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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