Specific Neural Networks Using the Genetic Algorithm
Steven A. Harp, Tang Samad and Aloke Guha
0455 Predicting Weather Using a Genetic Memory: A Combination of Kanerva's Sparse Distributed Memory with Holland's Genetic Algorithms
David Rogers

PART VI: NEW LEARNING ALGORITHMS

0465 Neural Network Visualization
Jakub Wejchert and Gerald Tesauro
0474 Sigma-Pi Learning: On Radial Basis Functions and Cortical Associative Learning
Bartlett W. Mel and Christof Koch
0482 Algorithms for Better Representation and Faster Learning in Radial Basis Function Networks
Avijit Saha and James D. Keeler
0490 Learning in Higher-Order 'Artificial Dendritic Trees'
Tony Bell
0498 Adjoint Operator Algorithms for Faster Learning in Dynamical Neural Networks
Jacob Barhen, Nikzad Toomarian and Sandeep Gulati
0509 Discovering High Order Features with Mean Field Modules
Conrad C. Galland and Geoffrey E. Hinton
0516 The CHIR Algorithm for Feed Forward Networks with Binary Weights
Tal Grossman
0524 The Cascade-Correlation Learning Architecture
Scott E. Fahlman and Christian Lebiere
0533 Meiosis Networks
Stephen Jose Hanson
0542 The Cocktail Party Problem: Speech/Data Signal Separation Comparison between Backpropagation and SONN
John Kassebaum, Manoel Fernando Tenorio and Christoph Schaefers
0550 Generalization and Scaling in Reinforcement Learning
David H. Ackley and Michael L. Littman
0558 The 'Moving Targets' Training Algorithm
Richard Rohwer
0566 Training Connectionist Networks with Queries and Selective Sampling
Les Atlas, David Cohn and Richard Ladner
0574 Maximum Likelihood Competitive Learning
Steven J. Nowlan
0583 Unsupervised Learning in Neurodynamics Using the Phase Velocity Field Approach
Michail Zak and Nikzad Toomarian

PART VII: EMPIRICAL ANALYSES

0590 A Method for the Associative Storage of Analog Vectors
Amir Atiya and Yaser Abu-Mostafa
0598 Optimal Brain Damage
Yann Le Cun, John S. Denker and Sara A. Solla
0606 Asymptotic Convergence of Backpropagation: Numerical Experiments
Subutai Ahmad, Gerald Tesauro and Yu He
0614 Comparing the Performance of Connectionist and Statistical Classifiers on an Image Segmentation Problem
Sheri L. Gish and W.E. Blanz
0622 Performance Comparisons Between Backpropagation Networks and Classification Trees on Three Real-World Applications
Les Atlas, Ronald Cole, Jerome Connor, Mohamed El-Sharkawi, Robert J. Marks II, Yeshwant Muthusamy and Etienne Barnard
0630 Generalization and Parameter Estimation in Feedforward Nets: Some Experiments
N. Morgan and H. Bourlard
0638 Subgrouping Reduces Complexity and Speeds Up Learning in Recurrent Networks
David Zipser
0642 Dynamic Behavior of Constrained Back-Propagation Networks
Yves Chauvin

PART VIII: THEORETICAL ANALYSES

0650 Synergy of Clustering Multiple Back Propagation Networks
William P. Lincoln and Josef Skrzypek
0660 Coupled Markov Random Fields and Mean Field Theory
Davi Geiger and Federico Girosi
0668 Complexity of Finite Precision Neural Network Classifier
Amir Dembo, Kai-Yeung Siu and Thomas Kailath
0676 The Perceptron Algorithm Is Fast for Non-Malicious Distributions
Eric B. Baum
0686 Sequential Decision Problems and Neural Networks
A.G. Barto, R.S. Sutton and C.J.C.H. Watkins
0694 Analysis of Linsker's Simulations of Hebbian Rules
David J.C. MacKay and Kenneth D. Miller
0702 Analog Neural Networks of Limited Precision I: Computing with Multilinear Threshold Functions
Zoran Obradovic and Ian Parberry
0710 Time Dependent Adaptive Neural Networks
Fernando J. Pineda
0719 A Neural Network for Feature Extraction
Nathan Intrator
0727 On the Distribution of the Number of Local Minima of a Random Function on a Graph
Pierre Baldi, Yosef Rinott and Charles Stein

PART IX: HARDWARE IMPLEMENTATION

0733 A Cost Function for Internal Representations
Anders Krogh, C.J. Thorbergsson and John A. Hertz
0742 An Analog VLSI Model of Adaptation in the Vestibulo-Ocular Reflex
Stephen P. DeWeerth and Carver A. Mead
0750 Real-Time Computer Vision and Robotics Using Analog VLSI Circuits
Christof Koch, Wyeth Bair, John G. Harris, Timothy Horiuchi, Andrew Hsu and Jin Luo
0758 A Reconfigurable Analog VLSI Neural Network Chip
Srinagesh Satyanarayana, Yannis Tsividis and Hans Peter Graf
0769 Digital-Analog Hybrid Synapse Chips for Electronic Neural Networks
A. Moopenn, T. Duong and A.P. Thakoor
0777 Analog Circuits for Constrained Optimization
John C. Platt
0785 Pulse-Firing Neural Chips for Hundreds of Neurons
Michael Brownlow, Lionel Tarassenko, Alan F. Murray, Alister Hamilton, Il Song Han and H. Martin Reekie
0793 VLSI Implementation of a High-Capacity Neural Network Associative Memory
Tzi-Dar Chiueh and Rodney M. Goodman
0801 An Efficient Implementation of the Back-propagation Algorithm on the Connection Machine CM-2
Xiru Zhang, Michael Mckenna, Jill P. Mesirov and David L. Waltz
0810 Performance of Connectionist Learning Algorithms on 2-D SIMD Processor Arrays
Fernando J. Nunez and Jose A.B. Fortes

PART X: HISTORY OF NEURAL NETWORKS

0818 Dataflow Architectures: Flexible Platforms for Neural Network Simulation
Ira G. Smotroff
0828 Neural Networks: The Early Days
J.D. Cowan
0843 Subject Index
0851 Index

NIPS'1990 Volume 3 : Table of Contents
Richard Lippmann, John Moody, David Touretzky (eds), Morgan-Kaufmann (1991)
i Title Pages
v Table of Contents
xv Preface

Part I Neurobiology

0003 Studies of a Model for the Development and Regeneration of Eye-Brain Maps
J.D. Cowan and A.E. Friedman
0011 Development and Spatial Structure of Cortical Feature Maps: A Model Study
K. Obermayer, H. Ritter, and K. Schulten
0018 Interaction Among Ocularity, Retinotopy and On-center/Off-center Pathways
Shigeru Tanaka
0026 Simple Spin Models for the Development of Ocular Dominance Columns and Iso-Orientation Patches
J.D. Cowan and A.E. Friedman
0032 A Recurrent Neural Network Model of Velocity Storage in the Vestibulo-Ocular Reflex
Thomas J. Anastasio
0039 Self-organization of Hebbian Synapses in Hippocampal Neurons
Thomas H. Brown, Zachary F. Mainen, Anthony M. Zador, and Brenda J. Claiborne

Part II Neuro-Dynamics

0046 Cholinergic Modulation May Enhance Cortical Associative Memory Function
Michael E. Hasselmo, Brooke P. Anderson, and James M. Bower
0055 Order Reduction for Dynamical Systems Describing the Behavior of Complex Neurons
Thomas B. Kepler, L.F. Abbott, and Eve Marder
0062 Stochastic Neurodynamics
J.D. Cowan
0070 Dynamics of Learning in Recurrent Feature-Discovery Networks
Todd K. Leen
0077 A Lagrangian Approach to Fixed Points
Eric Mjolsness and Willard L. Miranker
0084 Associative Memory in a Network of 'Biological' Neurons
Wulfram Gerstner
0091 CAM Storage of Analog Patterns and Continuous Sequences with 3N 2 Weight
Bill Baird and Frank Eeckman
0098 Connection Topology and Dynamics in Lateral Inhibition Networks
C.M. Marcus, F.R. Waugh, and R.M. Westervelt
0105 Shaping the State Space Landscape in Recurrent Networks
Patrice Y. Simard, Jean Pierre Raysz, and Bernard Victorri

Part III Oscillations

0113 Adjoint-Functions and Temporal Learning Algorithms in Neural Networks
N. Toomarian and J. Barhen
0123 Phase-coupling in Two-Dimensional Networks of Interacting Oscillators
Ernst Niebur, Daniel M. Kammen, Christof Koch, Daniel Ruderman, and Heinz G. Schuster
0130 Oscillation Onset in Neural Delayed Feedback
Andre Longtin

Part IV Temporal Reasoning

0137 Analog Computation at a Critical Point
Leonid Kruglyak and William Bialek
0147 Modeling Time Varying Systems Using Hidden Control Neural Architecture
Esther Levin
0155 The Tempo 2 Algorithm: Adjusting Time-Delays By Supervised Learning
Ulrich Bodenhausen and Alex Waibel
0162 A Theory for Neural Networks with Time Delays
Bert de Vries and Jose C. Principe
0169 ART2/BP Architecture for Adaptive Estimation of Dynamic Processes
Einar Sorheim
0176 Statistical Mechanics of Temporal Association in Neural Networks
Andreas V.M. Herz, Zhaoping Li, and J. Leo van Hemmen
0183 Learning Time-varying Concepts
Anthony Kuh, Thomas Petsche, and Ronald L. Rivest

Part V Speech

0190 The Recurrent Cascade-Correlation Architecture
Scott E. Fahlman
0199 Continuous Speech Recognition by Linked Predictive Neural Networks
Joe Tebelskis, Alex Waibel, Bojan Petek, and Otto Schmidbauer
0206 A Recurrent Neural Network for Word Identification from Continuous Phoneme Strings
Robert B. Allen and Candace A. Kamm
0213 Connectionist Approaches to the Use of Markov Models for Speech Recognition
Herve Bourlard, Nelson Morgan, and Chuck Wooters
0220 Spoken Letter Recognition
Mark Fanty and Ronald Cole
0227 Speech Recognition Using Demi-Syllable Neural Prediction Model
Ken-ichi Iso and Takao Watanabe
0234 RecNorm: Simultaneous Normalisation and Classification Applied to Speech Recognition
John S. Bridle and Stephen J. Cox
0241 Exploratory Feature Extraction in Speech Signals
Nathan Intrator
0248 Phonetic Classification and Recognition Using the Multi-Layer Perceptron
Hong C. Leung, James R. Glass, Michael S. Phillips, and Victor W. Zue
0255 From Speech Recognition to Spoken Language Understanding
Victor Zue, James Glass, David Goodine, Lynette Hirschman, Hong Leung, Michael Phillips, Joseph Polifroni, and Stephanie Seneff

Part VI Signal Processing

0262 Speech Recognition using Connectionist Approaches
Khalid Choukri
0273 Natural Dolphin Echo Recognition Using an Integrator Gateway Network
Herbert L. Roitblat, Patrick W.B. Moore, Paul E. Nachtigall, and Ralph H. Penner
0282 Signal Processing by Multiplexing and Demultiplexing in Neurons
David C. Tam

Part VII Visual Processing

0289 Applications of Neural Networks in Video Signal Processing
John C. Pearson, Clay D. Spence, and Ronald Sverdlove
0299 Discovering Viewpoint-Invariant Relationships That Characterize Objects
Richard S. Zemel and Geoffrey E. Hinton
0306 A Neural Network Approach for Three-Dimensional Object Recognition
Volker Tresp
0313 A Second-Order Translation, Rotation and Scale Invariant Neural Network
Shelly D.D. Goggin, Kristina M. Johnson, and Karl E. Gustafson
0320 Learning to See Rotation and Dilation with a Hebb Rule
Martin I. Sereno and Margaret E. Sereno
0327 Stereopsis by a Neural Network Which Learns the Constraints
Alireza Khotanzad and Ying-Wung Lee
0335 Grouping Contours by Iterated Pairing Network
Amnon Shashua and Shimon Uliman
0342 Neural Dynamics of Motion Segmentation and Grouping
Ennio Mingolla
0349 A Multiscale Adaptive Network Model of Motion Computation in Primates
H. Taichi Wang, Bimal Mathur, and Christof Koch
0356 Qualitative Structure From Motion
Daphna Weinshall
0363 Optimal Sampling of Natural Images
William Bialek, Daniel L. Ruderman, and A. Zee
0370 A VLSI Neural Network for Color Constancy
Andrew Moore, John Allman, Geoffrey Fox, and Rodney Goodman
0377 Optimal Filtering in the Salamander Retina
Fred Rieke, W. Geoffrey Owen, and William Bialek
0384 A Four Neuron Circuit Accounts for Change Sensitive Inhibition in Salamander Retina
Jeffrey L. Teeters, Frank H. Eeckman, and Frank S. Werblin
0391 Feedback Synapse to Cone and Light Adaptation
Josef Skrzypek
0399 An Analog VLSI Chip for Finding Edges from Zero-crossings
Wyeth Bair and Christof Koch

Part VIII Control and Navigation

0406 A Delay-Line Based Motion Detection Chip
Tim Horiuchi, John Lazzaro, Andrew Moore, and Christof Koch
0415 Neural Networks Structured for Control Application to Aircraft Landing
Charles Schley, Yves Chauvin, Van Henkle, and Richard Golden
0422 Real-time Autonomous Robot Navigation Using VLSI Neural Networks
Lionel Tarassenko, Michael Brownlow, Gillian Marshall, Jon Tombs, and Alan Murray
0429 Rapidly Adapting Artificial Neural Networks for Autonomous Navigation
Dean A. Pomerleau
0436 Learning Trajectory and Force Control of an Artificial Muscle Arm
Masazumi Katayama and Mitsuo Kawato
0443 Proximity Effect Corrections in Electron Beam Lithography
Robert C. Frye, Kevin D. Cummings, and Edward A. Reitman
0450 Planning with an Adaptive World Model
Sebastian B. Thrun, Knut Moller, and Alexander Linden
0457 A Connectionist Learning Control Architecture for Navigation
Jonathan R. Bachrach
0464 Navigating Through Temporal Difference
Peter Dayan
0471 Integrated Modeling and Control Based on Reinforcement Learning
Richard S. Sutton
0479 A Reinforcement Learning Variant for Control Scheduling
Aloke Guha
0486 Adaptive Range Coding
Bruce E. Rosen, James M. Goodwin, and Jacques J. Vidal
0493 Neural Network Implementation of Admission Control
Rodolfo A. Milito, Isabelle Guyon, and Sara A. Solla
0500 Reinforcement Learning in Markovian and Non-Markovian Environments
Jurgen Schmidhuber
0507 A Model of Distributed Sensorimotor Control in The Cockroach Escape Turn
R.D. Beer, G.J. Kacmarcik, R.E. Ritzmann, and H.J. Chiel

Part IX Applications

0514 Flight Control in the Dragonfly: A Neurobiological Simulation
William E. Falter and Marvin W. Luttges
0523 A Novel Approach to Prediction of the 3-Dimensional Structures
Henrik Fredholm, Henrik Bohr, Jakob Bohr, Soren Brunak, Rodney M.J. Cotterill, Benny Lautrup, and Steffen B. Petersen
0530 Training Knowledge-Based Neural Networks to Recognize Genes
Michiel O. Noordewier, Geoffrey G. Towell, and Jude W. Shavlik
0537 Neural Network Application to Diagnostics
Kenneth A. Marko
0544 Lg Depth Estimation and Ripple Fire Characterization
John L. Perry and Douglas R. Baumgardt
0551 A B-P ANN Commodity Trader
Joseph E. Collard
0557 Integrated Segmentation and Recognition of Hand-Printed Numerals
James D. Keeler, David E. Rumelhart, and Wee-Kheng Leow
0564 EMPATH: Face, Emotion, and Gender Recognition Using Holons
Garrison W. Cottrell and Janet Metcalfe
0572 SEXNET: A Neural Network Identifies Sex From Human Faces
B.A. Golomb, D.T. Lawrence, and T.J. Sejnowski
0578 A Neural Expert System with Automated Extraction of Fuzzy If-Then Rules
Yoichi Hayashi

Part X Language and Cognition

0585 Analog Neural Networks as Decoders
Ruth Erlanson and Yaser Abu-Mostafa
0591 Distributed Recursive Structure Processing
Geraldine Legendre, Yoshiro Miyata, and Paul Smolensky
0598 Translating Locative Prepositions
Paul W. Munro and Mary Tabasko
0605 A Short-Term Memory Architecture for the Learning of Morphophonemic Rules
Michael Gasser and Chan-Do Lee
0612 Exploiting Syllable Structure in a Connectionist Phonology Model
David S. Touretzky and Deirdre W. Wheeler
0619 Language Induction by Phase Transition in Dynamical Recognizers
Jordan B. Pollack
0627 Discovering Discrete Distributed Representations
Michael C. Mozer
0635 Direct Memory Access Using Two Cues
Janet Wiles, Michael S. Humphreys, John D. Bain, and Simon Dennis
0642 An Attractor Neural Network Model of Recall and Recognition
Eytan Ruppin and Yechezkel Yeshurun
0649 ALCOVE: A Connectionist Model of Human Category Learning
John K. Kruschke
0656 Spherical Units as Dynamic Consequential Regions
Stephen Jose Hanson and Mark A. Gluck

Part XI Local Basis Functions

0665 Connectionist Implementation of a Theory of Generalization
Roger N. Shepard and Sheila Kannappan
0675 Adaptive Spline Networks
Jerome H. Friedman
0684 Multi-Layer Perceptrons with B-Spline Receptive Field Functions
Stephen H. Lane, Marshall G. Flax, David A. Handelman, and Jack J. Gelfand
0693 Bumptrees for Efficient Function, Constraint, and Classification Learning
Stephen M. Omohundro
0700 Basis-Function Trees as a Generalization of Local Variable Selection Methods
Terence D. Sanger
0707 Generalization Properties of Radial Basis Functions
Sherif M. Botros and Christopher G. Atkeson
0714 Learning by Combining Memorization and Gradient Descent
John C. Platt
0721 Sequential Adaptation of Radial Basis Function Neural Networks
V. Kadirkamanathan, M. Niranjan, and F. Fallside
0728 Oriented Non-Radial Basis Functions for Image Coding and Analysis
Avijit Saha, Jim Christian, D.S. Tang, and Chuan-Lin Wu
0735 Computing with Arrays of Bell-Shaped and Sigmoid Functions
Pierre Baldi
0743 Discrete Affine Wavelet Transforms
Y.C. Pati and P.S. Krishnaprasad
0750 Extensions of a Theory of Networks for Approximation and Learning
Federico Girosi, Tomaso Poggio, and Bruno Caprile

Part XII Learning Systems

0757 How Receptive Field Parameters Affect Neural Learning
Bartlett W. Mel and Stephen M. Omohundro
0767 A Competitive Modular Connectionist Architecture
Robert A. Jacobs and Michael I. Jordan
0774 Evaluation of Adaptive Mixtures of Competing Experts
Steven J. Nowlan and Geoffrey E. Hinton
0781 A Framework for the Cooperation of Learning Algorithms
Leon Bottou and Patrick Gallinari
0789 Connectionist Music Composition Based on Melodic and Stylistic Constraints
Michael C. Mozer and Todd Soukup
0797 Using Genetic Algorithms to Improve Pattern Classification Performance
Eric I. Chang and Richard P. Lippmann
0804 Evolution and Learning in Neural Networks
Ron Keesing and David G. Stork
0811 Designing Linear Threshold Based Neural Network Pattern Classifiers
Terrence L. Fine
0818 On Stochastic Complexity and Admissible Models for Neural Network Classifiers
Padhraic Smyth
0825 Efficient Design of Boltzmann Machines
Ajay Gupta and Wolfgang Maass
0832 Note on Learning Rate Schedules for Stochastic Optimization
Christian Darken and John Moody
0839 Convergence of a Neural Network Classifier
John S. Baras and Anthony LaVigna
0846 Learning Theory and Experiments with Competitive Networks
Griff L. Bilbro and David E. Van den Bout
0853 Transforming Neural-Net Output Levels to Probability Distributions
John S. Denker and Yann leCun
0860 Back Propagation is Sensitive to Initial Conditions
John F. Kolen and Jordan B. Pollack

Part XIII Learning and Generalization

0868 Closed-Form Inversion of Backpropagation Networks
Michael L. Rossen
0875 Generalization by Weight-Elimination with Application to Forecasting
Andreas S. Weigend, David E. Rumelhart, and Bernardo A. Huberman
0883 The Devil and the Network
Sanjay Biswas and Santosh S. Venkatesh
0890 Generalization Dynamics in LMS Trained Linear Networks
Yves Chauvin
0897 Dynamics of Generalization in Linear Perceptrons
Anders Krogh and John A. Hertz
0904 Constructing Hidden Units Using Examples and Queries
Eric B. Baum and Kevin J. Lang
0911 Can Neural Networks do Better Than the Vapnik-Chervonenkis Bounds?
David Cohn and Gerald Tesauro
0918 Second Order Properties of Error Surfaces
Yann Le Cun, Ido Kanter, and Sara A. Solla
0925 Chaitin-Kolmogorov Complexity and Generalization in Neural Networks
Barak A. Pearlmutter and Ronald Rosenfeld
0932 Asymptotic Slowing Down of the Nearest-Neighbor Classifier
Robert R. Snapp, Demetri Psaltis, and Santosh S. Venkatesh
0939 Remarks on Interpolation and Recognition Using Neural Nets
Eduardo D. Sontag
0946 E-Entropy and the Complexity of Feedforward Neural Networks
Robert C. Williamson

Part XIV Performance Comparisons

0953 On The Circuit Complexity of Neural Networks
V.P. Roychowdhury, A. Orlitsky, K.Y. Siu, and T. Kailath
0963 Comparison of Three Classification Techniques, CART, C4.5 and Multi-Layer Perceptrons
A.C. Tsoi and R.A. Pearson
0970 Practical Characteristics of Neural Network and Conventional Pattern Classifiers
Kenney Ng and Richard P. Lippmann
0977 Time Trials on Second-Order and Variable-Learning-Rate Algorithms
Richard Rohwer

Part XV VLSI

0984 Kohonen Networks and Clustering
Wesley Snyder, Daniel Nissman, David Van den Bout, and Griff Bilbro
0993 VLSI Implementations of Learning and Memory Systems
Mark A. Holler
1001 Compact EEPROM-based Weight Functions
A. Kramer, C.K. Sin, R. Chu, and P.K. Ko
1008 An Analog VLSI Splining Network
Daniel B. Schwartz and Vijay K. Samalam
1015 Relaxation Networks for Large Supervised Learning Problems
Joshua Alspector, Robert B. Allen, Anthony Jayakumar, Torsten Zeppenfeld, and Ronny Meir
1022 Design and Implementation of a High Speed CMAC Neural Network
W. Thomas Miller, III, Brian A. Box, Erich C. Whitney, and James M. Glynn
1028 Back Propagation Implementation
Hal McCartor
1032 Reconfigurable Neural Net Chip with 32K Connections
H.P. Graf, R. Janow, D. Henderson, and R. Lee
1039 Simulation of the Neocognitron on a CCD Parallel Processing Architecture
Michael L. Chuang and Alice M. Chiang
1046 VLSI Implementation of TInMANN
Matt Melton, Tan Phan, Doug Reeves, and Dave Van den Bout
1053 Index
1061 Author Index

NIPS'1991 Volume 4 : Table of Contents
John Moody, Steven Hanson, Richard Lippmann (eds), Morgan-Kaufmann (1992)
i Title Pages
v Table of Contents
xv Preface

Part I NEUROBIOLOGY

0003 Models Wanted: Must Fit Dimensions of Sleep and Dreaming
J. Allan Hobson, Adam N. Mamelak, and Jeffrey P. Sutton
0011 Stationarity of Synaptic Coupling Strength Between Neurons with Nonstationary Discharge Properties
Mark Sydorenko and Eric D. Young
0019 Perturbing Hebbian Rules
Peter Dayan and Geoffrey Goodhill
0027 Statistical Reliability of a Blowfly Movement-Sensitive Neuron
Rob de Ruyter van Steveninck and William Bialek
0035 The Clusteron: Toward a Simple Abstraction for a Complex Neuron
Bartlett W. Mel
0043 Network activity determines spatio-temporal integration in single cells
Ojvind Bernander, Christof Koch, and Rodneyl Douglas
0051 Nonlinear Pattern Separation in Single Hippocampal Neurons with Active Dendritic Membrane
Anthony M. Zador, Brendaf Clai borne, and Thomas H. Brown
0059 Self-organisation in real neurons: Anti-Hebb in 'Channel Space'?
Anthony J. Bell
0067 Single Neuron Model: Response to Weak Modulation in the Presence of Noise
A.R. Bulsara, E.W. Jacobs, and F. Moss
0075 Dual Inhibitory Mechanisms for Definition of Receptive Field Characteristics in a Cat Striate Cortex
A.B. Bonds
0083 A comparison between a neural netwok model for the formation of brain maps and experimental data
K. Obermszyer, K. Schulten, and G. G. Blasdel

Part II NEURO-DYNAMICS

0091 Retinogeniculate Development: The Role of Competition and Correlated Retinal Activity
Ron Keesing, David G. Stork, and Carla J. Shatz
0101 Locomotion in a Lower Vertebrate: Studies of the Cellular Basis of Rhythmogenesis and Oscillator Coupling
James T. Buchanan
0109 Adaptive Synchronization of Neural and Physical Oscillators
Kenji Doya and Shuji Yoshizawa
0117 Burst Synchronization without Frequency Locking in a Completely Solvable Network Model
Heinz Schuster and Christof Koch

Part III SPEECH

0125 Oscillatory Model of Short Term Memory
David Horn and Marius Usher
0135 Multi-State Time Delay Neural Networks for Continuous Speech Recognition
Patrick Haffner andAlex Waibel
0143 Modeling Applications with the Focused Gamma Net
Jose C. Principe, Bert de Vries, Jyh Ming Kuo, Pedro Guedes de Oliveira
0151 Time-Warping Network: A Hybrid Framework for Speech Recognition
Esther Levin, Roberto Pieraccini, and Enrico Bocchieri
0159 Improved Hidden Markov Model Speech Recognition Using Radial Basis Function Networks
Elliot Singer and Richard P. Lippmann
0167 Connectionist Optimisation of Tied Mixture Hidden Markov Models
Steve Renals, Nelson Morgan, Herve Bourlard, Horacio Franco, and Michael Cohen
0175 Neural Network--Gaussian Mixture Hybrid for Speech Recognition or Density Estimation
Yoshua Bengio, Renato De Mori, Giovanni Flammia, Ralf Kompe
0183 JANUS: Speech-to-Speech Translation Using Connectionist and Non-Connectionist Techniques
Alex Waibel, Ajay N. fain, Arthru McNair, Joe Tebelskis, Louise Osterholtz, Hiroaki Saito, Otto Schmidbauer, Tilo Sloboda, and Monika Woszczyna
0191 Forward Dynamics Modeling of Speech Motor Control Using Physiological Data
Makoto Hirayama, Eric Vatikiotis-Bateson, Mitsuo Kawato, and Michael I. Jordan

Part IV LANGUAGE

0199 English Alphabet Recognition with Telephone Speech
Mark Fanty, Ronald A. Cole, and Krist Roginski
0209 Generalization Performance in PARSEC-A Structured Connectionist Parsing Architecture
Ajay N. fain
0217 Constructing Proofs in Symmetric Networks
Gadi Pinkas
0225 A Connectionist Learning Approach to Analyzing Linguistic Stress
Prahlad Gupta and David S. Thuretzky
0233 Propagation Filters in PDS Networks for Sequencing and Ambiguity Resolution
Ronald A. Sumida and Michael G. Dyer

Part V TEMPORAL SEQUENCES

0241 A Segment-based Automatic Language Identification System
Yeshwant K. Muthusamy and Ronald A. Cole
0251 The Efficient Learning of Multiple Task Sequences
Satinder P. Singh
0259 Practical Issues in Temporal Difference Learning
Gerald Tesauro
0267 HARMONET: A Neural Net for Harmonizing Chorales in the Style of J.S. Bach
Hermann Hild, Johannes Feulner, and Wolfram Menzel
0275 Induction of Multiscale Temporal Structure
Michael C. Mozer
0283 Network Model of State-Dependent Sequencing
Jeffley P. Sutton, Adam N. Mamelak, and J. Allan Hobson

Part VI RECURRENT NETWORKS

0291 Learning Unambiguous Reduced Sequence Descriptions
Jurgen Schmidhuber
0301 Recurrent Networks and NARMA Modeling
Jerome Connor, Les E. Atlas, and Douglas R. Martin
0309 Induction of Finite-State Automata Using Second-Order Recurrent Networks
Raymond L. Watrous, and Gary M. Kuhn
0317 Extracting and Learning an Unknown Grammar with Recurrent Neural Networks
C.L. Giles, C.B. Miller, D. Chen, G.Z. Sun, H.H. Chen, and Y.C. Lee
0325 Operators and curried functions: Training and analysis of simple recurrent networks
Janet Wiles and Anthony Bloesch
0333 Green's Function Method for Fast On-line Learning Algorithm of Recurrent Neural Networks
Guo-Zheng Sun, Hsing-Hen Chen, and Yee-Chun Lee

PartVII VISION

0341 Dynamically-Adaptive Winner-Take-All Networks
Trent E. Lange
0351 Information Processing to Create Eye Movements
David A. Robinson
0356 Decoding of Neuronal Signals in Visual Pattern Recognition
Emad N. Eskandar, Barryf. Richmond, John A. Hertz, Lance M. Optican, and Troels Kjer
0364 Learning How to Teach or Selecting Minimal Surface Data
Davi Geiger and Ricardo A. Marques Pereira
0372 Learning to Make Coherent Predictions in Domains with Discontinuities
Suzanna Becker and Geoffley E. Hinton
0380 Recurrent Eye Tracking Network Using a Distributed Representation of Image Motion
P.A. Viola, S. G. Lisberger, and T.J. Sejnowski
0388 Against Edges: Function Approximation with Multiple Support Maps
Trevor Darrell and Alex Pentland
0396 Markov Random Fields Can Bridge Levels of Abstraction
Paul R. Cooper and Peter N. Prokopowicz
0404 Illumination and View Position in 3D Visual Recognition
Amnon Shashua
0412 Hierarchical Transformation of Space in the Visual System
Alexandre Pouget, Stephen A. Fisher, and Terrence J. Sejnowski
0420 VISIT: A Neural Model of Covert Visual Attention
Subutai Ahmad
0428 Visual Grammars and their Neural Nets
Eric Mjolsness
0436 Learning to Segment Images Using Dynamic Feature Binding
Michael C. Mozer, Richard S. Zemel, and Marlene Behrmann
0444 Combined Neural Network and Rule-Based Framework for Probabilistic Pattern Recognition and Discovery
Hayit K. Greenspan, Rodney Goodman, and Rama Chellappa
0452 Linear Operator for Object Recognition
Ronen Basri and Shimon Ullman

Part VIII OPTICAL CHARACTER RECOGNITION

0460 3D Object Recognition Using Unsupervised Feature Extraction
Nathan Intrator, Josh I. Gold, Heinrich H. Bulthoffi and Shimon Edelman
0471 Structural Risk Minimization for Character Recognition
I. Guyon, V. Vapnik, B. Boser, L. Bottou, and S.A. Solla
0480 Image Segmentation with Networks of Variable Scales
Hans P. Graf, Craig R. Nohl, and Jan Ben
0488 Multi-Digit Recognition Using a Space Displacement Neural Network
Ofer Matan, Christopher J. C. Burges, Yann Le Cun, and John S. Denker
0496 A Self-Organizing Integrated Segmentation and Recognition Neural Net
Jim Keeler and David E. Rumelhart
0504 Recognizing Overlapping Hand-Printed Characters by Centered-Object Integrated Segmentation and Recognition
Gale L. Martin and Mosfeq Rashid

Part IX CONTROL AND PLANNING

0512 Adaptive Elastic Models for Hand-Printed Character Recognition
Geoffrey E. Hinton, Christophe K.I. Williams, and Michael D. Revow
0523 Obstacle Avoidance through Reinforcement Learning
Tony J. Prescott and John E. W. Mayhew
0531 Active Exploration in Dynamic Environments
Sebastian B. Thrun and Knut Moller
0539 Oscillatory Neural Fields for Globally Optimal Path Planning
Michael Lemmon
0547 Recognition of Manipulated Objects by Motor Learning
Hiroaki Gomi and Mitsuo Kawato
0555 Refining PID Controllers using Neural Networks
Gary M. Scott, Jude W. Shavlik, and W. Harmon Ray
0563 Fast Learning with Predictive Forward Models
Carlos Brody
0571 Fast, Robust Adaptive Control by Learning only Forward Models
Andrew W. Moore
0579 Reverse TDNN: An Architecture for Trajectory Generation
Patrice Simard and Yann Le Cun
0589 Learning Global Direct Inverse Kinematics
David DeMers and Kenneth Kreutz-Delgado
0595 A Neural Net Model for Adaptive Control of Saccadic Accuracy by Primate Cerebellum and Brainstem
Paul Dean, John E. W. Mayhew, and Pat Langdon
0603 Learning in the Vestibular System: Simulations of Vestibular Compensation Using Recurrent Back-Propagation
Thomas J. Anastasio
0611 A Cortico-Cerebellar Model that Learns to Generate Distributed Motor Commands to Control a Kinematic Arm
N.E. Berthier, S.P. Singh, A.G. Barto, and J.C. Houk
0619 A Computational Mechanism to Account for Averaged Modified Hand Trajectories
Ealan A. Henis and Tamar Flash

Part X APPLICATIONS

0627 Simulation of Optimal Movements Using the Minimum-Muscle-Tension-Change Model
Menashe Dornay, Yoji Uno, Mitsuo Kawato, and Ryoji Suzuki
0637 ANN Based Classification for Heart Defibrillators
M. Jabri, S. Pickard, P. Leong, Z. Chi, B. Flower, and Y. Xie
0645 Neural Network Diagnosis of Avascular Necrosis from Magnetic Resonance Images
Armando Manduca, Paul Christy, and Richard Ehman
0651 Neural Network Analysis of Event Related Potentials and Electroencephalogram Predicts Vigilance
Rita Venturini, William W. Lytton, and Terrence J. Sejnowski
0659 Neural Control for Rolling Mills: Incorporating Domain Theories to Overcome Data Deficiency
Martin Roscheisen, Reimar Hofmann, and Volker Tresp
0667 Fault Diagnosis of Antenna Pointing Systems Using Hybrid Neural Network and Signal Processing Models
Padhraic Smyth and Jeff Mellstrom
0675 Multimodular Architecture for Remote Sensing Options
Sylvie Thiria, Carlos Mejia, Fouad Badran, Michel Crepon
0683 Principled Architecture Selection for Neural Networks: Application to Corporate Bond Rating Prediction
John Moody and Joachim Utans
0691 Adaptive Development of Connectionist Decoders for Complex Error-Correcting Codes
Sheri L. Gish and Mario Blaum
0698 Application of Neural Network Methodology to the Modelling of the Yield Strength in a Steel Rolling Plate Mill
Ah Chung Tsoi
0706 Computer Recognition of Wave Location in Graphical Data by a Neural Network
Donald T. Freeman
0714 A Neural Network for Motion Detection of Drift-Balanced Stimuli
Hilary Tunley
0722 Neural Network Routing for Random Multistage Interconnection Networks
Mark W. Goudreau and C. Lee Giles

Part XI IMPLEMENTATION

0730 Networks for the Separation of Sources that are Superimposed and Delayed
John C. Platt and Federico Faggin
0741 CCD Neural Network Processors for Pattern Recognition
Alice M. Chiang, Michael L. Chuang, and Jeffrey R. LaFranchise
0748 A Parallel Analog CCD/CMOS Signal Processor
Charles F. Neugebauer and Amnon Yariv
0756 Direction Selective Silicon Retina that uses Null Inhibition
Ronald G. Benson and Tobi Delbruck
0764 A Contrast Sensitive Silicon Retina with Reciprocal Synapses
Kwabena A. Boahen and Andreas G. Andreou
0773 A Neurocomputer Board Based on the ANNA Neural Network Chip
Eduard Sackinger, Bernhard E. Boser, and Lawrence D. Jackel
0781 Software for ANN training on a Ring Array Processor
Phil Kohn, Jeff Bilmes, Nelson Morgan, and James Beck
0789 Constrained Optimization Applied to the Parameter Setting Problem for Analog Circuits
David Kirk, Kurt Fleischer, Lloyd Watts, and Alan Barr
0797 Segmentation Circuits Using Constrained Optimization
John G. Harris
0805 Analog LSI Implementation of an Auto-Adaptive Network for Real-Time Separation of Independent Signals
Marc H. Cohen, Phillipe O. Pouliquen, and Andreas G. Andreou
0813 Temporal Adaptation in a Silicon Auditory Nerve
John Lazzaro

Part XII LEARNING AND GENERALIZATION

0821 Optical Implementation of a Self-Organizing Feature Extractor
Dana Z. Anderson, Claus Benkert, Verena Hebler, Ju-Seog Jang, Don Montgomery, and Mark Saffman
0831 Principles of Risk Minimization for Learning Theory
V. Vapnik
0839 Bayesian Model Comparison and Backprop Nets
David J. C. MacKay
0847 The Effective Number of Parameters: An Analysis of Generalization and Regularization in Nonlinear Learning Systems
John E. Moody
0855 Estimating Average-Case Learning Curves Using Bayesian, Statistical Physics and VC Dimension Methods
David Haussler, Michael Kearns, Manfred Opper, and Robert Schapire
0863 Constant-Time Loading of Shallow 1-Dimensional Networks
Stephen Judd
0871 Experimental Evaluation of Learning in a Neural Microsystem
Joshua Alspector, Anthony Jayakumar, and Stephan Luna
0879 Threshold Network Learning in the Presence of Equivalences
John Shawe-Taylor
0887 Gradient Descent: Second Order Momentum and Saturating Error
Barak Pearlmutter
0895 Tangent Prop--A formalism for specifying selected invariances in an adaptive network
Patrice Simard, Bernard Victorri, Yann Le Cun, and John Denker
0904 Polynomial Uniform Convergence of Relative Frequencies to Probabilities
Alberto Bertoni, Paola Campadelli, Anna Morpurgo, and Sandra Panizza
0912 Unsupervised learning of distributions on binary vectors using 2-layer networks
Yoav Freund and David Haussler
0920 Incrementally Learning Time-varying Half-planes
Anthony Kuh, Thomas Petsche, and Ron L. Rivest
0928 The VC-Dimension versus the Statistical Capacity of Multilayer Networks
Chuanyi Ji and Demetri Psaltis
0936 Some Approximation Properties of Projection Pursuit Learning Networks
Ying Zhao and Christopher G. Atkeson
0944 Neural Computing with Small Weights
Kai-Yeung Siu and Jehoshua Bruck
0950 A Simple Weight Decay Can Improve Generalization
Anders Krogh and John A. Hertz

Part XIII ARCHITECTURES AND ALGORITHMS

0958 Best-First Model Merging for Dynamic Learning and Recognition
Stephen M. Omohundro
0969 Rule Induction through Integrated Symbolic and Subsymbolic Processing
Clayton McMillan, Michael C. Mozer, and Paul Smolensky
0977 Interpretation of Artificial Neural Networks: Mapping Knowledge-Based Neural Networks into Rules
Geoffiry Towell and Jude W. Shavlik
0985 Hierarchies of adaptive experts
Michael I. Jordan and Robert A. Jacobs
0993 Adaptive Soft Weight Tying using Gaussian Mixtures
Steven J. Nowlan and Geoffrey E. Hinton
1001 Repeat Until Bored: A Pattern Selection Strategy
Paul W. Munro
1009 Towards Faster Stochastic Gradient Search
Christian Darken and John Moody
1017 Competitive Anti-Hebbian Learning of Invariants
Nicol N. Schraudolph and Terrence J. Sejnowski
1025 Merging Constrained Optimisation with Deterministic Annealing to "Solve" Combinatorially Hard Problems
Paul Stolorz
1033 Kernel Regression and Backpropagation Training with Noise
Patti Koistinen and Lasse Holmstrom
1040 Splines, Rational Functions and Neural Networks
Robert C. Williamson and Peter L. Bartlett
1048 Networks with Learned Unit Response Functions
John Moody and Norman Yarvin
1056 Learning in Feedforward Networks with Nonsmooth Functions
Nicholas J. Redding and T. Downs
1064 Iterative Construction of Sparse Polynomial Approximations
Terence D. Sanger, Richard S. Sutton, and Christopher J. Matheus
1072 Node Splitting: A Contructive Algorithm for Feed-Forward Neural Networks
Mike Wynne-Jones
1080 Information Measure Based Skeletonisation
Sowmya Ramachandran and Lorien Y. Pratt
1088 Data Analysis Using G/Splines
David Rogers
1096 Unsupervised Classifiers, Mutual Information and 'Phantom Targets'
John S. Bridle, Anthony J.R. Heading, and David J. C. MacKay
1102 A Network of Localized Linear Discriminants
Martin S. Glassman
1110 A Weighted Probabilistic Neural Network
David Montana
1118 Network generalization for production: Learning and producing styled letterforms
Igor Grebert, David G. Stork, Ron Keesing, and Steve Mims
1125 Shooting Craps in Search of an Optimal Strategy for Training Connectionist Pattern Classifiers
J.B. Hampshire II and B.V.K. VijayaKumar
1133 Improving the Performance of Radial Basis Function Networks by Learning Center Locations
Dietrich Wettschereck and Thomas Dietterich

Part XIV PERFORMANCE COMPARISONS

1141 A Topograhic Product for the Optimization of Self-Organizing Feature Maps
Hans-Ulrich Bauer, Klaus Pawelzik, and Theo Geisel
1151 Human and Machine 'Quick Modeling'
Jakob Bernasconi and Karl Gustafson
1159 A Comparison of Projection Pursuit and Neural Network Regression Modeling
Jenq-Neng Hwang, Hang Li, Martin Maechler, R. Douglas Martin, and Jim Schimert
1167 Benchmarking Feed-Forward Neural Networks: Models and Measures
Leonard G.C. Hamey
1175 Keyword Index
1184 Author Index

NIPS'1992 Volume 5 : Table of Contents
Steven Hanson, Jack Cowan, Lee Giles (eds), Morgan-Kaufmann (1993
i Title Pages
v Table of Contents
xiv Preface

Part I LEARNING AND GENERALIZATION

0003 On the Use of Projection Pursuit Constraints for Training Neural Networks
Nathan Intrator
0011 Hidden Markov Model Induction by Bayesian Model Merging
Andreas Stolcke and Stephen Omohundro
0019 Computing with Almost Optimal Size Neural Networks
Kai-Yeung Siu, Vwani Roychowdhury, and Thomas Kailath
0027 Intersecting Regions: The Key to Combinatorial Structure in Hidden Unit Space
Janet Wiles and Mark Ollila
0034 Holographic Recurrent Networks
Tony A. Plate
0042 Improving Performance in Neural Networks Using a Boosting Algorithm
Harris Drucker, Robert Schapire, and Patrice Simard
0050 Efficient Pattern Recognition Using a New Transformation Distance
Patrice Simard, Yann Le Cun, and John Denker
0059 Optimal Depth Neural Networks for Multiplication and Related Problems
Kai-Yeung Siu and Vwani Roychowdhury
0065 Using Prior Knowledge in a NNDPA to Learn Context-Free Languages
Sreerupa Das, C. Lee Giles, and Guo-Zheng Sun
0073 A Method for Learning from Hints
Yaser S. Abu-Mostafa
0081 Q-Learning with Hidden-Unit Restarting
Charles W. Anderson

Part II ARCHITECTURES AND ALGORITHMS

0089 Nets with Unreliable Hidden Nodes Learn Error-Correcting Codes
Stephen Judd and Paul W. Munro
0099 Interposing an Ontogenic Model Between Genetic Algorithms and Neural Networks
Richard K. Belew
0107 Combining Neural and Symbolic Learning to Revise Probabilistic Rule Bases
J. Jeffrey Mahoney and Raymond J. Mooney
0115 Learning Sequential Tasks by Incrementally Adding Higher Orders
Mark Ring
0123 Kohonen Feature Maps and Growing Cell Structures-a Performance Comparison
Bernd Fritzke
0131 Metamorphosis Networks: An Alternative to Constructive Models
Brian V. Bonnlander and Michael C. Mozer
0139 A Boundary Hunting Radial Basis Function Classifier which Allocates Centers Constructively
Eric I. Chang and Richard P. Lippmann
0147 Automatic Capacity Tuning of Very Large VC-Dimension Classifiers
I. Guyon, B. Boser, and V. Vapnik
0156 Automatic Learning Rate Maximization in Large Adaptive Machines
Yann LeCun, Patrice Y. Simard, and Barak Pearlmutter:
0164 Second Order Derivatives for Network Pruning: Optimal Brain Surgeon
Babak Hassibi and David G. Stork
0172 Directional-Unit Boltzmann Machines
Richard S. Zemel, Christopher K. I. Williams, and Michael C. Mozer
0180 Time Warping Invariant Neural Networks
Guo-Zheng Sun, Hsing-Hen Chen, and Yee-Chun Lee
0188 Generalization Abilities of Cascade Network Architecture
E. Littmann and H. Ritter
0196 Assessing and Improving Neural Network Predictions by the Bootstrap Algorithm
Gerhard Paass
0204 Discriminability-Based Transfer between Neural Networks
L. Y. Pratt
0212 Summed Weight Neuron Perturbation: An O(N) Improvement Over Weight Perturbation
Barry Flower and Marwan Jabri
0220 A Note on Learning Vector Quantization
Virginia R. de Sa and Dana H. Ballard
0228 Extended Regularization Methods for Nonconvergent Model Selections
W. Finnoff, F. Hergert, and H. G. Zimmermann
0236 Synchronization and Grammatical Inference in an Oscillating Elman Net
Bill Baird, Todd Troyer, and Frank Eeckman

Part III CONTROL, NAVIGATION, AND PLANNING

0244 A Fast Stochastic Error-Descent Algorithm for Supervised Learning and Optimization
Gert Cauwenberghs
0255 Global Regularization of Inverse Kinematics for Redundant Manipulators
David DeMers and Kenneth Kreutz-Delgado
0263 Memory-based Reinforcement Learning: Efficient Computation with Prioritized Sweeping
Andrew W. Moore and Christopher G. Atkeson
0271 Feudal Reinforcement Learning
Peter Dayan and Geoffrey E. Hinton
0279 Input Reconstruction Reliability Estimation
Dean A. Pomerleau
0287 Explanation-based Neural Network Learning for Robot Control
Tom M. Mitchell and Sebastian B. Thrun
0295 Reinforcement Learning Applied to Linear Quadratic Regulation
Steven J. Bradtke
0303 Neural Network On-Line Learning Control of Spacecraft Smart Structures
Christopher Bowman
0311 Integration of Visual and Somatosensory Information for Preshaping Hand in Grasping Movements
Yoji Uno, Naohiro Fukumura, Ryoji Suzuki, and Mitsuo Kawato
0319 On Line Estimation of Optimal Control Sequences: HJB Estimators
James K. Peterson
0327 Learning Control Under Extreme Uncertainty
Vijaykumar Gullapalli
0335 A Practice Strategy for Robot Learning Control
Terence D. Sanger
0342 Learning Spatio-Temporal Planning from a Dynamic Programming Teacher: Feed-Forward Neurocontrol for Moving Obstacle Avoidance
Gerald Fahner and Rolf Eckmiller

Part IV VISUAL PROCESSING

0350 Learning Fuzzy Rule-Based Neural Networks for Control
Charles M. Higgins and Rodney M. Goodman
0361 Learning to Categorize Objects Using Temporal Coherence
Suzanna Becker
0369 Filter Selection Model for Generating Visual Motion Signals
Steven J. Nowlan and Terrence J. Sejnowski
0377 Stimulus Encoding By Multidimensional Receptive Fields in Single Cells and Cell Populations in V1 of Awake Monkey
Edward Stern, Ad Aertsen, Eilon Vaadia, and Shaul Hochstein
0385 The Computation of Stereo Disparity for Transparent and for Opaque Surfaces
Suthep Madarasmi, Daniel Kersten, and Ting-Chuen Pong
0393 Some Solutions to the Missing Feature Problem in Vision
Subutai Ahmad and Volker Tresp
0401 Improving Convergence in Hierarchical Matching Networks for Object Recognition
Joachim Utans and Gene Gindi
0409 A Model of Feedback to the Lateral Geniculate Nucleus
Carlos D. Brody
0417 Unsmearing Visual Motion: Development of Long-Range Horizontal Intrinsic Connections
Kevin E. Martin and Jonathan A. Marshall
0425 Remote Sensing Image Analysis via a Texture Classification Neural Network
Hayit K. Greens pan and Rodney Goodman
0433 Computation of Heading Direction from Optic Flow in Visual Cortex
Markus Lappe and Josef P. Rauschecker

Part V STOCHASTIC LEARNING AND ANALYSIS

0441 Learning to See Where and What: Training a Net to Make Saccades and Recognize Handwritten Characters
Gale Martin, Mosfeq Rashid, David Chapman, and James Pittman
0451 Weight Space Probability Densities in Stochastic Learning: I. Dynamics and Equilibria
Todd K. Leen and John E. Moody
0459 Diffusion Approximations for the Constant Step Size Backpropogation Algorithm and Resistance to Local Minima
William Finnoff
0467 Self-Organizing Rules for Robust Principal Component Analysis
Lei Xu and Alan Yuille
0475 Bayesian Learning via Stochastic Dynamics
Radford M. Neal
0483 Information, Prediction, and Query by Committee
Yoav Freund, H. Sebastian Seung, Eli Shamir, and Naftali Tishby
0491 Synaptic Weight Noise During MLP Learning Enhances Fault-Tolerance, Generalization and Learning Trajectory
Alan F. Murray and Peter J. Edwards
0499 Unsupervised Discrimination of Clustered Data via Optimization of Binary Information Gain
Nicol N. Schraudolph and Terrence J. Sejnowski
0507 Weight Space Probability Densities in Stochastic Learning: II. Transients and Basin Hopping Times
Genevieve B. Orr and Todd K. Leen
0515 Information Theoretic Analysis of Connection Structure from Spike Trains
Satoru Shiono, Satoshi Yamada, Michio Nakashima, and Kenji Matsumoto
0523 Statistical Mechanics of Learning in a Large Committee Machine
Hoim Schwarze and John Hertz
0531 Probability Estimation from a Database Using a Gibbs Energy Model
John Miller and Rodney M. Goodman

Part VI NETWORK DYNAMICS AND CHAOS

0539 On the Use of Evidence in Neural Networks
David H. Wolpert
0549 Destabilization and Route to Chaos in Neural Networks with Random Connectivity
Bernard Doyon, Bruno Cessac, Mathias Quoy, and Manuel Samuelides
0556 Predicting Complex Behavior in Sparse Asymmetric Networks
Au A. Minai and William B. Levy
0564 Single-iteration Threshold Hamming Networks
Isaac Meilijson, Eytan Ruppin, and Moshe Sipper
0572 History-dependent Attractor Neural Networks
Isaac Meilijson and Eytan Ruppin

Part VII THEORY AND ANALYSIS

0580 Non-Linear Dimensionality Reduction
David DeMers and Garrison Cottrell
0591 On Learning µ-Perceptron Networks with Binary Weights
Mostefa Golea, Mario Marchand, and Thomas R. Hancock
0599 Neural Network Model Selection Using Asymptotic Jackknife Estimator and Cross-Validation Method
Yong Liu
0607 Learning Curves, Model Selection and Complexity of Neural Networks
Noboru Murata, Shuji Yoshizawa, and Shun-ichi Amari
0615 The Power of Approximating: A Comparison of Activation Functions
Bhaskar Das Gupta and Georg Schnitger
0623 Rational Parameterizations of Neural Networks
Uwe Helmke and Robert C. Williamson
0631 Learning Cellular Automaton Dynamics with Neural Networks
N. H. Wulff and J. A. Hertz

Part VIII SPEECH AND SIGNAL PROCESSING

0639 Some Estimates of Necessary Number of Connections and Hidden Units for Feed-Forward Networks
Adam Kowalczyk
0649 Context-Dependent Multiple Distribution Phonetic Modeling with MLPs
Michael Cohen, Horacio Franco, Nelson Morgan, David Rumelhart, and Victor Abrash
0658 Physiologically Based Speech Synthesis
Makoto Hirayama, Eric Vatikiotis-Bateson, Kiyoshi Honda, Yasuharu Koike, and Misuo Kawato
0666 Analog Cochlear Model for Multiresolution Speech Analysis
Weimin Liu, Andreas G. Andreou, and Moise H. Goldstein Jr.
0674 A Hybrid Linear/Nonlinear Approach to Channel Equilization Problems
Wei-Tsih Lee and John Pearson
0682 Modeling Consistency in a Speaker Independent Continuous Speech Recognition System
Yochai Konig, Nelson Morgan, Chuck Wooters, Victor Abrash, Michael Cohen, and Horacio Franco
0688 Transient Signal Detection with Neural Networks: The Search for the Desired Signal
Jose C. Principe and Abir Zahalka
0696 Performance Through Consistency: MS-TDNN's for Large Vocabulary Continuous Speech Recognition
Joe Tebelskis and Alex Waibel
0704 A Hybrid Neural Net System for State-of-the-Art Continuous Speech Recognition
George Zavaliagkos, Y. Zhao, R. Schwartz, and J. Makhoul

Part IX APPLICATIONS

0712 Connected Letter Recognition with a Multi-State Time Delay Neural Network
Hermann Hild and Alex Waibel
0723 Recognition-Based Segmentation of On-line Hand-Printed Words
M. Schenkel, H. Weissman, I. Guyon, C. Nohl, and D. Henderson
0731 Planar Hidden Markov Modeling: from Speech to Optical Character Recognition
Esther Levin and Roberto Pieraccini
0739 Forecasting Demand for Electric Power
Jen-Lun Yuan and Terrence L. Fine
0747 Hidden Markov Models in Molecular Biology: New Algorithms and Applications
Pierre Baldi, Yves Chauvin, Tim Hunkapiller, and Marcella A. McClure

Part X IMPLEMENTATIONS

0755 A Neural Network that Learns to Interpret Myocardial Planar Thallium Scintigrams
Charles Rosenberg, Jacob Erel, and Henri Atlan
0765 An Analog VLSI Chip for Radial Basis Functions
Janeen Anderson, John C. Platt, and David B. Kirk
0773 Generic Analog Neural Computation-The Epsilon Chip
Stephen Churcher, Donald J. Baxter, Alister Hamilton, Alan F. Murray, and H. Martin Reekie
0781 Visual Motion Computation in Analog VLSI using Pulses
Rahul Sarpeshkar, Wyeth Bair, and Christof Koch
0789 Analog VLSI Implementation of Gradient Descent
David B. Kirk, Douglas Kerns, Kurt Fleischer, and Alan H. Barr
0797 An Object-Oriented Framework for the Simulation of Neural Networks
A. Linden, Th. Sudbrak, Ch. Tietz, and F. Weber
0805 Attractor Neural Networks with Local Inhibition: from Statistical Physics to a Digital Programmable Integrated Circuit
E. Pasero and R. Zecchina
0813 Hybrid Circuits of Interacting Computer Model and Biological Neurons
Sylvie Renaud-LeMasson, Gwendal LeMasson, Eve Marder, and L. F. Abbot
0820 Silicon Auditory Processors as Computer Peripherals
John Lazzaro, John Wawrzynek, M. Mahowald, Massimo Sivilotti, and Dave Gillespie
0828 Object-Based Analog VLSI Vision Circuits
Christof Koch, Bimal Mathur, Shih-Chii Liu, John G. Harris, Jin Luo, and Massimo Sivilotti

Part XI COGNITIVE SCIENCE

0836 A Parallel Gradient Descent Method for Learning in Analog VLSI Neural Networks
J. Alspector, R. Meir, B. Yuhas, A. Jayakumar, and D. Lippe
0847 Harmonic Grammars for Formal Languages
Paul Smolensky
0855 Analogy-Watershed or Waterloo? Structural Alignment and the Development of Connectionist Models of Cognition
Dedre Gentner and Arthur B. Markman
0863 A Connectionist Symbol Manipulator that Discovers the Structure of Context-Free Languages
Michael C. Mozer and Sreerupa Das
0871 Network Structuring and Training Using Rule-based Knowledge
Volker Tresp, Jurgen Hollatz, and Subutai Ahmad
0879 A Dynamical Model of Priming and Repetition Blindness
Daphne Bavelier and Michael I. Jordan
0887 A Knowledge-Based Model of Geometry Learning
Geoffrey Towell and Richard Lehrer
0895 Word Space
Hinrich Schutze

Part XII COMPUTATIONAL AND THEORETICAL NEUROBIOLOGY

0903 Perceiving Complex Visual Scenes: An Oscillator Neural Network Model that Integrates Selective Attention, Perceptual Organisation, and Invariant Recognition
Rainer Goebel
0913 Mapping Between Neural and Physical Activities of the Lobster Gastric Mill
Kenji Doya, Mary E. T. Boyle, and Allen I. Selverston
0921 A Neural Model of Descending Gain Control in the Electrosensory System
Mark E. Nelson
0929 Using Hippocampal 'Place Cells' for Navigation, Exploiting Phase Coding
Neil Burgess, John O'Keefe, and Michael Recce
0937 Adaptive Stimulus Representations: A Computational Theory of Hippocampal-Region Function
Mark A. Gluck and Catherine E. Myers
0945 Statistical Modeling of Cell-Assemblies Activities in Associative Cortex of Behaving Monkeys
Itay Gat and Naftali Tishby
0953 Deriving Receptive Fields Using an Optimal Encoding Criterion
Ralph Linsker
0961 Biologically Plausible Local Learning Rules for the Adaptation of the Vestibulo-Ocular Reflex
Olivier Coenen, Terrence J. Sejnowski, and Stephen G. Lisberger
0969 Using Aperiodic Reinforcement for Directed Self-Organization During Development
P. R. Montague, P. Dayan, S. J. Nowlan, and T J. Sejnowski
0977 How Oscillatory Neuronal Responses Reflect Bistability and Switching of the Hidden Assembly Dynamics
K. Pawelzik, H.-U. Bauer, J. Deppisch, and I Geisel
0985 Topography and Ocular Dominance with Positive Correlations
Geoffrey J. Goodhill
0993 Statistical and Dynamical Interpretation of ISIH Data from Periodically Stimulated Sensory Neurons
Frank Moss and Andre Longtin
1001 Spiral Waves in Integrate-and-Fire Neural Networks
John G. Milton, Po Hsiang Chu, and Jack D. Cowan
1007 Parameterising Feature Sensitive Cell Formation in Linsker Networks in the Auditory System
Lance C. Walton and David L. Bisset
1014 A Recurrent Neural Network for Generation of Occular Saccades
Lina E. Massone
1022 A Formal Model of the Insect Olfactory Macroglomerulus: Simulations and Analytic Results
Christiane Linster, David Marsan, Claudine Masson, Michel Kerszberg, Gerard Dreyfus, and Leon Personnaz
1030 An Information-Theoretic Approach to Deciphering the Hippocampal Code
William E. Skaggs, Bruce L. McNaughton, and Katalin M. Gothard
1039 Author Index
1043 Index

NIPS'1993 Volume 6 : Table of Contents
Jack Cowan, Gerry Tesauro, Josh Alspector (eds), Morgan-Kaufmann (1994)
i Title Pages
v Table of Contents
xvi Preface
xviii In Memoriam: Ed Posner
xxvi NIPS-93 Organizing Committee
xxvi NIPS-93 Publicity Committee
xxvi NIPS-93 Program Committee
xxvii NIPS Foundation Board Members
xxvii NIPS-93 Referees

PART I LEARNING ALGORITHMS

0003 Autoencoders, Minimum Description Length, and Helmholtz Free Energy
Geoffrey E. Hinton and Richard S. Zemel
0011 Developing Population Codes by Minimizing Description Length
Richard S. Zemel and Geoffrey E. Hinton
0019 A Unified Gradient-Descent/Clustering Architecture for Finite State Machine Induction
Sreerupa Das and Michael C. Mozer
0027 Unsupervised Learning of Mixtures of Multiple Causes in Binary Data
Eric Saund
0035 Fast Pruning Using Principal Components
Asriel U Levin, Todd K. Leen, and John E. Moody
0043 Surface Learning with Applications to Lipreading
Christoph Bregler and Stephen M. Omohundro
0051 When Will a Genetic Algorithm Outperform Hill Climbing?
Melanie Mitchell, John H. Holland, and Stephanie Forrest
0059 Hoeffding Races: Accelerating Model Selection Search for Classification and Function Approximation
Oded Maron and Andrew W. Moore
0067 Grammatical Inference by Attentional Control of Synchronization in an Oscillating Elman Network
Bill Baird, Todd Troyer, and Frank Eeckman
0075 Credit Assignment through Time: Alternatives to Backpropagation
Yoshua Bengio and Paolo Frasconi
0083 A Local Algorithm to Learn Trajectories with Stochastic Neural Networks
Javier R. Movellan
0088 Structural and Behavioral Evolution of Recurrent Networks
Gregory M. Saunders, Peter J. Angeline, and Jordan B. Pollack
0096 Clustering with a Domain-Specific Distance Measure
Steven Gold, Eric Mjolsness, and Anand Rangarajan
0104 Central and Pairwise Data Clustering by Competitive Neural Networks
Joachim Buhmann and Thomas Hofmann
0112 Learning Classification with Unlabeled Data
Virginia R. de Sa
0120 Supervised Learning from Incomplete Data via an EM Approach
Zoubin Ghahramani and Michael I. Jordan
0128 Training Neural Networks with Deficient Data
Volker Tresp, Subutai Ahmad, and Ralph Neuneier
0136 Unsupervised Parallel Feature Extraction from First Principles
Mats Osterberg and Reiner Lenz
0144 Two Iterative Algorithms for Computing the Singular Value Decomposition from Input/Output Samples
Terence D. Sanger
0152 Fast Non-Linear Dimension Reduction
Nanda Kambhatla and Todd K. Leen
0160 Assessing the Quality of Learned Local Models
Stefan Schall and Christopher G. Atkeson
0168 Efficient Computation of Complex Distance Metrics Using Hierarchical Filtering
Patrice Y Simard
0176 The Power of Amnesia
Dana Ron, Yoram Singer, and Naftali Tishby
0184 Locally Adaptive Nearest Neighbor Algorithms
Dietrich Wettschereck and Thomas G. Dietterich
0192 Robust Parameter Estimation and Model Selection for Neural Network Regression
Yong Liu
0200 Bayesian Backpropagation over I-O Functions Rather Than Weights
David H. Wolpert
0208 Bayesian Backprop in Action: Pruning, Committees, Error Bars, and an Application to Spectroscopy
Hans Henrik Thodberg
0216 A Comparison of Dynamic Reposing and Tangent Distance for Drug Activity Prediction
Thomas G. Dietterich, Ajay N. Jain, Richard H. Lathrop, and Tomas Lozano-Perez
0224 Combined Neural Networks for Time Series Analysis
Iris Ginzburg and David Horn
0232 Backpropagation without Multiplication
Patrice Y. Simard and Hans Peter Graf
0240 A Comparative Study of a Modified Bumptree Neural Network with Radial Basis Function Networks and the Standard Multi-Layer Perceptron
Richard T. J. Bostock and Alan J. Harget
0247 Adaptive Knot Placement for Nonparametric Regression
Hossein L. Najafi and Vladimir Cherkassky
0255 Supervised Learning with Growing Cell Structures
Bernd Fritzke
0263 Optimal Brain Surgeon: Extensions and Performance Comparisons
Babak Hassibi, David G. Stork, Gregory Wolff, and Takahiro Watanabe
0271 Generation of Internal Representation by α-Transformation
Ryotaro Kamimura
0279 Constructive Learning Using Internal Representation Conflicts
Laurens R. Leerink and Marwan A. Jabri
0285 Learning in Compositional Hierarchies: Inducing the Structure of Objects from Data
Joachim Utans

PART II LEARNING THEORY, GENERALIZATION, AND COMPLEXITY

0293 An Optimization Method of Layered Neural Networks Based on the Modified Information Criterion
Sumio Watanabe
0303 Optimal Stopping and Effective Machine Complexity in Learning
Changfeng Wang, Santosh S. Venkatesh, and J. Stephen Judd
0311 Agnostic PAC-Learning of Functions on Analog Neural Nets
Wolfgang Maass
0319 How to Choose an Activation Function
H. N. Mhaskar and C. A. Micchelli
0327 Learning Curves: Asymptotic Values and Rate of Convergence
Corinna Cortes, L. D. Jackel, Sara A. Solla, Vladimir Vapnik, and John S. Denker
0335 Recovering a Feed-Forward Net from Its Output
Charles Fefferman and Scott Markel
0343 Use of Bad Training Data for Better Predictions
Tal Grossman and Alan Lapedes
0351 H∞ Optimality Criteria for LMS and Backpropagation
Babak Hassibi, Ali H. Sayed, and Thomas Kailath
0359 Bounds on the Complexity of Recurrent Neural Network Implementations of Finite State Machines
Bill G. Home and Don R. Hush
0367 Generalization Error and the Expected Network Complexity
Chuanyi Ji
0375 Counting Function Theorem for Multi-Layer Networks
Adam Kowalczyk
0383 Backpropagation Convergence via Deterministic Nonmonotone Perturbed Minimization
O. L. Mangasarian and M. V. Solodov
0391 Cross-Validation Estimates IMSE
Mark Plutowski, Shinichi Sakata, and Halbert White
0399 Discontinuous Generalization in Large Committee Machines
H. Schwarze and J. Hertz
0407 Non-Linear Statistical Analysis and Self-Organizing Hebbian Networks
Jonathan L. Shapiro and Adam Prugelo-Bennett
0415 Structured Machine Learning for "Soft" Classification with Smoothing Spline ANOVA and Stacked Tuning, Testing, and Evaluation
Grace Wahba, Yuedong Wang, Chong Gu, Ronald Klein, and Barbara Klein
0423 Solvable Models of Artificial Neural Networks
Sumio Watanabe

PART III THEORETICAL ANALYSIS: DYNAMICS AND STATISTICS

0431 On the Non-Existence of a Universal Learning Algorithm for Recurrent Neural Networks
Herbert Wiklicky
0439 The Statistical Mechanics of k-Satisfaction
Scott Kirkpatrick, Geza Gyorgyi, Naftali Tishby, and Lidror Troyansky
0447 Coupled Dynamics of Fast Neurons and Slow Interactions
A.C.C. Coolen, R. W. Penney, and D. Sherrington
0455 Observability of Neural Network Behavior
Max Garzon and Fernanda Botelho
0463 How to Describe Neuronal Activity: Spikes, Rates, or Assemblies
Wulfram Gerstner and J. Leo van Hemmen
0471 Correlation Functions in a Large Stochastic Neural Network
Iris Ginzburg and Haim Sompolinsky
0477 Optimal Stochastic Search and Adaptive Momentum
Todd K. Leen and Genevieve B. Orr
0485 Optimal Signalling in Attractor Neural Networks
Isaac Meilijson and Eytan Ruppin
0493 Asynchronous Dynamics of Continuous Time Neural Networks
Xin Wang, Qingnan Li, and Edward K. Blum

PART IV NEUROSCIENCE

0501 Fool's Gold: Extracting Finite State Machines from Recurrent Network Dynamics
John F. Kolen
0511 Dynamic Modulation of Neurons and Networks
Eve Marder
0519 Amplifying and Linearizing Apical Synaptic Inputs to Cortical Pyramidal Cells
Ojvind Bernander, Christof Koch, and Rodney J. Douglas
0527 Odor Processing in the Bee: A Preliminary Study of the Role of Central Input to the Antennal Lobe
Christiane Linster, David Marsan, Claudine Masson, and Michel Kerszberg
0535 Lower Boundaries of Motoneuron Desynchronization via Renshaw Interneurons
Mitchell Gil Maltenfort, Robert E. Druzinsky, C. J. Heckman, and W. Zev Rymer
0543 Development of Orientation and Ocular Dominance Columns in Infant Macaques
Klaus Obermayer, Lynne Kiorpes, and Gary G. Blasdel
0551 Statistics of Natural Images: Scaling in the Woods
Daniel L. Ruderman and William Bialek
0559 Dopaminergic Neuromodulation Brings a Dynamical Plasticity to the Retina
Eric Boussard and Jean-Francois Vibert
0566 A Hodgkin-Huxley Type Neuron Model That Learns Slow Non-Spike Oscillation
Kenji Doya, Allen I. Selverston, and Peter F. Rowat
0574 Directional Hearing by the Mauthner System
Audrey L. Guzik and Robert C. Eaton
0582 An Analog VLSI Saccadic Eye Movement System
Timothy K. Horiuchi, Brooks Bishofberger, and Christof Koch
0590 Bayesian Modeling and Classification of Neural Signals
Michael S. Lewicki
0598 Foraging in an Uncertain Environment Using Predictive Hebbian Learning
P. Read Montague, Peter Dayan, and Terrence J. Sejnowski
0606 A Connectionist Model of the Owl's Sound Localization System
Daniel J. Rosen, David E. Rumelhart, and Eric I. Knudsen
0614 Optimal Unsupervised Motor Learning Predicts the Internal Representation of Barn Owl Head Movements
Terence D. Sanger
0622 An Analog VLSI Model of Central Pattern Generation in the Leech
Micah S. Siegel

PART V CONTROL, NAVIGATION, AND PLANNING

0629 Synchronization, Oscillations, and l/f Noise in Networks of Spiking Neurons
Martin Stemmler, Marius Usher, Christof Koch, and Zeev Olami
0639 Transition Point Dynamic Programming
Kenneth M. 0Buckland and Peter D. Lawrence
0647 Exploiting Chaos to Control the Future
Gary W. Flake, Guo-Zhen Sun, Yee-Chun Lee, and Hsing-Hen Chen
0655 Robust Reinforcement Learning in Motion Planning
Satinder P. Singh, Andrew G. Barto, Roderic Grupen, and Christopher Connolly
0663 Using Local Trajectory Optimizers to Speed Up Global Optimization in Dynamic Programming
Christopher G. Atkeson
0671 Packet Routing in Dynamically Changing Networks: A Reinforcement Learning Approach
Justin A. Boyan and Michael L. Littman
0679 Neural Network Exploration Using Optimal Experiment Design
David A. Cohn
0687 Monte Carlo Matrix Inversion and Reinforcement Learning
Andrew Barto and Michael Duff
0695 Convergence of Indirect Adaptive Asynchronous Value Iteration Algorithms
Vijaykumar Gullapalli and Andrew G. Barto
0703 Convergence of Stochastic Iterative Dynamic Programming Algorithms
Tommi Jaakkola, Michael I. Jordan, and Satinder P Singh
0711 The Parti-Game Algorithm for Variable Resolution Reinforcement Learning in Multidimensional State-Spaces
Andrew W. Moore
0719 Mixtures of Controllers for Jump Linear and Non-Linear Plants
Timothy W. Cacciatore and Steven J. Nowlan

PART VI APPLICATIONS

0727 A Computational Model for Cursive Handwriting Based on the Minimization Principle
Yasuhiro Wada, Yasuharu Koike, Eric Vatikiotis-Bateson, and Mitsuo Kawato
0737 Signature Verification Using a "Siamese" Time Delay Neural Network
Jane Bromley, Isabelle Guyon, Yann Le Cun, Eduard Sackinger, and Roopak Shah
0745 Postal Address Block Location Using a Convolutional Locator Network
Ralph Wolf and John C. Platt
0753 Non-Intrusive Gaze Tracking Using Artificial Neural Networks
Shumeet Baluja and Dean Pomerleau
0761 Hidden Markov Models for Human Genes
Pierre Baldi, Soren Brunak, Yves Chauvin, Jacob Engelbrecht, and Anders Krogh
0769 Illumination-Invariant Face Recognition with a Contrast Sensitive Silicon Retina
Joachim M. Buhmann, Martin Lades, and Frank Eeckman
0777 Recognition-Based Segmentation of On-Line Cursive Handwriting
Nicholas S. Flann
0785 Address Block Location with a Neural Net System
Hans Peter Graf and Eric Cosatto
0793 Identifying Fault-Prone Software Modules Using Feed-Forward Networks: A Case Study
N. Karunanithi
0801 Comparison Training for a Rescheduling Problem in Neural Networks
Didier Keymeulen and Martine de Gerlache
0809 Neural Network Definitions of Highly Predictable Protein Secondary Structure Classes
Alan Lapedes, Evan Steeg, and Robert Farber
0817 Temporal Difference Learning of Position Evaluation in the Game of Go
Nico N. Schraudolph, Peter Dayan, and Terrence J. Sejnowski
0825 Probabilistic Anomaly Detection in Dynamic Systems
Padhraic Smyth

PART VII IMPLEMENTATIONS

0833 Decoding Cursive Scripts
Yoram Singer and Naftali Tishby
0843 A Massively-Parallel SIMD Processor for Neural Network and Machine Vision Applications
Michael A. Glover and W. Thomas Miller III
0850 A Hybrid Radial Basis Function Neurocomputer and Its Applications
Steven S. Watkins, Paul M. Chau, Raoul Tawel, Bjorn Lambrigsten, and Mark Plutowski
0858 A Learning Analog Neural Network Chip with Continuous-Time Recurrent Dynamics
Gert Cauwenberghs
0866 VLSI Phase Locking Architectures for Feature Linking in Multiple Target Tracking Systems
Andreas G. Andreou and Thomas G. Edwards
0874 WATTLE: A Trainable Gain Analogue VLSI Neural Network
Richard Coggins and Marwan Jabri
0882 The "Softmax" Nonlinearity: Derivation Using Statistical Mechanics and Useful Properties as a Multiterminal Analog Circuit Element
I. M. Elfadel and J. L. Wyatt, Jr.
0888 High Performance Neural Net Simulation on a Multiprocessor System with "Intelligent" Communication
Urs A. Muller, Michael Kocheisen, and Anton Gunzinger
0896 Digital Boltzmann VLSI for Constraint Satisfaction and Learning
Michael Murray, Ming-Tak Leung, Kan Boonyanit, Kong Kritayakirana, James B. Bur, Gregory J. Wolff Takahiro Watanabe, Edward Schwartz, David G. Stork, and Allen M. Peterson
0904 Efficient Simulation of Biological Neural Networks on Massively Parallel Supercomputers with Hypercube Architecture
Ernst Niebur and Dean Brettle
0911 Learning Complex Boolean Functions: Algorithms and Applications
Arlindo L. Oliveira and Alberto Sangiovanni-Vincentelli
0919 Implementing Intelligence on Silicon Using Neuron-Like Functional MOS Transistors
Tadashi Shibata, Koji Kotani, Takeo Yamashita, Hiroshi Ishii, Hideo Kosaka, and Tadahiro Ohmi

PART VIII VISUAL PROCESSING

0927 Event-Driven Simulation of Networks of Spiking Neurons
Lloyd Watts
0937 Globally Trained Handwritten Word Recognizer Using Spatial Representation, Convolutional Neural Networks, and Hidden Markov Models
Yoshua Bengio, Yann Le Cun, and Donnie Henderson
0945 Classifying Hand Gestures with a View-Based Distributed Representation
Trevor J. Darrell and Alex P Pentland
0953 A Network Mechanism for the Determination of Shape-from-Texture
Ko Sakai and Leif H. Finkel
0961 Feature Densities Are Required for Computing Feature Correspondences
Subutai Ahmad
0969 The Role of MT Neuron Receptive Field Surrounds in Computing Object Shape from Velocity Fields
G. T. Buracas and T. D. Albright
0977 Resolving Motion Ambiguities
K. I. Diamantaras and D. Geiger
0985 Two-Dimensional Object Localization by Coarse-to-Fine Correlation Matching
Chien-Ping Lu and Eric Mjolsness
0993 Dual Mechanisms for Neural Binding and Segmentation
Paul Sajda and Leif H. Finkel

PART IX SPEECH AND SIGNAL PROCESSING

1001 Bayesian Self-Organization
Alan L. Yuille, Stelios M. Smirnakis, and Lei Xu
1011 Analysis of Short Term Memories for Neural Networks
Jose C. Principe, Hui-H. Hsu, and Jyh-Ming Kuo
1019 Figure of Merit Training for Detection and Spotting
Eric I. Chang and Richard P Lippmann
1027 Lipreading by Neural Networks: Visual Preprocessing, Learning, and Sensory Integration
Gregory J. Wolff K. Venkatesh Prasad, David G. Stork, and Marcus Hennecke
1035 Speaker Recognition Using Neural Tree Networks
Kevin R. Farrell and Richard J. Mammone
1043 Inverse Dynamics of Speech Motor Control
Makoto Hirayama, Eric Vatikiotis-Bateson, and Mitsuo Kawato
1051 Learning Temporal Dependencies in Connectionist Speech Recognition
Steve Renals, Mike Hochberg, and Tony Robinson

PART X COGNITIVE SCIENCE

1059 Segmental Neural Net Optimization for Continuous Speech Recognition
Ying Zhao, Richard Schwartz, John Makhoul, and George Zavaliagkos
1069 Connectionist Models for Auditory Scene Analysis
Richard O. Duda
1077 Computational Elements of the Adaptive Controller of the Human Arm
Reza Shadmehr and Ferdinando A. Mussa-Ivaldi
1085 Tonal Music as a Componential Code: Learning Temporal Relationships between and within Pitch and Timing Components
Catherine Stevens and Janet Wiles
1093 GDS: Gradient Descent Generation of Symbolic Classification Rules
Reinhard Blasig
1101 Emergence of Global Structure from Local Associations
Thea B. Ghiselli-Crippa and Paul W Munro
1109 Estimating Analogical Similarity by Dot-Products of Holographic Reduced Representations
Tony A. Plate
1117 Analyzing Cross-Connected Networks
Thomas R. Shultz and Jeffrey L. Elman

PART XI ADDENDA TO NIPS 5

1125 Encoding Labeled Graphs by Labeling RAAM
Alessandro Sperduti
1135 Learning Mackey-Glass from 25 Examples, Plus or Minus 2
Mark Plutowski, Garrison Cottrell, and Halbert White
1143 Classification of Multi-Spectral Pixels by the Binary Diamond Neural Network
Yehuda Salu

PART XII WORKSHOPS

1151 Classification of Electroencephalogram Using Artificial Neural Networks
A. C. Tsoi, D. S. C. So, and A. Sergejew
1161 Complexity Issues in Neural Computation and Learning
V. P. Roychowdhury and K. - Y. Siu
1163 Connectionism for Music and Audition
Andreas Weigend
1165 Memory-Based Methods for Regression and Classification
Thomas G. Dietterich, Dietrich Wettschereck, Chris G. Atkeson, and Andrew W Moore
1167 Neurobiology, Psychophysics, and Computational Models of Visual Attention
Ernst Niebur and Bruno A. Olshausen
1169 Robot Learning: Exploration and Continuous Domains
David A. Cohn
1171 Stability and Observability
Max Garzon and Fernanda Botelho
1173 What Does the Hippocampus Compute?: A Precis of the 1993 NIPS Workshop
Mark A. Gluck
1176 Catastrophic Interference in Connectionist Networks: Can It Be Predicted, Can It Be Prevented?
Robert M. French
1178 Connectionist Modeling and Parallel Architectures
Joachim Diederich and Ah Chung Tsoi
1180 Functional Models of Selective Attention and Context Dependency
Thomas H. Hildebrandt
1182 Learning in Computer Vision and Image Understanding
Hayit Greenspan
1184 Neural Network Methods for Optimization Problems
Arun Jagota
1186 Processing of Visual and Auditory Space and Its Modification by Experience
Josef P. Rauschecker and Terrence J. Sejnowski
1188 Putting It All Together: Methods for Combining Neural Networks
Michael P. Perrone
1191 Author Index
1195 Keyword Index

NIPS'1994 Volume 7 : Table of Contents
Gerry Tesauro, David Touretzky, Todd Leen (eds), MIT Press (1995)
i Title Pages
v Table of Contents
xvii Preface
xix Contributors

PART I COGNITIVE SCIENCE

0003 DIRECTION SELECTIVITY IN PRIMARY VISUAL CORTEX USING MASSIVE INTRACORTICAL CONNECTIONS
Humbert Suarez, Christof Koch, Rodney Douglas
0011 ON THE COMPUTATIONAL UTILITY OF CONSCIOUSNESS
Donald Mathis, Michael C. Mozer
0019 CATASTROPHIC INTERFERENCE IN HUMAN MOTOR LEARNING
Tom Brashers-Krug, Reza Shadmehr, Emanuel Todorov
0027 GRAMMAR LEARNING BY A SELF-ORGANIZING NETWORK
Michiro Negishi
0035 PATFERNS OF DAMAGE IN NEURAL NETWORKS: THE EFFECTS OF LESION AREA, SHAPE AND NUMBER
Eytan Ruppin, James A. Reggia
0043 FORWARD DYNAMIC MODELS IN HUMAN MOTOR CONTROL PSYCHOPHYSICAL EVIDENCE
Daniel M. Wolpert, Zoubin Ghahramani, Michael I. Jordan

PART II NEUROSCIENCE

0051 A SOLVABLE CONNECTIONIST MODEL OF IMMEDIATE RECALL OF ORDERED LISTS
Neil Burgess
0061 A MODEL FOR CHEMOSENSORY RECEPTION
Rainer Malaka, Thomas Ragg, Martin Hammer
0069 THE ELECTRONIC TRANSFORMATION: A TOOL FOR RELATING NEURONAL FORM TO FUNCTION
Nicholas Carnevale, Kenneth Y. Tsai, Brenda J. Claiborne, Thomas H. Brown
0077 A MODEL OF THE HIPPOCAMPUS COMBINING SELF-ORGANIZATION AND ASSOCIATIVE MEMORY FUNCTION
Michael E. Hasselmo, Eric Schnell, Joshua Berke, Edi Barkai
0085 MODEL OF BIOLOGICAL NEURON AS A TEMPORAL NEURAL NETWORK
Sean D. Murphy, Edward W. Kairiss
0093 A CRITICAL COMPARISON OF MODELS FOR ORIENTATION AND OCULAR DOMINANCE COLUMNS IN THE STRIATE CORTEX
E. Erwin, K. Obermayer, K. Schulten
0101 A NOVEL REINFORCEMENT MODEL OF BIRDSONG VOCALIZATION LEARNING
Kenji Doya, Terrence J. Sejnowski
0109 OCULAR DOMINANCE AND PATTERNED LATERAL CONNECTIONS IN A SELF-ORGANIZING MODEL OF THE PRIMARY VISUAL CORTEX
Joseph Sirosh, Risto Miikkulainen
0117 ANATOMICAL ORIGIN AND COMPUTATIONAL ROLE OF DIVERSITY IN THE RESPONSE PROPERTIES OF CORTICAL NEURONS
Kalanit Grill Spector, Shimon Edelman, Rafael Malach
0125 REINFORCEMENT LEARNING PREDICTS THE SITE OF PLASTICITY FOR AUDITORY REMAPPING IN THE BARN OWL
Alexandre Pouget, Cedric Deffayet, Terrence J. Sejnowski
0133 MORPHOGENESIS OF THE LATERAL GENICULATE NUCLEUS: HOW SINGULARITIES AFFECT GLOBAL STRUCTURE
Svilen Tzonev, Klaus Schulten, Joseph G. Malpeli
0141 A COMPUTATIONAL MODEL OF PREFRONTAL CORTEX FUNCTION
Todd S. Braver, Jonathan D. Cohen, David Servan-Schreiber
0149 A NEURAL MODEL OF DELUSIONS AND HALLUCINATIONS IN SCHIZOPHRENIA
Eytan Ruppin, James A. Reggia, David Horn
0157 SPATIAL REPRESENTATIONS IN THE PARIETAL CORTEX MAY USE BASIS FUNCTIONS
Alexandre Pouget, Terrence J. Sejnowski
0165 GROUPING COMPONENTS OF THREE-DIMENSIONAL MOVING OBJECTS IN AREA MST OF VISUAL CORTEX
Richard S. Zemel, Terrence J. Sejnowski

PART III LEARNING THEORY AND DYNAMICS

0173 A MODEL OF THE NEURAL BASIS OF THE RAT'S SENSE OF DIRECTION
William Skaggs, James J. Knierim, Hemant S. Kudrimoti, Bruce L. McNaughton
0183 ON THE COMPUTATIONAL COMPLEXITY OF NETWORKS OF SPIKING NEURONS
Wolfgang Maass
0191 H∞ OPTIMAL TRAINING ALGORITHMS AND THEIR RELATION TO BACK PROPAGATION
Babak Hassibi, Thomas Kailath
0199 SYNCHRONY AND DESYNCHRONY IN NEURAL OSCILLATOR NETWORKS
DeLiang Wang, David Terman
0207 LEARNING IN LARGE LINEAR PERCEPTRONS AND WHY THE THERMODYNAMIC LIMIT IS RELEVANT TO THE REAL WORLD
Peter Sollich
0215 GENERALISATION IN FEEDFORWARD NETWORKS
Adam Kowalczyk, Herman Ferra
0223 FROM DATA DISTRIBUTIONS TO REGULARIZATION IN INVARIANT LEARNING
Todd Leen
0231 NEURAL NETWORK ENSEMBLES, CROSS VALIDATION, AND ACTIVE LEARNING
Anders Krogh, Jesper Vedelsby
0239 LIMITS ON LEARNING MACHINE ACCURACY IMPOSED BY DATA QUALITY
Corinna Cortes, L. D. Jackel, Wan-Ping Chiang
0247 HIGHER ORDER STATISTICAL DECORRELATION WITHOUT INFORMATION LOSS
Gustavo Deco, Wilfried Brauer
0255 HYPERPARAMETERS, EVIDENCE AND GENERALISATION FOR AN UNREALISABLE RULE
Glenn Marion, David Saad
0263 TEMPORAL DYNAMICS OF GENERALIZATION IN NEURAL NETWORKS
Changfeng Wang, Santosh S. Venkatesh
0271 STOCHASTIC DYNAMICS OF THREE-STATE NEURAL NETWORKS
Toru Ohira, Jack D. Cowan
0279 LEARNING STOCHASTIC PERCEPTRONS UNDER K-BLOCKING DISTRIBUTIONS
Mario Marchand, Saeed Hadjifaradji
0287 LEARNING FROM QUERIES FOR MAXIMUM INFORMATION GAIN IN IMPERFECTLY LEARNABLE PROBLEMS
Peter Sollich, David Saad
0295 BIAS, VARIANCE AND THE COMBINATION OF LEAST SQUARES ESTIMATORS
Ronny Meir
0303 ON-LINE LEARNING OF DICHOTOMIES
N. Barkai, H. S. Seung, H. Sompolinsky
0311 DYNAMIC MODELLING OF CHAOTIC TIME SERIES WITH NEURAL NETWORKS
Jose Principe, Jyh-Ming Kuo
0319 A RIGOROUS ANALYSIS OF LINSKER-TYPE HEBBIAN LEARNING
Jianfeng Feng, H. Pan, V. P. Roychowdhury
0327 SAMPLE SIZE REQUIREMENTS FOR FEEDFORWARD NEURAL NETWORKS
Michael Turmnon, Terrence L. Fine

PART IV REINFORCEMENT LEARNING

0335 ASYMPTOTICS OF GRADIENT-BASED NEURAL NETWORK TRAINING ALGORITHMS
Sayandev Mukherjee, Terrence L. Fine
0345 REINFORCEMENT LEARNING ALGORITHM FOR PARTIALLY OBSERVABLE MARKOV DECISION PROBLEMS
Tommi Jaakkola, Satinder P. Singh, Michael I. Jordan
0353 ADVANTAGE UPDATING APPLIED TO A DIFFERENTIAL GAME
Mance E. Harmon, Leemnon C. Baird Ill, A. Harry Klopf
0361 REINFORCEMENT LEARNING WITH SOFT STATE AGGREGATION
Satinder Singh, Tommni Jaakkola, Michael I. Jordan
0369 GENERALIZATION IN REINFORCEMENT LEARNING: SAFELY APPROXIMATING THE VALUE FUNCTION
Justin Boyan, Andrew W. Moore
0377 INSTANCE-BASED STATE IDENTIFICATION FOR REINFORCEMENT LEARNING
R.Andrew McCallum
0385 FINDING STRUCTURE IN REINFORCEMENT LEARNING
Sebastian Thrun, Anton Schwartz
0393 REINFORCEMENT LEARNING METHODS FOR CONTINUOUS-TIME MARKOV DECISION PROBLEMS
Steven Bradtke, Michael O. Duff

PART V ALGORITHMS AND ARCHITECTURES

0401 AN ACTOR/CRITIC ALGORITHM THAT IS EQUIVALENT TO Q-LEARNING
Robert Crites, Andrew G. Barto
0411 FINANCIAL APPLICATIONS OF LEARNING FROM HINTS
Yaser S. Abu-Mostafa (Invited Paper)
0419 COMBINING ESTIMATORS USING NON-CONSTANT WEIGHTING FUNCTIONS
Volker Tresp, Michiaki Taniguchi
0427 AN INPUT OUTPUT HMM ARCHITECTURE
Yoshua Bengio, Paolo Frasconi
0435 BOLTZMANN CHAINS AND HIDDEN MARKOV MODELS
Lawrence K. Saul, Michael I. Jordan
0443 BAYESIAN QUERY CONSTRUCTION FOR NEURAL NETWORK MODELS
Gerhard Paass, Jorg Kindermann
0451 USING A SALIENCY MAP FOR ACTIVE SPATIAL SELECTIVE ATTENTION: IMPLEMENTATION & INITIAL RESULTS
Shumeet Baluja, Dean A. Pomerleau
0459 MULTIDIMENSIONAL SCALING AND DATA CLUSTERING
Thomas Hofmann, Joachim Buhmann
0467 A NON-LINEAR INFORMATION MAXIMISATION ALGORITHM THAT PERFORMS BLIND SEPARATION
Anthony J. Bell, Terrence J. Sejnowski
0475 PLASTICITY-MEDIATED COMPETITIVE LEARNING
Nicol Schraudolph, Terrence J. Sejnowski
0481 PHASE-SPACE LEARNING
Fu-Sheng Tsung, Garrison W. Cottrell
0489 LEARNING LOCAL ERROR BARS FOR NONLINEAR REGRESSION
David A. Nix, Andreas S. Weigend
0497 DYNAMIC CELL STRUCTURES
Jorg Bruske, Gerald Sommer
0505 EXTRACTING RULES FROM ARTIFICIAL NEURAL NETWORKS WITH DISTRIBUTED REPRESENTATIONS
Sebastian Thrun
0513 CAPACITY AND INFORMATION EFFICIENCY OF A BRAIN-LIKE ASSOCIATIVE NET
Bruce Graham, David Wilishaw
0521 BOOSTING THE PERFORMANCE OF RBF NETWORKS WITH DYNAMIC DECAY ADJUSTMENT
Michael R. Berthold, Jay Diamond
0529 SIMPLIFYING NEURAL NETS BY DISCOVERING FLAT MINIMA
Sepp Hochreiter, Jurgen Schmidhuber
0537 LEARNING WITH PRODUCT UNITS
Laurens Leerink, C. Lee Giles, Bill G. Home, Marwan A. Jabri
0545 DETERMINISTIC ANNEALING VARIANT OF THE EM ALGORITHM
Naonori Ueda, Ryohei Nakano
0553 DIFFUSION OF CREDIT IN MARKOVIAN MODELS
Yoshua Bengio, Paolo Frasconi
0561 FACTORIAL LEARNING BY CLUSTERING FEATURES
Joshua B. Tenenbaum, Emmanuel V. Todorov
0569 INTERIOR POINT IMPLEMENTATIONS OF ALTERNATING MINIMIZATION TRAINING
Michael Lemmon, Peter T. Szymanski
0577 SARDNEI: A SELF-ORGANIZING FEATURE MAP FOR SEQUENCES
Daniel L. James, Risto Miikkulainen
0585 CONVERGENCE PROPERTIES OF THE K-MEANS ALGORITHMS
Leon Bottou, Yoshua Bengio
0593 ACTIVE LEARNING FOR FUNCTION APPROXIMATION
Kah Kay Sung, Partha Niyogi
0601 ANALYSIS OF UNSTANDARDIZED CONTRIBUTIONS IN CROSS CONNECTED NETWORKS
Thomas R. Shultz, Yuriko Oshima-Takane, Yoshio Takane
0609 TEMPLATE-BASED ALGORITHMS FOR CONNECTIONIST RULE EXTRACTION
Jay A. Alexander, Michael C. Mozer
0617 FACFORIAL LEARNING AND THE EM ALGORITHM
Zoubin Ghahramani
0625 A GROWING NEURAL GAS NETWORK LEARNS TOPOLOGIES
Bernd Fritzke
0633 AN ALTERNATIVE MODEL FOR MIXTURES OF EXPERTS
Lei Xu, Michael I. Jordan, Geoffrey E. Hinton
0641 ESTIMATING CONDITIONAL PROBABILITY DENSITIES FOR PERIODIC VARIABLES
Chris M. Bishop, Claire Legleye
0649 EFFECTS OF NOISE ON CONVERGENCE AND GENERALIZATION IN RECURRENT NETWORKS
Kam Jim, Bill G. Home, C. Lee Giles
0657 LEARNING MANY RELATED TASKS AT THE SAME TIME WITH BACKPROPAGATION
Rich Caruana
0665 A RAPID GRAPH-BASED METHOD FOR ARBITRARY TRANSFORMATION-INVARIANT PATTERN CLASSIFICATION
Alessandro Sperduti, David G. Stork
0673 RECURRENT NETWORKS: SECOND ORDER PROPERTIES AND PRUNING
Morten With Pedersen, Lars Kai Hansen
0681 CLASSIFYING WITH GAUSSIAN MIXTURES AND CLUSTERS
Nanda Kambhatla, Todd K. Leen
0689 EFFICIENT METHODS FOR DEALING WITH MISSING DATA IN SUPERVISED LEARNING
Volker Tresp, Ralph Neuneier, Subutai Ahmad
0697 AN EXPERIMENTAL COMPARISON OF RECURRENT NEURAL NETWORKS
Bill G. Home, C. Lee Giles
0705 ACTIVE LEARNING WITH STATISTICAL MODELS
David Cohn, Zoubin Ghahramani, Michael I. Jordon
0713 LEARNING WITH PREKNOWLEDGE: CLUSTERING WITH POINT AND GRAPH MATCHING DISTANCE MEASURES
Steven Gold, Anand Rangarajan, Eric Mjolsness

PART VI IMPLEMENTATIONS

0721 DIRECT MULTI-STEP TIME SERIES PREDICTION USING TD(λ)
Peter Kazlas, Andreas S. Weigend
0731 ICEG MORPHOLOGY CLASSIFICATION USING AN ANALOGUE VLSI NEURAL NETWORK
Richard Coggins, Marwan Jabri, Barry Flower, Stephen Pickard
0739 A SILICON AXON
Bradley A. Minch, Paul Hasler, Chris Diorio, Carver Mead
0747 THE NI1000: HIGH SPEED PARALLEL VLSI FOR IMPLEMENTING MULTILAYER PERCEPTRONS
Michael P. Perrone, Leon N. Cooper
0755 A REAL TIME CLUSTERING CMOS NEURAL ENGINE
T. Serrano-Gotarredona, B. Linares-Barranco, J. L. Huertas
0763 PULSESTREAM SYNAPSES WITH NON-VOLATILE ANALOGUE AMORPHOUS-SILICON MEMORIES
A.J. Holmes, A. F. Murray, S. Churcher, J. Hajto, M. J. Rose
0771 A LAGRANGIAN FORMULATION FOR OPTICAL BACKPROPAGATION TRAINING IN KERR-TYPE OPTICAL NETWORKS
James E. Steck, Steven R. Skinner, Alvaro A. Cruz-Cabrara, Elizabeth C. Behrman
0779 A CHARGE-BASED CMOS PARALLEL ANALOG VECTOR QUANTIZER
Gert Cauwenberghs, Volnei Pedroni
0787 AN AUDITORY LOCALIZATION AND COORDINATE TRANSFORM CHIP
Timothy Horiuchi
0795 AN ANALOG NEURAL NETWORK INSPIRED BY FRACTAL BLOCK CODING
Fernando Pineda, Andreas G. Andreou
0803 A STUDY OF PARALLEL PERTURBATIVE GRADIENT DESCENT
D. Lippe, J. Aispector
0811 IMPLEMENTATION OF NEURAL HARDWARE WITH THE NEURAL VLSI OF URAN IN APPLICATIONS WITH REDUCED REPRESENTATIONS
Il-Song Han, Hwang-Soo Lee, Ki-Chul Kim

PART VII SPEECH AND SIGNAL PROCESSING

0817 SINGLE TRANSISTOR LEARNING SYNAPSES
Paul Hasler, Chris Diorio, Bradley A. Minch, Carver Mead
0827 PATTERN PLAYBACK IN THE '90S
Malcolm Slaney (Invited Paper)
0835 NON-LINEAR PREDICTION OF ACOUSTIC VECTORS USING HIERARCHICAL MIXTURES OF EXPERTS
S.R. Waterhouse, A. J. Robinson
0843 GLOVE-TALKII: MAPPING HAND GESTURES TO SPEECH USING NEURAL NETWORKS
S. Sidney Fels, Geoffrey Hinton
0851 VISUAL SPEECH RECOGNITION WITH STOCHASTIC NETWORKS
Javier Movellan
0859 HIERARCHICAL MIXTURES OF EXPERTS METHODOLOGY APPLIED TO CONTINUOUS SPEECH RECOGNITION
Ying Zhao, Richard Schwartz, Jason Sroka, John Makhoul
0867 CONNECTIONIST SPEAKER NORMALIZATION WITH GENERALIZED RESOURCE ALLOCATING NETWORKS
Cesare Furlanello, Diego Giuliani, Edmondo Trentin
0875 USING VOICE TRANSFORMATIONS TO CREATE ADDITIONAL TRAINING TALKERS FOR WORD SPOTTING
Eric I. Chang, Richard P. Lippmann

PART VIII VISUAL PROCESSING

0883 A COMPARISON OF DISCRETE-TIME OPERATOR MODELS FOR NONLINEAR SYSTEM IDENTIFICATION
Andrew D. Back, Ah Chung Tsoi
0893 LEARNING SACCADIC EYE MOVEMENTS USING MULTISCALE SPATIAL FILTERS
Rajesh P. N. Rao, Dana H Ballard
0901 A CONVOLUTIONAL NEURAL NETWORK HAND TRACKER
Steven J. Nowlan, John C. Platt
0909 CORRELATION AND INTERPOLATION NETWORKS FOR REAL-TIME EXPRESSION ANALYSIS/SYNTHESIS
Trevor Darrell, Irfan Essa, Alex Pentland
0917 LEARNING DIRECTION IN GLOBAL MOTION: TWO CLASSES OF PSYCHOPHYSICALLY-MOTIVATED MODELS
V. Sundareswaran, Lucia M. Vaina
0925 ASSOCIATIVE DECORRELATION DYNAMICS: A THEORY OF SELF-ORGANIZATION AND OPTIMIZATION IN FEEDBACK NETWORKS
Dawei W. Dong
0933 JPMAX: LEARNING TO RECOGNIZE MOVING OBJECTS AS A MODEL-FITTING PROBLEM
Suzanna Becker
0941 PCA-PYRAMIDS FOR IMAGE COMPRESSION
Horst Bischof, Kurt Hornik
0949 UNSUPERVISED CLASSIFICATION OF 3D OBJECTS FROM 2D VIEWS
Satoshi Suzuki, Hiroshi Ando
0957 NEW ALGORITHMS FOR 2D AND 3D POINT MATCHING: POSE ESTIMATION AND CORRESPONDENCE
Steven Gold, Chien Ping Lu, Anand Rangarajan, Suguna Pappu, Eric Mjolsness
0965 USING A NEURAL NET TO INSTANTIATE A DEFORMABLE MODEL
Christopher K. I. Williams, Michael D. Revow, Geoffrey E. Hinton
0973 NONLINEAR IMAGE INTERPOLATION USING MANIFOLD LEARNING
Christoph Bregler, Stephen M. Omohundro

PART IX APPLICATIONS

0981 COARSE-TO-FINE IMAGE SEARCH USING NEURAL NETWORKS
Clay D. Spence, John C. Pearson, Jim Bergen
0991 TRANSFORMATION INVARIANT AUTOASSOCIATION WITH APPLICATION TO HANDWRITTEN CHARACTER RECOGNITION
Holger Schwenk, Maurice Milgram
0999 LEARNING PROTOTYPE MODELS FOR TANGENT DISTANCE
Trevor Hastie, Patrice Simard, Eduard Sackinger
1007 REAL-TIME CONTROL OF TOKAMAK PLASMA USING NEURAL NETWORKS
Chris M. Bishop, Paul S. Haynes, Mike E. U. Smith, Tom N. Todd, David L. Trotman, Cohn G. Windsor
1015 RECOGNIZING HANDWRITTEN DIGITS USING MIXTURES OF LINEAR MODELS
Geoffrey E. Hinton, Michael Revow, Peter Dayan
1023 OPTIMAL MOVEMENT PRIMITIVES
Terence Sanger
1031 AN INTEGRATED ARCHITECTURE OF ADAPTIVE NEURAL NETWORK CONTROL FOR DYNAMIC SYSTEMS
Liu Ke, Robert L. Tokar, Brian D. McVey
1039 A CONNECTIONIST TECHNIQUE FOR ACCELERATED TEXTUAL INPUT: LETTING A NETWORK DO THE TYPING
Dean Pomerleau
1047 PREDICTIVE CODING WITH NEURAL NETS: APPLICATION TO TEXT COMPRESSION
Jurgen Schmidhuber, Stefan Heil
1055 PREDICTING THE RISK OF COMPLICATIONS IN CORONARY ARTERY BYPASS OPERATIONS USING NEURAL NETWORKS
Richard P. Lippmann, Linda Kukolich, David Shahian
1063 COMPARING THE PREDICTION ACCURACY OF ARTIFICIAL NEURAL NETWORKS AND OTHER STATISTICAL MODELS FOR BREAST CANCER SURVIVAL
Harry B. Burke, David B. Rosen, Philip H. Goodman
1069 LEARNING TO PLAY THE GAME OF CHESS
Sebastian Thrun
1077 A MIXTURE MODEL SYSTEM FOR MEDICAL AND MACHINE DIAGNOSIS
Magnus Stensmo, Terrence J. Sejnowski
1085 INFERRING GROUND TRUTH FROM SUBJECTIVE LABELLING OF VENUS IMAGES
Padhraic Smyth, Usama Fayyad, Michael Burl, Pietro Perona, Pierre Baldi
1093 THE USE OF DYNAMIC WRITING INFORMATION IN A CONNECTIONIST ON-LINE CURSIVE HANDWRITING RECOGNITION SYSTEM
Stefan Manke, Michael Finke, Alex Waibel
1101 ADAPTIVE ELASTIC INPUT FIELD FOR RECOGNITION IMPROVEMENT
Minoru Asogawa
1109 PAIRWISE NEURAL NETWORK CLASSIFIERS WITH PROBABILISTIC OUTPUTS
David Price, Stefan Knerr, Leon Personnaz, Gerard Dreyfus
1117 INTERFERENCE IN LEARNING INTERNAL MODELS OF INVERSE DYNAMICS IN HUMANS
Reza Shadmehr, Tom Brashers-Krug, Ferdinando Mussa-Ivaldi
1125 COMPUTATIONAL STRUCTURE OF COORDINATE TRANSFORMATIONS: A GENERALIZATION STUDY
Zoubin Ghahramani, Daniel M. Wolpert, Michael I. Jordan
1133 Author Index
1137 Keyword Index

NIPS'1995 Volume 8 : Table of Contents
David Touretzky, Michael Mozer, Mark Hasselmo (eds), MIT Press (1996)
i Title Pages
v Table of Contents
xv Preface
xvii Contributors

PART I COGNITIVE SCIENCE

0003 Learning the Structure of Similarity
J. B. TENENBAUM
0010 A Model of Spatial Representations in Parietal Cortex Explains Hemineglect
A. POUGET, T. J. SEJNOWSKI
0017 Human Reading and the Curse of Dimensionality
G. L. MARTIN
0024 Extracting Tree-structured Representations of Trained Networks
M. W. CRAVEN, J. W. SHAVLIK
0031 Harmony Networks Do Not Work
R. GOURLEY
0038 Dynamics of Attention as Near Saddle-node Bifurcation Behavior
H. NAKAHARA, K. DOYA
0045 Rapid Quality Estimation of Neural Network Input Representations
K. J. CHERKAUER, J. W. SHAVLIK

PART II NEUROSCIENCE

0052 A Model of Auditory Streaming
S. L. MCCABE, M. J. DENHAM
0061 Modeling Interactions of the Rat's Place and Head Direction Systems
A. D. REDISH, D. S. TOURETZKY
0068 Correlated Neuronal Response: Time Scales and Mechanisms
W. BAIR, E. ZOHARY, C. KOCH
0075 Information through a Spiking Neuron
C. STEVENS, A. ZADOR
0082 Reorganization of Somatosensory Cortex after Tactile Training
R. S. PETERSEN. J. G. TAYLOR
0089 A Dynamical Model of Context Dependencies for the Vestibulo-Ocular Reflex
O. J. M. D. COENEN, T. J. SEJNOWSKI
0096 The Role of Activity in Synaptic Competition at the Neuromuscular Junction
S. R. H. JOSEPH, D. J. WILLSHAW
0103 When Is an Integrate-and-fire Neuron like a Poisson Neuron?
C. F. STEVENS, A. ZADOR
0110 How Perception Guides Production in Birdsong Learning
C. L. FRY
0117 The Geometry of Eye Rotations and Listing's Law
A. A. HANDZEL, T. FLASH
0124 Temporal Coding in the Submillisecond Range: Model of Barn Owl Auditory Pathway
R. KEMPTER, W. GERSTNER, J. L. VAN HEMMEN, H. WAGNER
0131 Cholinergic Suppression of Transmission May Allow Combined Associative Memory Function and Self-organization in the Neocortex
M. E. HASSELMO, M. CEKIC
0138 A Predictive Switching Model of Cerebellar Movement Control
A. G. BARTO, J. T. BUCKINGHAM, J. C. HOUK
0145 Independent Component Analysis of Electroencephalographic Data
S. MAKEIG, A. J. BELL, T. P. JUNG, T. J. SEJNOWSKI
0152 Simulation of a Thalamocortical Circuit for Computing Directional Heading in the Rat
H. T. BLAIR

PART III THEORY

0159 Plasticity of Center-Surround Opponent Receptive Fields in Real and Artificial Neural Systems of Vision
S. YASUI, T. FURUKAWA, M. YAMADA, T. SAITO
0169 Learning Model Bias
J. BAXTER
0176 Statistical Theory of Overtraining--Is Cross-Validation Asymptotically Effective?
S. AMARI, N. MURATA, K. R. MULLER, M. FINKE, H. YANG
0183 A Bound on the Error of Cross Validation Using the Approximation and Estimation Rates, with Consequences for the Training-test Split
M. KEARNS
0190 Learning with Ensembles: How Overfitting Can Be Useful
P. SOLLLCH, A. KROGH
0197 Neural Networks with Quadratic VC Dimension
P. KOIRAN, E. D. SONTAG
0204 Sample Complexity for Learning Recurrent Perceptron Mappings
B. DASGUPTA, E. D. SONTAG
0211 On the Computational Power of Noisy Spiking Neurons
W. MAASS
0218 A Realizable Learning Task Which Exhibits Overfitting
S. BOS
0225 Stable Dynamic Parameter Adaptation
S. M. RUGER
0232 Estimating the Bayes Risk from Sample Data
R. R. SNAPP, T. XU
0239 Recursive Estimation of Dynamic Modular RBF Networks
V. KADIRKAMANATHAN, M. KADIRKAMANATHAN
0246 On Neural Networks with Minimal Weights
V. BOHOSSIAN, J. BRUCK
0253 Modern Analytic Techniques to Solve the Dynamics of Recurrent Neural Networks
A. C. C. COOLEN, S. N. LAUGHTON, D. SHERRINGTON
0260 Implementation Issues in the Fourier Transform Algorithm
Y. MANSOUR, S. SAHAR
0267 Generalisation of a Class of Continuous Neural Networks
J. SHAWE-TAYLOR, J. ZHAO
0274 Gradient and Hamiltonian Dynamics Applied to Learning in Neural Networks
J. W. HOWSE, C. T. ABDALLAH, G. L. HEILEMAN
0281 Optimization Principles for the Neural Code
M. DEWEESE
0288 Strong Unimodality and Exact Learning of Constant Depth μ-Perceptron Networks
M. MARCHAND, S. HADJIFARADJI
0295 Active Learning in Multilayer Perceptrons
K. FUKUMIZU
0302 Dynamics of On-line Gradient Descent Learning for Multilayer Neural Networks
D. SAAD, S. A. SOLLA
0309 Worst-case Loss Bounds for Single Neurons
D. P. HELMBOLD, J. KIVINEN, M. K. WARMUTH
0316 Exponentially Many Local Minima for Single Neurons
P. AUER, M. HERBSTER, M. K. WARMUTH
0323 Adaptive Back-Propagation in On-line Learning of Multilayer Networks
A. H. L. WEST, D. SAAD
0330 Optimizing Cortical Mappings
G. J. GOODHILL, S. FINCH, T.J. SEJNOWSKI
0337 Quadratic-type Lyapunov Functions for Competitive Neural Networks with Different Time-scales
A. MEYER-BASE
0344 Examples of Learning Curves from a Modified VC-formalism
A. KOWALCZYK, J. SZYMANSKI, P. L. BARTLETT, R. C. WILLIAMSON
0351 Bayesian Methods for Mixtures of Experts
S. WATERHOUSE, D. MACKAY, T. ROBINSON
0358 Some Results on Convergent Unlearning Algorithm
S. A. SEMENOV, I. B. SHUVALOVA
0365 Geometry of Early Stopping in Linear Networks
R. DODIER

PART IV ALGORITHMS AND ARCHITECTURES

0372 Absence of Cycles in Symmetric Neural Networks
X. WANG, A. JAGOTA, E BOTELHO, M. GARZON
0381 Adaptive Mixture of Probabilistic Transducers
Y. SINGER
0388 REMAP: Recursive Estimation and Maximization of A Posteriori Probabilities--Application to Transition-based Connectionist Speech Recognition
Y. KONIG, H. BOURLARD, N. MORGAN
0395 Recurrent Neural Networks for Missing or Asynchronous Data
Y. BENGIO, F. GINGRAS
0402 Family Discovery
S. M. OMOHUNDRO
0409 Discriminant Adaptive Nearest Neighbor Classification and Regression
T. HASTIE, R. TIBSHIRANI
0416 Clustering Data through an Analogy to the Potts Model
M. BLATT, S. WISEMAN, E. DOMANY
0423 Generalized Learning Vector Quantization
A. SATO, K. YAMADA
0430 Stochastic Hillclimbing as a Baseline Method for Evaluating Genetic Algorithms
A. JUELS, M. WATTENBERG
0437 Symplectic Nonlinear Component Analysis
L. C. PARRA
0444 A Unified Learning Scheme: Bayesian-Kuilback Ying-Yang Machine
L. XU
0451 Universal Approximation and Learning of Trajectories Using Oscillators
P. BALDI, K. HORNIK
0458 A Smoothing Regularizer for Recurrent Neural Networks
L. WU, J. MOODY
0465 EM Optimization of Latent-Variable Density Models
C. M. BISHOP, M. SVENSEN, C. K. I. WILLIAMS
0472 Factorial Hidden Markov Models
Z. GHAHRAMANI, M. I. JORDAN
0479 Boosting Decision Trees
H. DRUCKER, C. CORTES
0486 Exploiting Tractable Substructures in Intractable Networks
L. K. SAUL. M. I. JORDAN
0493 Hierarchical Recurrent Neural Networks for Long-term Dependencies
S. E. HIHI, Y. BENGIO
0500 Discovering Structure in Continuous Variables Using Bayesian Networks
R. HOFMANN, V. TRESP
0507 Using Pairs of Data Points to Define Splits for Decision Trees
G. E. HINTON, M. REVOW
0514 Gaussian Processes for Regression
C. K. I. WILLIAMS, C. E. RASMUSSEN
0521 Pruning with Generalization Based Weight Saliencies: λOBD, λOBS
M. W. PEDERSEN. L. K. HANSEN, J. LARSEN
0528 Fast Learning by Bounding Likelihoods in Sigmoid Type Belief Networks
T. JAAKKOLA, L. K. SAUL. M., I. JORDAN
0535 Generating Accurate and Diverse Members of a Neural-network Ensemble
D. W. OPITZ, J. W. SHAVLIK
0542 Improved Gaussian Mixture Density Estimates Using Bayesian Penalty Terms and Network Averaging
D. ORMONEIT, V. TRESP
0549 Explorations with the Dynamic Wave Model
T. P. REBOTIER, J. L. ELMAN
0556 The Capacity of a Bump
G. W. FLAKE
0563 Tempering Backpropagation Networks: Not All Weights Are Created Equal
N. N. SCHRAUDOLPH, T. J. SEJNOWSKI
0570 Investment Learning with Hierarchical PSOM5
J. WALTER, H. RITTER
0577 Learning Long-term Dependencies Is Not as Difficult with NARX Networks
T. LIN, B. G. HORNE, P. TINO, C. L. GILES
0584 Constructive Algorithms for Hierarchical Mixtures of Experts
S. R. WATERHOUSE, A. J. ROBINSON
0591 An Information-theoretic Learning Algorithm for Neural Network Classification
D. MILLER, A. RAO, K. ROSE, A. GERSHO
0598 A Practical Monte Carlo Implementation of Bayesian Learning
C. E. RASMUSSEN
0605 From Isolation to Cooperation: An Alternative View of a System of Experts
S. SCHAAL, C. C. ATKESON
0612 Finite State Automata that Recurrent Cascade-Correlation Cannot Represent
S. C. KREMER
0619 SPERT-II: A Vector Microprocessor System and Its Application to Large Problems in Backpropagation Training
J. WAWRZYNEK. K. ASANOVIC, B. KINGSBURY, J. BECK, D. JOHNSON, N. MORGAN
0626 Softassign versus Softmax: Benchmarks in Combinatorial Optimization
S. GOLD, A. RANGARAJAN
0633 A Multiscale Attentional Framework for Relaxation Neural Networks
D. I. TSIOUTSIAS, E. MJOLSNESS
0640 Is Learning the n-th Thing Any Easier Than Learning the First?
S. THRUN
0647 Using Unlabeled Data for Supervised Learning
G. TOWELL
0654 Learning Sparse Perceptrons
J. C. JACKSON, M. W. CRAVEN

PART V IMPLEMENTATIONS

0661 Does the Wake-sleep Algorithm Produce Good Density Estimators?
B. J. FREY, G. E. HINTON, P. DAYAN
0671 Improved Silicon Cochlea Using Compatible Lateral Bipolar Transistors
A. VAN SCHAIK, E. FRAGNIERE, E. VITTOZ
0678 Adaptive Retina with Center-Surround Receptive Field
S. C. LIU. K. BOAHEN
0685 Neuron-MOS Temporal Winner Search Hardware for Fully-parallel Data Processing
T. SHIBATA, T. NAKAI, T. MORIMOTO. R. KAIHARA, T. YAMASHITA, T. OHMI
0692 Analog VLSI Processor Implementing the Continuous Wavelet Transform
R. T. EDWARDS. G. CAUWENBERGHS
0699 Silicon Models for Auditory Scene Analysis
J. LAZZARO, J. WAWRZYNEK
0706 VLSI Model of Primate Visual Smooth Pursuit
R. ETIENNE-CUMMINGS, J. VAN DER SPIEGEL, P. MUELLER
0713 Model Matching and SFMD Computation
S. REHFUSS, D. HAMMERSTROM

PART VI SPEECH AND SIGNAL PROCESSING

0720 Parallel Analog VLSI Architectures for Computation of Heading Direction and Time-to-contact
G. INDIVERI, J. KRAMER, C. KOCH
0729 Onset-based Sound Segmentation
L. S. SMITH
0736 Laterally Interconnected Self-organizing Maps in Handwritten Digit Recognition
Y. CHOE, J. SIROSH, R. MIIKKULAINEN
0743 Forward-backward Retraining of Recurrent Neural Networks
A. SENIOR, T. ROBINSON
0750 Context-dependent Classes in a Hybrid Recurrent Network-HMM Speech Recognition System
D. KERSHAW, T. ROBINSON, M. HOCHBERG
0757 A New Learning Algorithm for Blind Signal Separation
S. AMARI, A. CICHOCKI, H. H. YANG
0764 Handwritten Word Recognition Using Contextual Hybrid Radial Basis Function Network/Hidden Markov Models
B. LEMARIE, M. GILLOUX, M. LEROUX
0771 Selective Attention for Handwritten Digit Recognition
E. ALPAYDIN
0778 KODAK IMAGELINK TM OCR Alphanumeric Handprint Module
A. SHUSTOROVICH, C. W. THRASHER

PART VII VISION

0785 The Gamma MLP for Speech Phoneme Recognition
S. LAWRENCE, A. C. TSOI, A. D. BACK
0795 A Framework for Nonrigid Matching and Correspondence
S. PAPPU, S. GOLD, A. RANGARAJAN
0802 Control of Selective Visual Attention: Modeling the "Where" Pathway
E. NIEBUR, C. KOCH
0809 Unsupervised Pixel-prediction
W. R. SOFTKY
0816 Learning to Predict Visibility and Invisibility from Occlusion Events
J. A. MARSHALL, R. K. ALLEY, R. S. HUBBARD
0823 Classifying Facial Action
M. S. BARTLETT, P. A. VIOLA, T. J. SEJNOWSKI, B. A. GOLOMB, J. LARSEN, C. HAGER, P. EKMAN
0830 Modeling Saccadic Targeting in Visual Search
R. P. N. RAO, G. J. ZELINSKY, M. M. HAYHOE, D. H. BALLARD
0837 A Model of Transparent Motion and Non-transparent Motion Aftereffects
A. GRUNEWALD
0844 A Neural Network Model of 3-D Lightness Perception
L. PESSOA, W. D. ROSS
0851 Empirical Entropy Manipulation for Real-world Problems
P. VIOLA, N. N. SCHRAUDOLPH, T. J. SEJNOWSKI
0858 Active Gesture Recognition Using Learned Visual Attention
T. DARRELL, A. PENTLAND

PART VIII APPLICATIONS

0865 SEEMORE: A View-based Approach to 3-D Object Recognition Using Multiple Visual Cues
B. W. MEL
0875 Human Face Detection in Visual Scenes
H. A. ROWLEY, S. BALUJA, T. KANADE
0882 Improving Committee Diagnosis with Resampling Techniques
B. PARMANTO, P. W. MUNRO, H. R. DOYLE
0889 Primitive Manipulation Learning with Connectionism
Y. MATSUOKA
0896 Beating a Defender in Robotic Soccer: Memory-based Learning of a Continuous Function
P. STONE, M. VELOSO
0903 Visual Gesture-based Robot Guidance with a Modular Neural System
E. LITTMANN, A. DREES, H. RITTER
0910 A Novel Channel Selection System in Cochlear Implants Using Artificial Neural Network
M. A. JABRI, R. J. WANG
0917 Prediction of Beta Sheets in Proteins
A. KROGH, S. K. RIIS
0924 A Neural Network Autoassociator for Induction Motor Failure Prediction
T. PETSCHE, A. MARCANTONIO, C. DARKEN, S. J. HANSON, G. M. KUHN, I. SANTOSO
0931 Using Feedforward Neural Networks to Monitor Alertness from Changes in EEG Correlation and Coherence
S. MAKEIG, T. P. JUNG, T. J. SEJNOWSKI
0938 A Neural Network Classifier for the 11000 OCR Chip
J. C. PLATT, T. P. ALLEN
0945 Predictive Q-Routing: A Memory-based Reinforcement Learning Approach to Adaptive Traffic Control
S. P. M. CHOI, D. YEUNG
0952 Optimal Asset Allocation Using Adaptive Dynamic Programming
R. NEUNEIER
0959 Using the Future to "Sort Out" the Present: Rankprop and Multitask Learning for Medical Risk Evaluation
R. CARUANA, S. BALUJA, T. MITCHELL
0966 Stock Selection via Nonlinear Multi-factor Models
A. U. LEVIN
0973 Experiments with Neural Networks for Real Time Implementation of Control
P. CAMPBELL, M. DALE, H. L. FERRA, A. KOWALCZYK

PART IX CONTROL

0980 High-speed Airborne Particle Monitoring Using Artificial Neural Networks
A. FERGUSON, T. SABISCH, P. KAYE, L. C. DIXON, H. BOLOURI
0989 A Dynamical Systems Approach for a Learnable Autonomous Robot
J. TANI, N. FUKUMURA
0996 Parallel Optimization of Motion Controllers via Policy Iteration
J. A. COELHO JR., R. SITARAMAN, R. A. GRUPEN
1003 Learning Fine Motion by Markov Mixtures of Experts
M. MEILA, M. I. JORDAN
1010 Neural Control for Nonlinear Dynamic Systems
S. YU, A. M. ANNASWAMY
1017 Improving Elevator Performance Using Reinforcement Learning
R. H. CRITES. A. G. BARTO
1024 High-performance Job-Shop Scheduling with a Time-delay TD(λ) Network
W. ZHANG, 1. G. DIETTERICH
1031 Competence Acquisition in an Autonomous Mobile Robot Using Hardware Neural Techniques
G. JACKSON, A. F. MURRAY
1038 Generalization in Reinforcement Learning: Successful Examples Using Sparse Coarse Coding
R. S. SUTTON
1045 Stable Linear Approximations to Dynamic Programming for Stochastic Control Problems with Local Transitions
B. V. ROY, J. N. TSITSIKLIS
1052 Stable Fitted Reinforcement Learning
G. J. GORDON
1059 Improving Policies without Measuring Merits
P. DAYAN, S. P. SINGH
1066 Memory-based Stochastic Optimization
A. W. MOORE, J. SCHNEIDER
1073 Temporal Difference in Learning in Continuous Time and Space
K. DOYA
1080 Reinforcement Learning by Probability Matching
P. N. SABES, M. I. JORDAN
1087 Author Index
1091 Keyword Index

NIPS'1996 Volume 9 : Table of Contents
Michael Mozer, Michael Jordan, Thomas Petsche (eds), MIT Press (1997)
i Title Pages
v Table of Contents
xiii Preface
xv NIPS Committees
xvii Reviewers

Part I Cognitive Science

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

NIPS'1997 Volume 10 : Table of Contents
Michael Jordan, Michael Kearns, Sara Solla (eds), MIT Press (1998)
i Title Pages
v Table of Contents
xiii Preface
xv NIPS Committees
xvii Reviewers

Part I Cognitive Science

0003 Synchronized Auditory and Cognitive 40 Hz Attentional Streams, and the Impact of Rhythmic Expectation on Auditory Scene Analysis,
Bill Baird
0010 On Parallel versus Serial Processing: A Computational Study of Visual Search,
Eyal Cohen and Eytan Ruppin
0017 Task and Spatial Frequency Effects on Face Specialization,
Matthew N. Dailey and Garrison W. Cottrell
0024 Neural Basis of Object-Centered Representations,
Sophie Deneve and Alexandre Pouget
0031 A Neural Network Model of Naive Preference and Filial Imprinting in the Domestic Chick,
Lucy E. Hadden
0038 Adaptation in Speech Motor Control,
John F. Houde and Michael I. Jordan
0045 Learning Human-like Knowledge by Singular Value Decomposition.' A Progress Report,
Thomas K. Landauer, Darrell Laham and Peter Foltz
0052 Multi-modular Associative Memory,
Nit Levy, David Horn and Eytan Ruppin
0059 Serial Order in Reading Aloud: Connectionist Models and Neighborhood Structure,
Jeanne C. Milostan and Garrison W. Cottrell
0066 A Superadditive-Impairment Theory of Optic Aphasia,
Michael C. Mozer, Mark Sitton and Martha Farah
0073 A Hippocampal Model of Recognition Memory,
Randall C. O'Reilly, Kenneth A. Norman and James L. McClelland
0080 Correlates of Attention in a Model of Dynamic Visual Recognition,
Rajesh P. N. Rao
0087 Recurrent Neural Networks Can Learn to Implement Symbol-Sensitive Counting,
Paul Rodriguez and Janet Wiles
0094 Comparison of Human and Machine Word Recognition,
Markus Schenkel, Cyril Latimer and Marwan Jabri

Part II Neuroscience

0103 Coding of Naturalistic Stimuli by Auditory Midbrain Neurons,
Hagai Attias and Christoph E. Schreiner
0110 Refractoriness and Neural Precision,
Michael J. Berry II and Markus Meister
0117 Statistical Models of Conditioning,
Peter Dayan and Theresa Long
0124 Characterizing Neurons in the Primary Auditory Cortex of the Awake Primate Using Reverse Correlation,
R. Christopher deCharms and Michael M. Mer-zenich
0131 Using Helmholtz Machines to Analyze Multi-channel Neuronal Recordings,
Virginia R. de Sa, R. Christopher deCharms and Michael M. Merzenich
0138 Instabilities in Eye Movement Control: A Model of Periodic Alternating Nystagmus,
Ernst R. Dow and Thomas J. Anastasio
0145 Hippocampal Model of Rat Spatial Abilities Using Temporal Difference Learning,
David J. Foster, Richard G. M. Morris and Peter Dayan
0152 Gradients for Retinotectal Mapping,
Geoffrey J. Goodhill
0159 A Mathematical Model of Axon Guidance by Diffusible Factors,
Geoffrey J. Goodhill
0166 Computing with Action Potentials (Invited Talk),
John J. Hopfield, Carlos D. Brody and Sam Roweis
0173 A Model of Early Visual Processing,
Laurent Itti, Jochen Braun, Dale K. Lee and Christof Koch
0180 Perturbative M-Sequences for Auditory Systems Identification,
Maxk Kvale and Christoph E. Schreiner
0187 Effects of Spike Timing Underlying Binocular Integration and Rivalry in a Neural Model of Early Visual Cortex,
Erik D. Lumer
0194 Dynamic Stochastic Synapses as Computational Units,
Wolfgang Maass and Anthony M. Zador
0201 Synaptic Transmission: An Information-Theoretic Perspective,
Amit Manwani and Christof Koch
0208 Toward a Single-Cell Account for Binocular Disparity Tuning: An Energy Model May Be Hiding in Your Dendrites,
Bartlett W. Mel, Daniel L. Ruderman and Kevin A. Archie
0215 Just One View: Invariances in Inferotemporal Cell Tuning,
Maximilian Riesenhuber and Tomaso Poggio
0222 On the Separation of Signals from Neighboring Cells in Tetrode Recordings,
Maneesh Sahani, John S. Pezaris and Richard A. Andersen
0229 Independent Component Analysis for Identification of Artifacts in MagnetoencephaIographic Recordings,
Ricardo firio, Veikko Jousmfiki, Matti H'fi. mfil'ninen, Riitta Hari and Erkki Oja
0236 Modeling Complex Cells in an Awake Macaque during Natural Image Viewing,
William E. Vinje and Jack L. Gallant

Part III Theory

0245 The Canonical Distortion Measure in Feature Space and 1-NN Classification,
Jonathan Baxter and Peter Bartlett
0252 Multiple Threshold Neural Logic,
Vasken Bohossian and Jehoshua Brock
0259 Generalization in Decision Trees and DNF: Does Size Matter?
Mostefa Golea, Peter Bartlett, Wee Sun Lee and Llew Mason
0266 Selecting Weighting Factors in Logarithmic Opinion Pools,
Tom Heskes
0273 New Approximations of Differential Entropy for Independent Component Analysis and Projection Pursuit,
Aapo Hyv'firinen
0280 Boltzmann Machine Learning Using Mean Field Theory and Linear Response Correction,
Hilbert J. Kappen and F. B. Rodriguez
0287 Relative Loss Bounds for Multidimensional Regression Problems,
Jyrki Kivinen and Manfred K. Warmuth
0294 Asymptotic Theory for Regularization: One-Dimensional Linear Case,
Petri Koistinen
0301 Two Approaches to Optimal Annealing,
Todd K. Leen, Bernhard Schottky and David Saad
0308 Structural Risk Minimization for Nonparametric Time Series Prediction,
Ron Meir
0315 Analytical Study of the Interplay between Architecture and Predictability,
Avner Priel, Ido Kanter and David A. Kessler
0322 Globally Optimal On-line Learning Rules,
Magnus Rattray and David Saad
0329 Minimax and Hamiltonian Dynamics of Excitatory-Inhibitory Networks,
H. Sebastian Seung, Tom J. Richardson, Jeffrey C. Lagarias and John J. Hopfield
0336 Data-Dependent Structural Risk Minimization for Perceptron Decision Trees,
John Shawe-qnaylor and Nello Cristianini
0343 From Regularization Operators to Support Vector Kernels,
Alex J. Smola and Bernhard Schoelkopf
0350 The Rectified Gaussian Distribution,
Nicholas D. Socci, Daniel D. Lee and H. Sebastian Seung
0357 On-line Learning from Finite Training Sets in Nonlinear Networks,
Peter Sollich and David Barber
0364 Competitive On-line Linear Regression,
Volodya Vovk
0371 On the Infeasibility of Training Neural Networks with Small Squared Errors,
Van H. Vu
0378 The Storage Capacity of a Fully-Connected Committee Machine,
Yuansheng Xiong, Chulan Kwon and Jong-Hoon Oh
0385 The Efficiency and the Robustness of Natural Gradient Descent Learning Rule,
Howard H. Yang and Shun-ichi Amari

Part IV Algorithms and Architecture

0395 Ensemble Learning for Multi-Layer Networks,
David Barber and Christopher M. Bishop
0402 Radial Basis Functions: A Bayesian Treatment,
David Barber and Bernhard Schottky
0409 Shared Context Probabilistic Transducers,
Yoshua Bengio, Samy Bengio, Jean-Franqois Isabelle and Yoram Singer
0416 Approximating Posterior Distributions in Belief Networks Using Mixtures,
Christopher M. Bishop, Nell Lawrence, Tommi Jaakkola and Michael I. Jordan
0423 Receptive Field Formation in Natural Scene Environments: Comparison of Single Cell Learning Rules,
Brian S. Blais, Nathan Intrator, Harel Shouval and Leon N. Cooper
0430 An Annealed Self-Organizing Map for Source Channel Coding,
Matthias Burger, Thore Graepel and Klaus Obermayer
0437 Incorporating Test Inputs into Learning,
Zehra Cataltepe and Malik Magdon-Isrnail
0444 On Efficient Heuristic Ranking of Hypotheses,
Steve Chien, Andre Stechert and Darren Mutz
0451 Learning to Order Things,
Wiliam W. Cohen, Robert E. Schapire and Yoram Singer
0458 Regularisation in Sequential Learning Algorithms,
Joao F. G. de Freitas, Mahesan Niranjan and Andrew H. Gee
0465 Agnostic Classification of Markovian Sequences,
Ran E1-Yaniv, Shai Fine and Naftali Tlshby
0472 Ensemble and ModularApproaches for Face Detection: A Comparison,
Raphael Feraud and Olivier Bernier
0479 A Revolution: Belief Propagation in Graphs with Cycles,
Brendan J. Frey and David J. C. MacKay
0486 Hierarchical Non-linear Factor Analysis and Topographic Maps,
Zoubin Ghahramani and Geoffrey E. Hinton
0493 Regression with Input-dependent Noise: A Gaussian Process Treatment,
Paul W. Goldberg, Christopher K. I. Williams and Christopher M. Bishop
0500 Linear Concepts and Hidden Variables: An Empirical Study,
Adam J. Grove and Dan Roth
0507 Classification by Pairwise Coupling,
Trevor Hastie and Robert Tibshirani
0514 Unsupervised On-line Learning of Decision Trees for Hierarchical Data Analysis,
Marcus Held and Joachim M. Buhmann
0521 Nonlinear Markov Networks for Continuous Variables,
Reimar Hofmann and Volker Tresp
0528 Active Data Clustering,
Thomas Hofmann and Joachim M. Buhnmnn
0535 Function Approximation with the Sweeping Hinge Algorithm,
Don R. Hush, Fernando Lozano and Bill Home
0542 The Error Coding and Substitution PaCTs,
Gareth James and Trevor Hastie
0549 S-Map: A Network with a Simple Self-Organization Algorithm for Generarive Topographic Mappings,
Kimmo Kiviluoto and Erkki Oja
0556 Learning Nonlinear Overcomplete Representations for Efficient Coding,
Michael S. Lewicki and Terrence J. Sejnowski
0563 Factorizing Multivariate Function Classes,
Juan K. Lin
0570 A Framework for Multiple-Instance Learning,
Oded Maron and Tonaris Lozano-Perez
0577 An Application of Reversible-Jump MCMC to Multivariate Spherical Gaussian Mixtures,
Alan D. Marts
0584 Estimating Dependency Structure as a Hidden Variable,
Marina Meila and Michael I. Jordan
0591 Combining Classifiers Using Correspondence Analysis,
Christopher J. Merz
0598 Learning Path Distributions Using Nonequilibrium Diffusion Networks,
Paul Mineiro, Javier Movellan and Ruth J. Williams
0605 Learning Generarive Models with the Up-Propagation Algorithm,
Jong-Hoon Oh and H. Sebastian Seung
0612 An Incremental Nearest Neighbor Algorithm with Queries,
Joel Ratsaby
0619 RCC Cannot Compute Certain FSA,
Even with Arbitrary Transfer Functions, Mark Ring
0626 EM Algorithms for PCA and SPCA,
Sam Roweis
0633 Local Dimensionality Reduction,
Stefan Schaal, Sethu Vijayakumar and Christopher G. Atkeson
0640 Prior Knowledge in Support Vector Kernels,
Bernhard Sch61kopf, Patrice Simard, Alex J. Smola and Vladimir Vapnik
0647 Training Methods for Adaptive Boosting of Neural Networks,
Holger Schwenk and Yoshua Bengio
0654 Learning Continuous Attractors in Recurrent Networks,
H. Sebastian Seung
0661 Monotonic Networks,
Joseph Sill
0668 Stacked Density Estimation,
Padhraic Smyth and David Wolpert
0675 Bidirectional Retrieval from Associative Memory,
Friedrich T. Sommer and Gunther Palm
0682 Mapping a Manifold of Perceptual Observations,
Joshua B. Tenenbaum
0689 Graph Matching with Hierarchical Discrete Relaxation,
Richard C. Wilson and Edwin R. Hancock
0696 Multiplicative Updating Rule for Blind Separation Derived from the Method of Scoring,
Howard H. Yang

Part V Implementation

0705 A 1,000-Neuron System with One Million 7-bit Physical Interconnections,
Yuzo Hirai
0712 Silicon Retina with Adaptive Filtering Propertie,
Shih-Chii Liu
0719 Analog VLSI Model of lntersegmental Coordination with Nearest-Neighbor Coupling,
Girish N. Patel, Jeremy H. Holleman and Stephen P. DeWeerth
0726 An Analog VLSI Neural Network for Phase-based Machine Vision,
Bertram E. Shi and Kwok Fai Hui

Part VI Speech, Handwriting and Signal Processing

0735 Analysis of Drifting Dynamics with Neural Network Hidden Markov Models,
Jens Kohlmorgen, Klaus-Robert Muller and Klaus Pawelzik
0742 Bayesian Robustification for Audio Visual Fusion,
Javier Movellan and Paul Mineiro
0749 Modeling Acoustic Correlations by Factor Analysis,
Lawrence Saul and Mazin Rahim
0756 Blind Separation of Radio Signals in Fading Channels,
Karl Torkkola
0763 Hybrid NN/HMM-Based Speech Recognition with a Discriminant Neural Feature Extraction,
Daniel Willett and Gerhard Rigoll

Part VII Visual Processing

0773 A Non-Parametric Multi-Scale Statistical Model for Natural Images,
Jeremy S. De Bonet and Paul A. Viola
0780 Recovering Perspective Pose with a Dual Step EM Algorithm,
Andrew D. J. Cross and Edwin R. Hancock
0787 Bayesian Model of Surface Perception,
Wfiliam T. Freeman and Paul A. Viola
0794 Features as Sufficient Statistics,
Davi Geiger, Archisman Rudra and Laurance T. Maloney
0801 Detection of First and Second Order Motion,
Alexander Grunewald and Heiko Neumann
0808 A Simple and Fast Neural Network Approach to Stereovision,
Rolf D. Henkel
0815 Inferring Sparse, Overcomplete Image Codes Using an Efficient Coding Framework,
Michael S. Lewicki and Bruno A. Olshausen
0822 Visual Navigation in a Robot Using Zig-Zag Behavior,
M. Anthony Lewis
0829 2D Observers for Human 3D Object Recognition,
Zili Liu and Daniel Kersten
0836 Self-similarity Properties of Natural Images,
Antonio Turiel, Germfin Mato, N6stor Parga and Jean-Pierre Nadal
0843 Multiresolution Tangent Distance forAffine-invariant Classification,
Nuno Vasconcelos and Andrew Lippman
0850 Phase Transitions and the Perceptual Organization of Video Sequences,
Yair Weiss

Part VIII Applications

0859 Using Expectation to Guide Processing: A Study of Three Real-World Applications,
Shumeet Baluja
0866 Structure Driven Image Database Retrieval,
Jeremy S. De Bonet and Paul A. Viola
0873 A General Purpose Image Processing Chip: Orientation Detection,
Ralph Etienne-Cummings and Donghui Cai
0880 An Analog VLSI Model of the Fly Elementary Motion Detector,
Reid R. Hamson and Christof Koch
0887 MELONET h Neural Nets for Inventing Baroque-Style Chorale Variations,
Dominik Hornel
0894 Extended ICA Removes Artifacts from Electroencephalographic Recordings,
Tzyy-Ping Jung, Colin Humphties, Te-Won Lee, Scott Makeig, Martin J. McKeown, Vicente Iragui and Terrence J. Sejnowski
0901 A Generic Approach for Identification of Event Related Brain Potentials via a Competitive Neural Network Structure,
Daniel H. Lange, Hava T. Siegelmann, Hillel Pratt and Gideon F. Inbar
0915 A Neural Network Based Head Tracking System,
Daniel D. Lee and H. Sebastian Seung
0915 Wavelet Models for Video Time-Series,
Sheng Ma and Chuanyi Ji
0922 Reinforcement Learning for Call Admission Control and Routing in Integrated Service Networks,
Peter Marbach, Oliver Mihatsch, Miriam Schulte and John N. Tsitsiklis
0929 Learning to Schedule Straight-Line Code,
Eliot Moss, Paul Utgoff, John Cavazos, Doina Precup, Darko Stefanovid, Carla Brodley and David Scheeff
0936 Enhancing Q-Learning for Optimal Asset Allocation,
Ralph Neuneier
0943 Intrusion Detection with Neural Networks,
Jake Ryan, Meng-Jang Lin and Risto Mikkulainen
0950 Incorporating Contextual Information in White Blood Cell Identification,
Xubo Song, Yaser Abu-Mostafa, Joseph Sill and Harvey Kasdan
0957 Bach in a Box--Real-Time Harmony,
Randall R. Spangler, Rodney M. Goodman and Jim Hawkins
0964 Experiences with Bayesian Learning in a Real World Application,
Peter Sykacek, Georg Dorffner, Peter Rappelsberger and Josef Zeitlhofer
0971 A Solution for Missing Data in Recurrent Neural Networks with anApplication to Blood Glucose Prediction,
Volker Tresp and Thomas Briegel
0978 Use of a Multi-Layer Perceptron to Predict Malignancy in Ovarian Tumors,
Herman Verrelst, Yves Moreau, Joos Vandewalle and Dirk Ttmmennan
0985 Modelling Seasonality and Trends in Daily Rainfall Data,
Peter M. Williams
0992 The Observer-Observation Dilemma in Neuro-Forecasting,
Hans Georg Zimmermann and Ralph Netmeier

Part IX Control, Navigation and Planning

1001 Generalized Prioritized Sweeping,
David Andre, Nit Friedman and Ronald Parr
1008 Nonparametric Model-Based Reinforcement Learning,
Christopher G. Atkeson
1015 An Improved Policy Iteration Algorithm for Partially Observable MDPS,
Eric A. Hansen
1022 Automated Aircraft Recovery via Reinforcement Learning: Initial Experiments,
Jeffrey F. Monaco, David G. Ward and Andrew G. Barto
1029 Reinforcement Learning for Continuous Stochastic Control Problems,
Remi Munos and Paul Bourgine
1036 Adaptive Choice of Grid and Time in Reinforcement Learning,
Stephan Pareigis
1043 Reinforcement Learning with Hierarchies of Machines,
Ronald Parr and Stuart Russell
1050 Multi-time Models for Temporally Abstract Planning,
Doina Precup and Richard S. Sutton
1057 How to Dynamically Merge Markov Decision Processes,
Satinder Singh and David Cohn
1064 The Asymptotic Convergence-Rate of Q-learning,
Csaba Szepesvttri
1071 Hybrid Reinforcement Learning and Its Application to Biped Robot Control,
Satoshi Yamada, Akira Watanabe and Michio Nakashima
1079 Index of Authors
1083 Keyword Index

NIPS'1998 Volume 11 : Table of Contents
Michael Kearns, Sara Solla, David Cohn (eds), MIT Press (1999)
i Title Pages
v Table of Contents
xv Preface
xvii NIPS Committees
xix Reviewers

Part I Cognitive Science

0003 Evidence for a Forward Dynamics Model in Human Adaptive Motor Control,
Nikhil Bhushan and Reza Shadmehr
0010 Perceiving without Learning: From Spirals to Inside/Outside Relations,
Ke Chen and DeLiang L. Wang
0017 A Model for Associative Multiplication,
G. Bjorn Christianson and Suzanna Becker
0024 Facial Memory Is Kernel Density Estimation (Almost),
Matthew N. Dailey, Garrison W. Cottrell and Thomas A. Busey
0031 Multiple Paired Forward-Inverse Models for Human Motor Learning and Control,
Masahiko Haruno, Daniel M. Wolpert and Mitsuo Kawato
0038 Utilizing lime: Asynchronous Binding,
Bradley C. Love
0045 Mechanisms of Generalization in Perceptual Learning,
Zili Liu and Daphna Weinshall
0052 A Principle for Unsupervised Hierarchical Decomposition of Visual Scenes,
Michael C. Mozer

Part II Neuroscience

0059 Bayesian Modeling of Human Concept Learning,
Joshua B. Tenenbaum
0069 Temporally Asymmetric Hebbian Learning, Spike liming and Neural Response Variability,
L. F. Abbott and Sen Song
0076 Contrast Adaptation in Simple Cells by Changing the Transmitter Release Probability,
Peter Adorjan and Klaus Obermayer
0083 Where Does the Population Vector of Motor Cortical Cells Point during Reaching Movements?,
Pierre Baraduc, Emmanuel Guigon and Yves Burnod
0090 Recurrent Cortical Amplification Produces Complex Cell Responses,
Frances S. Chance, Sacha B. Nelson and L. F. Abbott
0097 Neuronal Regulation Implements Efficient Synaptic Pruning,
Gal Chechik, Isaac Meilijson and Eytan Ruppin
0104 Divisive Normalization, Line Attractor Networks and Ideal Observers,
Sophie Deneve, Alexandre Pouget and Peter E. Latham
0111 Synergy and Redundancy among Brain Cells of Behaving Monkeys,
Itay Gat and Naftali Tishby
0118 Analyzing and Visualizing Single-Trial Event-Related Potentials,
Tzyy-Ping Jung, Scott Makeig, Marissa Westerfield, Jeanne Townsend, Eric Courchesne and Terrence J. Sejnowski
0125 Spike-Based Compared to Rate-Based Hebbian Learning,
Richard Kempter, Wuifram Gerstner and J. Leo van Hemmen
0132 Signal Detection in Noisy Weakly-Active Dendrites,
Amit Manwani and Christof Koch
0139 The Role of Lateral Cortical Competition in Ocular Dominance Development,
Christian Piepenbrock and Klaus Obermayer
0146 Multi-Electrode Spike Sorting by Clustering Transfer Functions,
Dmitry Rinberg, Hanan Davidowitz and Naftali Tishby
0153 Modeling Surround Suppression in V1 Neurons with a Statistically Derived Normalization Model,
Eero P. Simoncelli and Odelia Schwartz
0160 Information Maximization in Single Neurons,
Martin Stemmler and Christof Koch
0167 The Effect of Correlations on the Fisher Information of Population Codes,
Hyoungsoo Yoon and Haim Sompolinsky

Part III Theory

0174 Distributional Population Codes and Multiple Motion Models,
Richard S. Zemel and Peter Dayan
0183 Tractable Variational Structures for Approximating Graphical Models,
David Barber and Wim Wiegerinck
0190 Almost Linear VC Dimension Bounds for Piecewise Polynomial Networks,
Peter L. Bartlett, Vitaly Maiorov and Ron Meir
0197 Dynamics of Supervised Learning with Restricted Training Sets,
A. C. C. Coolen and David Saad
0204 Dynamically Adapting Kernels in Support Vector Machines,
Nello Cristianini, Cohn Campbell and John Shawe-Taylor
0211 Phase Diagram and Storage Capacity of Sequence-Storing Neural Networks,
A. During, A. C. C. Coolen and D. Sherrington
0218 Finite-Dimensional Approximation of Gaussian Processes,
Giancarlo Ferrari-Trecate, Christopher K. I. Williams and Manfred Opper
0225 Linear Hinge Loss and Average Margin,
Claudio Gentile and Manfred K. Warmuth
0232 Unsupervised and Supervised Clustering: The Mutual Information between Parameters and Observations,
Didier Herschkowitz and Jean-Pierre Nadal
0239 Convergence of the Wake-Sleep Algorithm,
Shiro Ikeda, Shun-ichi Amari and Hiroyuki Nakahara
0246 The Belief in TAP,
Yoshiyuki Kabashima and David Saad
0253 Optimizing Classifers for Imbalanced Training Sets,
Grigoris Karakoulas and John Shawe-Taylor
0260 Inference in Multilayer Networks via Large Deviation Bounds,
Michael Kearns and Lawrence Saul
0267 Stationarity and Stability of Autoregressive Neural Network Processes,
Friedrich Leisch, Adrian Trapletti and Kurt Hornik
0274 Computational Differences between Asymmetrical and Symmetrical Networks,
Zhaoping Li and Peter Dayan
0281 A Precise Characterization of the Class of Languages Recognized by Neural Nets under Gaussian and Other Common Noise Distributions
Wolfgang Maass and Eduardo D. Sontag
0288 Direct Optimization of Margins Improves Generalization in Combined Classifiers,
Llew Mason, Peter L. Bartlett and Jonathan Baxter
0295 On the Optimality of Incremental Neural Network Algorithms,
Ron Meir and Vitaly Maiorov
0302 General Bounds on Bayes Errors for Regression with Gaussian Processes,
Manfred Upper and Francesco Vivarelli
0309 Mean Field Methods for Classification with Gaussian Processes,
Manfred Upper and Ole Winther
0316 On-Line Learning with Restricted Training Sets: Exact Solution as Benchmark for General Theories,
H. C. Rae, Peter Sollich and A. C. C. Coolen
0323 Tight Bounds for the VC-Dimension of Piecewise Polynomial Networks,
Akito Sakurai
0330 Shrinking the Tube: A New Support Vector Regression Algorithm,
Bernhard Scholkopf, Peter L. Bartlett, Alex J. Smola and Robert Williamson
0337 Discontinuous Recall Transitions Induced by Competition Between Short- and Long-Range Interactions in Recurrent Networks,
N. S. Skantzos, C. F. Beckmann and A. C. C. Coolen
0344 Learning Curves for Gaussian Processes,
Peter Sollich

Part IV Algorithms and Architecture

0351 A Theory of Mean Field Approximation,
Toshiyuki Tanaka
0361 Learning a Hierarchical Belief Network of Independent Factor Analyzers,
Hagai Attias
0368 Semi-Supervised Support Vector Machines,
Kristin Bennett and Ayhan Demiriz
0375 Lazy Learning Meets the Recursive Least Squares Algorithm,
Mauro Birattari, Gianluca Bontempi and Hugues Bersini
0382 Bayesian PCA,
Christopher M. Bishop
0389 Learning Multi-Class Dynamics,
Andrew Blake, Ben North and Michael Isard
0396 Approximate Learning of Dynamic Models,
Xavier Boyen and Daphne Koller
0403 Fisher Scoring and a Mixture of Modes Approach for Approximate Inference and Learning in Nonlinear State Space Models,
Thomas Briegel and Volker Tresp
0410 Global Optimisation of Neural Network Models via Sequential Sampling,
Joao F. G. de Freitas, Mahesan Niranjan, Arnaud Doucet and Andrew H. Gee
0417 Efficient Bayesian Parameter Estimation in Large Discrete Domains,
Nir Friedman and Yoram Singer
0424 A Randomized Algorithm for Pairwise Clustering,
Yoram Gdalyahu, Daphna Weinshall and Michael Werman
0431 Learning Nonlinear Dynamical Systems Using an EM Algorithm,
Zoubin Ghahramani and Sam T. Roweis
0438 Classification on Pairwise Proximity Data,
Thore Graepel, Ralf Herbrich, Peter Bollmann-Sdorra and Klaus Obermayer
0445 Outcomes of the Equivalence of Adaptive Ridge with Least Absolute Shrinkage,
Yves Grandvalet and Stephane Canu
0452 Visualizing Group Structure,
Marcus Held, Jan Puzicha and Joachim M. Buhmann
0459 Source Separation as a By-Product of Regularization,
Sepp Hochreiter and Jurgen Schmidhuber
0466 Learning from Dyadic Data,
Thomas Hofmann, Jan Puzicha and Michael I. Jordan
0473 Sparse Code Shrinkage: Denoising by Nonlinear Maximum Likelihood Estimation,
Aapo Hyvarinen, Patrik Hoyer and Erkki Oja
0480 Restructuring Sparse High Dimensional Data for Effective Retrieval,
Charles Lee Isbell, Jr. and Paul Viola
0487 Exploiting Generative Models in Discriminative Classifiers,
Tommi S. Jaakkola and David Haussler
0494 Maximum Conditional Likelihood via Bound Maximization and the CEM Algorithm,
Tony Jebara and Alex Pentland
0501 A Polygonal Line Algorithm for Constructing Principal Curves,
Balazs Kegl, Adam Krzyzak, Tamas Linder and Kenneth Zeger
0508 Unsupervised Classification with Non-Gaussian Mixture Models Using ICA,
Te-Won Lee, Michael S. Lewicki and Terrence J. Sejnowski
0515 Learning a Continuous Hidden Variable Model for Binary Data,
Daniel D. Lee and Haim Sompolinsky
0522 Neural Networks for Density Estimation,
Malik Magdon-Ismail and Amir Atiya
0529 Exploratory Data Analysis Using Radial Basis Function Latent Variable Models,
Alan D. Marrs and Andrew R. Webb
0536 Kernel PCA and De-Noising in Feature Spaces,
Sebastian Mika, Bernhard Scholkopf, Alex J. Smola, Klaus-Robert Muller, Matthias Scholz and Gunnar Ratsch
0543 Very Fast EM-Based Mixture Model Clustering Using Multiresolution Kd-Trees,
Andrew W. Moore
0550 Replicator Equations, Maximal Cliques, and Graph Isomorphism,
Marcello Pelillo
0557 Using Analytic QP and Sparseness to Speed Training of Support Vector Machines,
John C. Platt
0564 Regularizing AdaBoost, Gunnar Ratsch,
Takashi Onoda and Klaus-Robert Muller
0571 Boxlets: A Fast Convolution Algorithm for Signal Processing and Neural Networks,
Patrice Y. Simard, Leon Bottou, Patrick Haffner and Yann Le Cun
0578 Batch and On-Line Parameter Estimation of Gaussian Mixtures Based on the Joint Entropy,
Yoram Singer and Manfred K. Warmuth
0585 Semiparametric Support Vector and Linear Programming Machines,
Alex J. Smola, Thilo T. Frieß and Bernhard Scholkopf
0592 Probabilistic Visualisation of High-Dimensional Binary Data,
Michael E. Tipping
0599 SMEM Algorithm for Mixture Models,
Naonori Ueda, Ryohei Nakano, Zoubin Ghabramani and Geoffrey E. Hinton
0606 Learning Mixture Hierarchies,
Nuno Vasconcelos and Andrew Lippman
0613 Discovering Hidden Features with Gaussian Processes Regression,
Francesco Vivarelli and Christopher K. I. Williams
0620 The Bias-Variance Tradeoff and the Randomized GACV,
Grace Wahba, Xiwu Lin, Fangyu Gao, Dong Xiang, Ronald Klein and Barbara Klein
0627 Basis Selection for Wavelet Regression,
Kevin R. Wheeler and Atam P. Dhawan
0634 DTs: Dynamic Trees,
Christopher K. I. Williams and Nicholas J. Adams
0641 Convergence Rates of Algorithms for Visual Search: Detecting Visual Contours,
A. L. Yuille and James M. Coughlan

Part V Implementation

0648 Blind Separation of Filtered Sources Using State-Space Approach,
Liqing Zhang and Andrzej Cichocki
0657 Analog VLSI Cellular Implementation of the Boundary Contour System,
Gert Cauwenberghs and James Waskiewicz
0664 Active Noise Canceling Using Analog Neuro-Chip with On-Chip Learning Capability,
Jung-Wook Cho and Soo-Young Lee
0671 A Micropower CMOS Adaptive Amplitude and Shift Invariant Vector Quantiser,
Richard J. Coggins, Raymond J. W. Wang and Marwan A. Jabri
0678 Optimizing Correlation Algorithms for Hardware-Based Transient Classification,
R. Timothy Edwards, Gert Cauwenberghs and Fernando J. Pineda
0685 VLSI Implementation of Motion Centroid Localization for Autonomous Navigation,
Ralph Etienne-Cummings, Vilctor Gruev and Mohammed Abdel Ghani
0692 A Neuromorphic Monaural Sound Localizer,
John G. Harris, Chiang-Jung Pu and Jose C. Principe
0699 An Integrated Vision Sensor for the Computation of Optical Flow Singular Points,
Charles M. Higgins and Christof Koch
0706 Computation of Smooth Optical Flow in a Feedback Connected Analog Network,
Alan Stocker and Rodney Douglas

Part VI Speech, Handwriting and Signal Processing

0713 A High Performance k-NN Classifier Using a Binary Correlation Matrix Memory,
Ping Zhou, Jim Austin and John Kennedy
0723 An Entropic Estimator for Structure Discovery,
Matthew Brand
0730 Coding Time-Varying Signals Using Sparse, Shift-Invariant Representations,
Michael S. Lewicki and Terrence J. Sejnowski
0737 Controlling the Complexity of HMM Systems by Regularization,
Christoph Neukirchen and Gerhard Rigoll
0744 Maximum-Likelihood Continuity Mapping (MALCOM): An Alternative to HMMs,
David A. Nix and John E. Hogden

Part VII Visual Processing

0751 Markov Processes on Curves for Automatic Speech Recognition,
Lawrence Saul and Mazin Rahim
0761 A Phase Space Approach to Minimax Entropy Learning and the Minutemax Approximations,
James M. Coughlan and A. L. Yuille
0768 Example-Based Image Synthesis of Articulated Figures,
Trevor Darrell
0775 Learning to Estimate Scenes from Images,
William T. Freeman and Egon C. Pasztor
0782 Learning to Find Pictures of People,
Sergey loffe and David Forsyth
0789 Attentional Modulation of Human Pattern Discrimination Psychophysics Reproduced by a Quantitative Model,
Laurent Itti, Jochen Braun, Dale K. Lee and Christof Koch
0796 A V1 Model of Pop Out and Asymmetty in Visual Search,
Zhaoping Li
0803 Support Vector Machines Applied to Face Recognition,
P. Jonathon Phillips
0810 Learning Lie Groups for Invariant Visual Perception,
Rajesh P. N. Rao and Daniel L. Ruderman
0817 General-Purpose Localization of Textured Image Regions,
Ruth Rosenholtz
0824 Probabilistic Image Sensor Fusion,
Ravi K. Sharma, Todd K. Leen and Misha Pavel
0831 Orientation, Scale, and Discontinuity as Emergent Properties of Illusory Contour Shape,
Karvel K. Thornber and Lance R. Williams

Part VIII Applications

0838 Classification in Non-Metric Spaces,
Daphna Weinshall, David W. Jacobs and Yoram Gdalyahu
0847 Making Templates Rotationally Invariant. An Application to Rotated Digit Recognition,
Shumeet Baluja
0854 Probabilistic Modeling for Face Orientation Discrimination: Learning from Labeled and Unlabeled Data,
Shumeet Baluja
0861 Adding Constrained Discontinuities to Gaussian Process Models of Wind Fields,
Dan Cornford, Ian T. Nabney and Christopher K. I. Williams
0868 Vertex Identification in High Energy Physics Experiments,
Gideon Dror, Halina Abramowicz and David Horn
0875 Familiarity Discrimination of Radar Pulses,
Eric Granger, Stephen Grossberg, Mark A. Rubin and William W. Streilein
0882 Fast Neural Network Emulation of Dynamical Systems for Computer Animation,
Radek Grzeszczuk, Demetri Terzopoulos and Geoffrey E. Hinton
0889 Call-Based Fraud Detection in Mobile Communication Networks Using a Hierarchical Regime-Switching Model,
Jaakko Hollmen and Volker Tresp
0896 Graph Matching for Shape Retrieval,
Benoit Huet, Andrew D. J. Cross and Edwin R. Hancock
0903 Scheduling Straight-Line Code Using Reinforcement Learning and Rollouts,
Amy McGovern and Eliot Moss
0910 Bayesian Modeling of Facial Similarity,
Baback Moghaddam, Tony Jebara and Alex Pentland
0917 Reinforcement Learning for Trading,
John Moody and Matthew Saffell
0924 Graphical Models for Recognizing Human Interactions,
Nuria M. Oliver, Barbara Rosario and Alex Pentland
0931 Independent Component Analysis of Intracellular Calcium Spike Data,
Klaus Prank, Julia Borger, Alexander von zur Muhlen, Georg Brabant and Christof Schofl
0938 Applications of Multi-Resolution Neural Networks to Mammography,
Clay D. Spence and Paul Sajda
0945 Robot Docking Using Mixtures of Gaussians,
Matthew M. Williamson, Roderick Murray-Smith and Volker Hansen

Part IX Control, Navigation and Planning

0952 Using Collective Intelligence to Route Internet Traffic,
David H. Wolpert, Kagan Turner and Jeremy Frank
0961 Robust, Efficient, Globally-Optimized Reinforcement Learning with the Parti-Game Algorithm,
Mohammad A. Al-Ansari and Ronald J. Williams
0968 Gradient Descent for General Reinforcement Learning,
Leemon Baird and Andrew W. Moore
0975 Non-Linear PI Control Inspired by Biological Control Systems,
Lyndon J. Brown, Gregory E. Gonye and James S. Schwaber
0982 Optimizing Admission Control while Ensuring Quality of Service in Multimedia Networks via Reinforcement Learning,
Timothy X. Brown, Hui Tong and Satinder Singh
0989 Viewing Classifier Systems as Model Free Learning in POMDPs,
Akira Hayashi and Nobuo Suematsu
0996 Finite-Sample Convergence Rates for Q-Learning and Indirect Algorithms,
Michael Kearns and Satinder Singh
1003 Exploring Unknown Environments with Real-Time Search or Reinforcement Learning,
Sven Koenig
1010 The Effect of Eligibility Traces on Finding Optimal Memoryless Policies in Partially Observable Markov Decision Processes,
John Loch
1017 Learning Instance-Independent Value Functions to Enhance Local Search, Robert Moll, Andrew G. Barto,
Theodore J. Perkins and Richard S. Sutton
1024 Barycentric Interpolators for Continuous Space and Time Reinforcement Learning,
Remi Munos and Andrew W. Moore
1031 Risk Sensitive Reinforcement Learning,
Ralph Neuneier and Oliver Mihatsch
1038 Coordinate Transformation Learning of Hand Position Feedback Controller by Using Change of Position Error Norm,
Eimei Oyama and Susumu Tachi
1045 Learning Macro-Actions in Reinforcement Learning,
Jette Randlov
1052 Reinforcement Learning Based on On-Line EM Algorithm,
Masa-aki Sato and Shin Ishii
1059 A Reinforcement Learning Algorithm in Partially Observable Environments Using Short-Term Memory,
Nobuo Suematsu and Akira Hayashi
1066 Improved Switching among Temporally Abstract Actions,
Richard S. Sutton, Satinder Singh, Doina Precup and Balaraman Ravindran
1073 Experimental Results on Learning Stochastic Memoryless Policies for Partially Observable Markov Decision Processes,
John K. Williams and Satinder Singh
1081 Index of Authors
1085 Keyword Index

NIPS'1999 Volume 12 : Table of Contents
Sara Solla, Todd Leen, Klaus-Robert Muller (eds), MIT Press (2000)
i Title Pages
v Table of Contents
xiii Preface
xv NIPS Committees
xvii Reviewers

Part I Cognitive Science

0003 Recognizing Evoked Potentials in a Virtual Environment,
Jessica D. Bayliss and Dana H. Ballard
0010 A Neurodynamical Approach to Visual Attention,
Gustavo Deco and Josef Zihl
0017 Effects of Spatial and Temporal Contiguity on the Acquisition of Spatial Information,
Thea B. Ghiselli-Crippa and Paul W. Munro
0024 Acquisition in Autoshaping,
Sham Kakade and Peter Dayan
0031 Robust Recognition of Noisy and Superimposed Patterns via Selective Attention,
Soo-Young Lee and Michael C. Mozer
0038 Perceptual Organization Based on Temporal Dynamics,
Xiuwen Liu and DeLiang L. Wang
0045 Information Factorization in Connectionist Models of Perception,
Javier R. Movellan and James L. McClelland
0052 Graded Grammaticality in Prediction Fractal Machines,
Shan Parfitt, Peter Tino and Georg Dorffner
0059 Rules and Similarity in Concept Learning,
Joshua B. Tenenbaum
0066 Evolving Learnable Languages, Bradley Tonkes,
Alan Blair and Janet Wiles
0073 Learning Statistically Neutral Tasks without Expert Guidance,
Ton Weijters, Antal van den Bosch and Eric Postma

Part II Neuroscience

0080 A Generative Model for Attractor Dynamics,
Richard S. Zemel and Michael C. Mozer
0089 Recurrent Cortical Competition: Strengthen or Weaken?,
Peter Adorjan, Lars Schwabe, Christian Piepenbrock and Klaus Obermayer
0096 Effective Learning Requires Neuronal Remodeling of Hebbian Synapses,
Gal Chechik, Isaac Meilijson and Eytan Ruppin
0103 Wiring Optimization in the Brain,
Dmitri B. Chklovskii and Charles F. Stevens
0108 Optimal Sizes of Dendritic and Axonal Arbors,
Dmitri B. Chklovskii
0115 Neural Representation of Multi-Dimensional Stimuli,
Christian W. Eurich, Stefan D. Wilke and Helmut Schwegler
0122 Spiking Boltzmann Machines,
Geoffrey E. Hinton and Andrew D. Brown
0129 Distributed Synchrony of Spiking Neurons in a Hebbian Cell Assembly,
David Horn, Nir Levy, Isaac Meilijson and Eytan Ruppin
0136 Can VI Mechanisms Account for Figure-Ground and Medial Axis Effects?,
Zhaoping Li
0143 Channel Noise in Excitable Neural Membranes,
Amit Manwani, Peter N. Steinmetz and Christof Koch
0150 LTD Facilitates Learning in a Noisy Environment,
Paul W. Munro and Gerardina Hernandez
0157 Memory Capacity of Linear vs. Nonlinear Models of Dendritic Integration,
Panayiota Poirazi and Bartlett W. Mel
0164 Predictive Sequence Learning in Recurrent Neocortical Circuits,
Rajesh P. N. Rao and Terrence J. Sejnowski
0171 A Recurrent Model of the Interaction Between Prefrontal and Inferotemporal Cortex in Delay Tasks,
Alfonso Renart, Nestor Parga and Edmund T. Rolls
0178 Information Capacity and Robustness of Stochastic Neuron Models,
Elad Schneidman, Idan Segev and Naftali Tishby
0185 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 and Michael P. Weisend
0192 Population Decoding Based on an Unfaithful Model,
Si Wu, Hiroyuki Nakahara, Noboru Murata and Shun-ichi Amari

Part III Theory

0199 Spike-based Learning Rules and Stabilization of Persistent Neural Activity,
Xiaohui Xie and H. Sebastian Seung
0209 A Variational Baysian Framework for Graphical Models,
Hagai Attias
0216 Model Selection in Clustering by Uniform Convergence Bounds,
Joachim M. Buhmann and Marcus Held
0223 Uniqueness of the SVM Solution,
Christopher J. C. Burges and David J. Crisp
0230 Model Selection for Support Vector Machines,
Olivier Chapelle and Vladimir N. Vapnik
0237 Dynamics of Supervised Learning with Restricted Training Sets and Noisy Teachers,
A. C. C. Coolen and C. W. H. Mace
0244 A Geometric Interpretation of v-SVM Classifiers,
David J. Crisp and Christopher J. C. Burges
0251 Efficient Approaches to Gaussian Process Classification,
Lehel Csato, Ernest Fokoue, Manfred Opper, Bernhard Schottky and Ole Winther
0258 Potential Boosters?,
Nigel Duffy and David Helmbold
0265 Bayesian Averaging is Well-Temperated,
Lars Kai Hansen
0272 Regular and Irregular Gallager-zype Error-Correcting Codes,
Yoshiyuki Kabashima, Tatsuto Murayama, David Saad and Renato Vicente
0279 Mixture Density Estimation,
Jonathan Q. Li and Andrew R. Barron
0286 Statistical Dynamics of Batch Learning,
Song Li and K. Y. Michael Wong
0293 Neural Computation with Winner-Take-All as the Only Nonlinear Operation,
Wolfgang Maass
0300 Boosting with Multi-Way Branching in Decision Trees,
Yishay Mansour and David McAllester
0307 Inference for the Generalization Error
Claude Nadeau and Yoshua Bengio
0314 Resonance in a Stochastic Neuron Model with Delayed Interaction,
Toru Ohira, Yuzuru Sato and Jack D. Cowan
0321 Understanding Stepwise Generalization of Support Vector Machines: a Toy Model,
Sebastian Risau-Gusman and Mirta B. Gordon
0328 Lower Bounds on the Complexity of Approximating Continuous Functions by Sigmoidal Neural Networks,
Michael Schmitt
0335 Noisy Neural Networks and Generalizations,
Hava T. Siegelmann, Alexander Roitershtein and Asa Ben-Hur
0342 The Entropy Regularization Information Criterion,
Alexander J. Smola, John Shawe-Taylor, Bernhard Scholkopf and Robert C. Williamson
0349 Probabilistic Methods for Support Vector Machines,
Peter Sollich
0356 Algebraic Analysis for Non-regular Learning Machines,
Sumio Watanabe
0363 Semiparametric Approach to Multichannel Blind Deconvolution of Nonminimum Phase Systems,
L. Q. Zhang, Shun-ichi Amari and A. Cichocki

Part IV Algorithms and Architecture

0370 Some Theoretical Results Concerning the Convergence of Compositions of Regularized Linear Functions,
Tong Zhang
0379 Robust Full Bayesian Methods for Neural Networks,
Christophe Andrieu, Joao F. G. de Freitas and Arnaud Doucet
0386 Independent Factor Analysis with Temporally Structured Sources,
Hagai Attias
0393 Gaussian Fields for Approximate Inference in Layered Sigmoid Belief Networks,
David Barber and Peter Sollich
0400 Modeling High-Dimensional Discrete Data with Multi-Layer Neural Networks,
Yoshua Bengio and Samy Bengio
0407 Robust Neural Network Regression for Offline and Online Learning,
Thomas Briegel and Volker Tresp
0414 Reconstruction of Sequential Data with Probabilistic Models and Continuity Constraints,
Miguel A. Carreira-Perpinan
0421 Transductive Inference for Estimating Values of Functions,
Olivier Chapelle, Vladimir N. Vapnik and Jason Weston
0428 The Nonnegative Boltzmann Machine,
Oliver B. Downs, David J.C. MacKay and Daniel D. Lee
0435 Differentiating Functions of the Jacobian with Respect to the Weights,
Gary William Flake and Barak A. Pearlmutter
0442 Local Probability Propagation for Factor Analysis,
Brendan J. Frey
0449 Variational Inference for Bayesian Mixtures of Factor Analysers,
Zoubin Ghahramani and Matthew J. Beal
0456 Bayesian Transduction,
Thore Graepel, Ralf Herbrich and Klaus Obermayer
0463 Learning to Parse Images,
Geoffrey E. Hinton, Zoubin Ghahramani and Yee Whye Teh
0470 Maximum Entropy Discrimination,
Tommi Jaakkola, Marina Meila and Tony Jebara
0477 Topographic Transformation as a Discrete Latent Variable,
Nebojsa Jojic and Brendan J. Frey
0484 An Improved Decomposition Algorithm for Regression Support Vector Machines,
Pavel Laskov
0491 Algorithms for Independent Components Analysis and Higher Order Statistics,
Daniel D. Lee, Uri Rokni and Haim Sompolinsky
0498 The Relaxed Online Maximum Margin Algorithm,
Yi Li and Philip M. Long
0505 Bayesian Network Induction via Local Neighborhoods,
Dimitris Margaritis and Sebastian Thrun
0512 Boosting Algorithms as Gradient Descent,
Liew Mason, Jonathan Baxter, Peter Bartlett and Marcus Frean
0519 A Multi-class Linear Learning Algorithm Related to Winnow,
Chris Mesterharm
0526 Invariant Feature Extraction and Classification in Kernel Spaces,
Sebastian Mika, Gunnar Rätsch, Jason Weston, Bernhard Scholkopf, Alexander J. Smola and Klaus-Robert Muller
0533 Approximate Inference A lgorithms for Two-Layer Bayesian Networks,
Andrew Y. Ng and Michael I. Jordan
0540 Optimal Kernel Shapes for Local Linear Regression,
Dirk Ormoneit and Trevor Hastie
0547 Large Margin DAGs for Multiclass Classification,
John C. Platt, Nello Cristianini and John Shawe-Taylor
0554 The Infinite Gaussian Mixture Model,
Carl Edward Rasmussen
0561 v-Arc: Ensemble Learning in the Presence of Outliers,
Gunnar Rätsch, Bernhard Scholkopf, Alexander J. Smola, Klaus-Robert Muller, Takashi Onoda and Sebastian Mika
0568 Nonlinear Discriminant Analysis Using Kernel Functions,
Volker Roth and Volker Steinhage
0575 An Analysis of Turbo Decoding with Gaussian Densities,
Paat Rusmevichientong and Benjamin Van Roy
0582 Support Vector Method for Novelty Detection,
Bernhard Scholkopf, Robert C. Williamson, Alexander J. Smola, John Shawe-Taylor and John C. Platt
0589 Better Generative Models for Sequential Data Problems: Bidirectional Recurrent Mixture Density Networks,
Mike Schuster
0596 Greedy Importance Sampling,
Dale Schuurmans
0603 Bayesian Model Selection for Support Vector Machines, Gaussian Processes and Other Kernel Classifiers,
Matthias Seeger
0610 Leveraged Vector Machines,
Yoram Singer
0617 Agglomerative Information Bottleneck,
Noam Slonim and Naftali Tishby
0624 Training Data Selection for Optimal Generalization in Trigonometric Polynomial Networks,
Masashi Sugiyama and Hidemitsu Ogawa
0631 Predictive App roaches for Choosing Hyperparameters in Gaussian Processes,
S. Sundararajan and S. Sathiya Keerthi
0638 On Input Selection with Reversible Jump Markov Chain Monte Carlo Sampling,
Peter Sykacek
0645 Building Predictive Models from Fractal Representations of Symbolic Sequences,
Peter Tino and Georg Dorffner
0652 The Relevance Vector Machine,
Michael E. Tipping
0659 Support Vector Method for Multivariate Density Estimation,
Vladimir N. Vapnik and Sayan Mukherjee
0666 Dual Estimation and the Unscented Transformation,
Eric A. Wan, Rudolph van der Merwe and Alex T. Nelson
0673 Correctness of Belief Propagation in Gaussian Graphical Models of Arbitrary Topology,
Yair Weiss and William T. Freeman
0680 A MCMC Approach to Hierarchical Mixture Modelling,
Christopher K. I. Williams
0687 Data Visualization and Feature Selection: New Algorithms for Nongaussian Data,
Howard Hua Yang and John Moody

Part V Implementation

0694 Manifold Stochastic Dynamics for Bayesian Learning,
Mark Ziochin and Yoram Baram
0703 The Parallel Problems Server: an Interactive Tool for Large Scale Machine Learning,
Charles Lee Isbell, Jr. and Parry Husbands
0710 An Oculo-Motor System with Multi-Chip Neuromorphic Analog VLSI Control,
Oliver Landolt and Steve Gyger
0717 A Winner-Take-All Circuit with Controllable Soft Max Property,
Shih-Chii Liu.
0724 A Neuromorphic VLSI System for Modeling the Neural Control of Axial Locomotion,
Girish N. Patel, Edgar A. Brown and Stephen P. DeWeerth
0731 Bifurcation Analysis of a Silicon Neuron,
Girish N. Patel, Gennady S. Cymbalyuk, Ronald L. Calabrese and Stephen P. DeWeerth

Part VI Speech, Handwriting and Signal Processing

0738 An Analog VLSI Model of Periodicity Extraction,
Andre van Schaik
0747 An Oscillatory Correlation Frame work for Computational Auditory Scene Analysis,
Guy J. Brown and DeLiang L. Wang
0754 Bayesian Modelling of fMRI lime Series,
Pedro A. d. F. R. Hojen-Sørensen, Lars Kai Hansen and Carl Edward Rasmussen
0761 Neural System Model of Human Sound Localization,
Craig T. Jin and Simon Carlile
0768 Spectral Cues in Human Sound Localization,
Craig T. Jin, Anna Corderoy, Simon Carlile and Andre van Schaik
0775 Broadband Direction-Of-Arrival Estimation Based on Second Order Statistics,
Justinian Rosca, Joseph O Ruanaidh, Alexander Jourjine and Scott Rickard
0782 Constrained Hidden Markov Models,
Sam Roweis
0789 Online Independent Component Analysis with Local Learning Rate Adaptation,
Nicol N. Schraudolph and Xavier Giannakopoulos
0796 Speech Modelling Using Subspace and EM Techniques,
Gavin Smith, Joao F. G. de Freitas, Tony Robinson and Mahesan Niranjan

Part VII Visual Processing

0803 Search for Information Bearing Components in Speech,
Howard Hua Yang and Hynek Hermansky
0813 Audio Vision: Using Audio-Visual Synchrony to Locate Sounds,
John Hershey and Javier R. Movellan
0820 Bayesian Reconstruction of 3D Human Motion from Single-Camera Video,
Nicholas R. Howe, Michael E. Leventon and William T. Freeman
0827 Emergence of Topography and Complex Cell Properties from Natural Images using Extensions of ICA,
Aapo Hyvarinen and Patrik Hoyer
0834 An Information-Theoretic Framework for Understanding Saccadic Eye Movements,
Tai Sing Lee and Stella X. Yu
0841 Learning Sparse Codes with a Mixture-of-Gaussians Prior,
Bruno A. Olshausen and K. Jarrod Millman
0848 Hierarchical Image Probability (H1P) Models,
Clay D. Spence and Lucas Parra
0855 Scale Mixtures of Gaussians and the Statistics of Natural Images,
Martin J. Wainwright and Eero P. Simoncelli
0862 A SNoW-Based Face Detector,
Ming-Hsuan Yang, Dan Roth and Narendra Ahuja

Part VIII Applications

0869 Managing Uncertainty in Cue Combination,
Zhiyong Yang and Richard S. Zemel
0879 Robust Learning of Chaotic Attractors,
Rembrandt Bakker, Jaap C. Schouten, Marc-Olivier Coppens, Floris Takens, C. Lee Giles and Cor M. van den Bleek
0886 Image Representations for Facial Expression Coding,
Marian Stewart Bartlett, Gianluca Donato, Javier R. Movellan, Joseph C. Hager, Paul Ekman and Terrence J. Sejnowski
0893 Low Power Wireless Communication via Reinforcement Learning,
Timothy X. Brown
0900 Learning Informative Statistics: A Nonparametnic Approach,
John W. Fisher III, Alexander T. Ihier and Paul A. Viola
0907 Kirchoff Law Markov Fields for Analog Circuit Design,
Richard M. Golden
0914 Learning the Similarity of Documents: An Information-Geometric Approach to Document Retrieval and Categorization,
Thomas Hofmann
0921 Constructing Heterogeneous Committees Using Input Feature Grouping: Application to Economic Forecasting,
Yuansong Liao and John Moody
0928 From Coexpression to Coregulation: An Approach to Inferring Transcriptional Regulation among Gene Classes from Large-Scale Expression Data,
Eric Mjolsness, Tobias Mann, Rebecca Castano and Barbara Wold
0935 Churn Reduction in the Wireless Industry,
Michael C. Mozer, Richard Wolniewicz, David B. Grimes, Eric Johnson and Howard Kaushansky
0942 Unmixing Hyperspectral Data,
Lucas Parra, Clay D. Spence, Paul Sajda, Andreas Ziehe and Klaus-Robert Muller
0949 Application of Blind Separation of Sources to Optical Recording of Brain Activity,
Holger Schoner, Martin Stetter, Ingo SchieBi, John E.W. Mayhew, Jennifer Lund, Niall McLoughlin and Klaus Obermayer
0956 Reinforcement Learning for Spoken Dialogue Systems,
Satinder Singh, Michael Kearns, Diane Litman and Marilyn Walker
0963 Image Recognition in Context: Application to Microscopic Urinalysis,
Xubo B. Song, Joseph Sill, Yaser Abu-Mostafa and Harvey Kasdan
0970 Generalized Model Selection for Unsupervised Learning in High Dimensions,
Shivakumar Vaithyanathan and Byron Dom

Part IX Control, Navigation and Planning

0977 Learning from User Feedback in Image Retrieval Systems,
Nuno Vasconcelos and Andrew Lippman
0987 An Environment Model for Nonstationary Reinforcement Learning,
Samuel P. M. Choi, Dit-Yan Yeung and Nevin L. Zhang
0994 State Abstraction in MAXQ Hierarchical Reinforcement Learning,
Thomas G. Dietterich
1001 Approximate Planning in Large POMDPs via Reusable Trajectories,
Michael Kearns, Yishay Mansour and Andrew Y. Ng
1008 Actor-Critic Algorithms,
Vijay R. Konda and John N. Tsitsiklis
1015 Bayesian Map Learning in Dynamic Environments,
Kevin P. Murphy
1022 Policy Search via Density Estimation,
Andrew Y. Ng, Ronald Parr and Daphne Koller
1029 Neural Network Based Model Predictive Control,
Stephen Piche, Jim Keeler, Greg Martin, Gene Boe, Doug Johnson and Mark Gerules
1036 Reinforcement Learning Using Approximate Belief States,
Andrés Rodriguez, Ronald Parr and Daphne Koller
1043 Coastal Navigation with Mobile Robots,
Nicholas Roy and Sebastian Thrun
1050 Learning Factored Representations for Partially Observable Markov Decision Processes,
Brian Sallans
1057 Policy Gradient Methods for Reinforcement Learning with Function Approximation,
Richard S. Sutton, David McAllester, Satinder Singh and Yishay Mansour
1064 Monte Carlo POMDPs,
Sebastian Thrun
1071 Index of Authors
1075 Keyword Index

NIPS'2000 Volume 13 : Table of Contents
Todd Leen, Tom Dietterich, Volker Tresp (eds), MIT Press (2001)
? What Can a Single Neuron Compute?
Blaise Ag{\"u}era y Arcas, Adrienne L. Fairhall, William Bialek
? Who Does What? A Novel Algorithm to Determine Function Localization
Ranit Aharonov-Barki, Isaac Meilijson, Eytan Ruppin
? Programmable Reinforcement Learning Agents
David Andre, Stuart J. Russell
? From Mixtures of Mixtures to Adaptive Transform Coding
Cynthia Archer, Todd K. Leen
? Dendritic Compartmentalization Could Underlie Competition and Attentional Biasing of Simultaneous Visual Stimuli
Kevin A. Archie, Bartlett W. Mel
? Place Cells and Spatial Navigation Based on 2D Visual Feature Extraction, Path Integration, and Reinforcement Learning
Angelo Arleo, Fabrizio Smeraldi, St\'ephane Hug, Wulfram Gerstner
? Speech Denoising and Dereverberation Using Probabilistic Models
Hagai Attias, John C. Platt, Alex Acero, Li Deng
? Combining ICA and Top-Down Attention for Robust Speech Recognition
Un-Min Bae, Soo-Young Lee
? Modelling Spatial Recall, Mental Imagery and Neglect
Suzanna Becker, Neil Burgess
? Shape Context: A New Descriptor for Shape Matching and Object Recognition
Serge Belongie, Jitendra Malik, Jan Puzicha
? Efficient Learning of Linear Perceptrons
Shai Ben-David, Hans Ulrich Simon
? A Support Vector Method for Clustering
Asa Ben-Hur, David Horn, Hava T. Siegelmann, Vladimir Vapnik
? A Neural Probabilistic Language Model
Yoshua Bengio, R\'ejean Ducharme, Pascal Vincent
? A Variational Mean-Field Theory for Sigmoidal Belief Networks
Chiranjib Bhattacharyya, S. Sathiya Keerthi
? Stability and Noise in Biochemical Switches
William Bialek
? Emergence of Movement Sensitive Neurons' Properties by Learning a Sparse Code for Natural Moving Images
Rafal Bogacz, Malcolm W. Brown, Christophe Giraud-Carrier
? New Approaches Towards Robust and Adaptive Speech Recognition {\rm (invited paper)}
Herv\'e Bourlard, Samy Bengio, Katrin Weber
? Algorithmic Stability and Generalization Performance
Olivier Bousquet, Andr\'e Elisseeff
? Exact Solutions to Time-Dependent MDPs
Justin A. Boyan, Michael L. Littman
? Direct Classification with Indirect Data
Timothy X Brown
? Model Complexity, Goodness of Fit and Diminishing Returns
Igor V. Cadez, Padhraic Smyth
? A Linear Programming Approach to Novelty Detection
Colin Campbell, Kristin P. Bennett
? Decomposition of Reinforcement Learning for Admission Control of Self-Similar Call Arrival Processes
Jakob Carlstr{\"o}m
? Overfitting in Neural Nets: Backpropagation, Conjugate Gradient, and Early Stopping
Rich Caruana, Steve Lawrence, Lee Giles
? Incremental and Decremental Support Vector Machine Learning
Gert Cauwenberghs, Tomaso Poggio
? Vicinal Risk Minimization
Olivier Chapelle, Jason Weston, L\'eon Bottou, Vladimir Vapnik
? Temporally Dependent Plasticity: An Information Theoretic Account
Gal Chechik, Naftali Tishby
? Gaussianization
Scott Saobing Chen, Ramesh A. Gopinath
? The Missing Link - A Probabilistic Model of Document Content and Hypertext Connectivity
David Cohn, Thomas Hofmann
? The Manhattan World Assumption: Regularities in Scene Statistics which Enable Bayesian Inference
James M. Coughlan, Allen L. Yuille
? Improved Output Coding for Classification Using Continuous Relaxation
Koby Crammer, Yoram Singer
? Sparse Representation for Gaussian Process Models
Lehel Csat\'o, Manfred Opper
? Competition and Arbors in Ocular Dominance
Peter Dayan
? Explaining Away in Weight Space
Peter Dayan, Sham Kakade
? Feature Correspondence: A Markov Chain Monte Carlo Approach
Frank Dellaert, Steven M. Seitz, Sebastian Thrun, Charles Thorpe
? A New Model of Spatial Representation in Multimodal Brain Areas
Sophie Deneve, Jean-Rene Duhamel, Alexandre Pouget
? An Adaptive Metric Machine for Pattern Classification
Carlotta Domeniconi, Jing Peng, Dimitrios Gunopulos
? High-temperature Expansions for Learning Models of Nonnegative Data
Oliver B. Downs
? Incorporating Second-Order Functional Knowledge for Better Option Pricing
Charles Dugas, Yoshua Bengio, Fran\c{c}ois B\'elisle, Claude Nadeau, Ren\'e Garcia
? A Productive, Systematic Framework for the Representation of Visual Structure
Shimon Edelman, Nathan Intrator
? Discovering Hidden Variables: A Structure-Based Approach
Gal Elidan, Noam Lotner, Nir Friedman, Daphne Koller
? Multiple Timescales of Adaptation in a Neural Code
Adrienne L. Fairhall, Geoffrey D. Lewen, William Bialek, Robert R. de Ruyter van Steveninck
? Learning Joint Statistical Models for Audio-Visual Fusion and Segregation
John W. Fisher III, Trevor Darrell, William T. Freeman, Paul Viola
? Accumulator Networks: Suitors of Local Probability Propagation
Brendan J. Frey, Anitha Kannan
? Sequentially Fitting ``Inclusive'' Trees for Inference in Noisy-OR Networks
Brendan J. Frey, Relu Patrascu, Tommi S. Jaakkola, Jodi Moran
? Factored Semi-Tied Covariance Matrices
Mark J.F. Gales
? A New Approximate Maximal Margin Classification Algorithm
Claudio Gentile
? Propagation Algorithms for Variational Bayesian Learning
Zoubin Ghahramani, Matthew J. Beal
? Reinforcement Learning with Function Approximation Converges to a Region
Geoffrey J. Gordon
? The Kernel Gibbs Sampler
Thore Graepel, Ralf Herbrich
? From Margin to Sparsity
Thore Graepel, Ralf Herbrich, Robert C. Williamson
? `N-Body' Problems in Statistical Learning
Alexander G. Gray, Andrew W. Moore
? A Comparison of Image Processing Techniques for Visual Speech Recognition Applications
Michael S. Gray, Terrence J. Sejnowski, Javier R. Movellan
? The Interplay of Symbolic and Subsymbolic Processes in Anagram Problem Solving
David B. Grimes, Michael C. Mozer
? Permitted and Forbidden Sets in Symmetric Threshold-Linear Networks
Richard H.R. Hahnloser, H. Sebastian Seung
? Support Vector Novelty Detection Applied to Jet Engine Vibration Spectra
Paul Hayton, Bernhard Sch{\"o}lkopf, Lionel Tarassenko, Paul Anuzis
? Large Scale Bayes Point Machines
Ralf Herbrich, Thore Graepel
? A PAC-Bayesian Margin Bound for Linear Classifiers: Why SVMs work
Ralf Herbrich, Thore Graepel
? Hierarchical Memory-Based Reinforcement Learning
Natalia Hernandez-Gardiol, Sridhar Mahadevan
? Beyond Maximum Likelihood and Density Estimation: A Sample-Based Criterion for Unsupervised Learning of Complex Models
Sepp Hochreiter, Michael C. Mozer
? Ensemble Learning and Linear Response Theory for ICA
Pedro A.d.F.R. H{\o}jen-S{\o}rensen, Ole Winther, Lars Kai Hansen
? A Silicon Primitive for Competitive Learning
David Hsu, Miguel Figueroa, Chris Diorio
? On Reversing Jensen's Inequality
Tony Jebara, Alex Pentland
? Automated State Abstraction for Options using the U-Tree Algorithm
Anders Jonsson, Andrew G. Barto
? Dopamine Bonuses
Sham Kakade, Peter Dayan
? Hippocampally-Dependent Consolidation in a Hierarchical Model of Neocortex
Szabolcs K{\'a}li, Peter Dayan
? Second Order Approximations for Probability Models
Hilbert J. Kappen, Wim Wiegerinck
? Generalizable Singular Value Decomposition for Ill-posed Datasets
Ulrik Kjems, Lars Kai Hansen, Stephen C. Strother
? Some New Bounds on the Generalization Error of Combined Classifiers
Vladimir Koltchinskii, Dmitriy Panchenko, Fernando Lozano
? Sparsity of Data Representation of Optimal Kernel Machine and Leave-one-out Estimator
Adam Kowalczyk
? Keeping Flexible Active Contours on Track using Metropolis Updates
Trausti T. Kristjansson, Brendan J. Frey
? Smart Vision Chip Fabricated Using Three Dimensional Integration Technology
Hiroyuki Kurino, M. Nakagawa, Kang Wook Lee, Tomonori Nakamura, Yuusuke Yamada, Ki Tae Park, Mitsumasa Koyanagi
? Algorithms for Non-negative Matrix Factorization
Daniel D. Lee, H. Sebastian Seung
? Color Opponency Constitutes a Sparse Representation for the Chromatic Structure of Natural Scenes
Te-Won Lee, Thomas Wachtler, Terrence J. Sejnowski
? Foundations for a Circuit Complexity Theory of Sensory Processing
Robert A. Legenstein, Wolfgang Maass
? A Tighter Bound for Graphical Models
Martijn A. R. Leisink, Hilbert J. Kappen
? Position Variance, Recurrence and Perceptual Learning
Zhaoping Li, Peter Dayan
? Homeostasis in a Silicon Integrate and Fire Neuron
Shih-Chii Liu, Bradley A. Minch
? Text Classification using String Kernels
Huma Lodhi, John Shawe-Taylor, Nello Cristianini, Chris Watkins
? Constrained Independent Component Analysis
Wei Lu, Jagath C. Rajapakse
? Learning Curves for Gaussian Processes Regression: A Framework for Good Approximations
D\"orthe Malzahn, Manfred Opper
? Active Support Vector Machine Classification
Olvi L. Mangasarian, David R. Musicant
? Weak Learners and Improved Rates of Convergence in Boosting
Shie Mannor, Ron Meir
? Recognizing Hand-written Digits Using Hierarchical Products of Experts
Guy Mayraz, Geoffrey E. Hinton
? Learning Segmentation by Random Walks
Marina Meil\u{a}, Jianbo Shi
? The Unscented Particle Filter
Rudolph van der Merwe, Arnaud Doucet, Nando de Freitas, Eric Wan
? A Mathematical Programming Approach to the Kernel Fisher Algorithm
Sebastian Mika, Gunnar R{\"a}tsch, Klaus-Robert M{\"u}ller
? Automatic Choice of Dimensionality for PCA
Thomas P. Minka
? On Iterative Krylov-Dogleg Trust-Region Steps for Solving Neural Networks Nonlinear Least Squares Problems
Eiji Mizutani, James W. Demmel
? Sex with Support Vector Machines
Baback Moghaddam, Ming-Hsuan Yang
? Robust Reinforcement Learning
Jun Morimoto, Kenji Doya
? Partially Observable SDE Models for Image Sequence Recognition Tasks
Javier R. Movellan, Paul Mineiro, Ruth J. Williams
? The Use of MDL to Select among Computational Models of Cognition
In J. Myung, Mark A. Pitt, Shaobo Zhang, Vijay Balasubramanian
? Probabilistic Semantic Video Indexing
Milind R. Naphade, Igor Kozintsev, Thomas Huang
? Finding the Key to a Synapse
Thomas Natschl{\"a}ger, Wolfgang Maass
? Processing of Time Series by Neural Circuits with Biologically Realistic Synaptic Dynamics
Thomas Natschl{\"a}ger, Wolfgang Maass, Eduardo D. Sontag, Anthony Zador
? Active Inference in Concept Learning
Jonathan D. Nelson, Javier R. Movellan
? Learning Continuous Distributions: Simulations With Field Theoretic Priors
Ilya Nemenman, William Bialek
? Interactive Parts Model: An Application to Recognition of On-line Cursive Script
Predrag Neskovic, Philip C. Davis, Leon N. Cooper
? Learning Sparse Image Codes using a Wavelet Pyramid Architecture
Bruno A. Olshausen, Phil Sallee, Michael S. Lewicki
? Kernel-Based Reinforcement Learning in Average-Cost Problems: An Application to Optimal Portfolio Choice
Dirk Ormoneit, Peter Glynn
? Learning and Tracking Cyclic Human Motion
Dirk Ormoneit, Hedvig Sidenbladh, Michael J. Black, Trevor Hastie
? Higher-Order Statistical Properties Arising from the Non-Stationarity of Natural Signals
Lucas Parra, Clay Spence, Paul Sajda
? Learning Switching Linear Models of Human Motion
Vladimir Pavlovi\'c, James M. Rehg, John MacCormick
? Bayes Networks on Ice: Robotic Search for Antarctic Meteorites
Liam Pedersen, Dimi Apostolopoulos, Red Whittaker
? Redundancy and Dimensionality Reduction in Sparse-Distributed Representations of Natural Objects in Terms of Their Local Features
Penio S. Penev
? Fast Training of Support Vector Classifiers
Fernando P\'erez-Cruz, Pedro L. Alarc\'on-Diana, Angel Navia-V\'azquez, Antonio Art\'es-Rodr\'{\i}guez
? The Use of Classifiers in Sequential Inference
Vasin Punyakanok, Dan Roth
? Occam's Razor
Carl Edward Rasmussen, Zoubin Ghahramani
? One Microphone Source Separation
Sam T. Roweis
? Using Free Energies to Represent Q-values in a Multiagent Reinforcement Learning Task
Brian Sallans, Geoffrey E. Hinton
? Minimum Bayes Error Feature Selection for Continuous Speech Recognition
George Saon, Mukund Padmanabhan
? Periodic Component Analysis: An Eigenvalue Method for Representing Periodic Structure in Speech
Lawrence K. Saul, Jont B. Allen
? Spike-Timing-Dependent Learning for Oscillatory Networks
Silvia Scarpetta, Zhaoping Li, John Hertz
? Universality and Individuality in a Neural Code
Elad Schneidman, Naama Brenner, Naftali Tishby, Robert R. de Ruyter van Steveninck, William Bialek
? Machine Learning for Video-Based Rendering
Arno Sch{\"o}dl, Irfan Essa
? The Kernel Trick for Distances
Bernhard Sch{\"o}lkopf
? Natural Sound Statistics and Divisive Normalization in the Auditory System
Odelia Schwartz, Eero P. Simoncelli
? Balancing Multiple Sources of Reward in Reinforcement Learning
Christian R. Shelton
? An Information Maximization Approach to Overcomplete and Recurrent Representations
Oren Shriki, Haim Sompolinsky, Daniel D. Lee
? Development of Hybrid Systems: Interfacing a Silicon Neuron to a Leech Heart Interneuron
Mario F. Simoni, Gennady S. Cymbalyuk, Michael Q. Sorensen, Ronald L. Calabrese, Stephen P. DeWeerth
? FaceSync: A Linear Operator for Measuring Synchronization of Video Facial Images and Audio Tracks
Malcolm Slaney, Michele Covell
? The Early Word Catches the Weights
Mark A. Smith, Garrison W. Cottrell, Karen L. Anderson
? Sparse Greedy Gaussian Process Regression
Alex J. Smola, Peter Bartlett
? Regularization with Dot-Product Kernels
Alex J. Smola, Zolt\'an L. \'Ov\'ari, Robert C. Williamson
? APRICODD: Approximate Policy Construction Using Decision Diagrams
Robert St-Aubin, Jesse Hoey, Craig Boutilier
? Four-legged Walking Gait Control Using a Neuromorphic Chip Interfaced to a Support Vector Learning Algorithm
Susanne Still, Bernhard Sch{\"o}lkopf, Klaus Hepp, Rodney J. Douglas
? Kernel Expansions with Unlabeled Examples
Martin Szummer, Tommi S. Jaakkola
? Analysis of Bit Error Probability of Direct-Sequence CDMA Multiuser Demodulators
Toshiyuki Tanaka
? Noise Suppression Based on Neurophysiologically-motivated SNR Estimation for Robust Speech Recognition
J\"urgen Tchorz, Michael Kleinschmidt, Birger Kollmeier
? Rate-coded Restricted Boltzmann Machines for Face Recognition
Yee Whye Teh, Geoffrey E. Hinton
? Structure Learning in Human Causal Induction
Joshua B. Tenenbaum, Thomas L. Griffiths
? Sparse Kernel Principal Component Analysis
Michael E. Tipping
? Data Clustering by Markovian Relaxation and the Information Bottleneck Method
Naftali Tishby, Noam Slonim
? Adaptive Object Representation with Hierarchically-Distributed Memory Sites
Bosco S. Tjan
? Active Learning for Parameter Estimation in Bayesian Networks
Simon Tong, Daphne Koller
? Mixtures of Gaussian Processes
Volker Tresp
? Bayesian Video Shot Segmentation
Nuno Vasconcelos, Andrew Lippman
? Error-correcting Codes on a Bethe-like Lattice
Renato Vicente, David Saad, Yoshiyuki Kabashima
? Whence Sparseness?
Carl van Vreeswijk
? Tree-Based Modeling and Estimation of Gaussian Processes on Graphs with Cycles
Martin J. Wainwright, Erik B. Sudderth, Alan S. Willsky
? Algebraic Information Geometry for Learning Machines with Singularities
Sumio Watanabe
? Feature Selection for SVMs
Jason Weston, Sayan Mukherjee, Olivier Chapelle, Massimiliano Pontil, Tomaso Poggio, Vladimir Vapnik
? On a Connection between Kernel PCA and Metric Multidimensional Scaling
Christopher K. I. Williams
? Using the Nystr{\"o}m Method to Speed Up Kernel Machines
Christopher K. I. Williams, Matthias Seeger
? Computing with Finite and Infinite Networks
Ole Winther
? Stagewise Processing in Error-correcting Codes and Image Restoration
K. Y. Michael Wong, Hidetoshi Nishimori
? Learning Winner-take-all Competition Between Groups of Neurons in Lateral Inhibitory Networks
Xiaohui Xie, Richard H.R. Hahnloser, H. Sebastian Seung
? Generalized Belief Propagation
Jonathan S. Yedidia, William T. Freeman, Yair Weiss
? A Gradient-Based Boosting Algorithm for Regression Problems
Richard S. Zemel, Toniann Pitassi
? Divisive and Subtractive Mask Effects: Linking Psychophysics and Biophysics
Barbara Zenger, Christof Koch
? Regularized Winnow Methods
Tong Zhang
? Convergence of Large Margin Separable Linear Classification
Tong Zhang