NIPS Online: Table of Contents Vol. 0-13

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

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

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

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

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

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

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