NIPS Proceedings^β

Advances in Neural Information Processing Systems 3 (NIPS 1990)

The papers below appear in Advances in Neural Information Processing Systems 3 edited by R.P. Lippmann and J.E. Moody and D.S. Touretzky.
They are proceedings from the conference, "Neural Information Processing Systems 1990."

• Further Studies of a Model for the Development and Regeneration of Eye-Brain Maps Jack D. Cowan, A. E. Friedman
• Development and Spatial Structure of Cortical Feature Maps: A Model Study Klaus Obermayer, Helge Ritter, Klaus Schulten
• Interaction Among Ocularity, Retinotopy and On-center/Off-center Pathways During Development Shigeru Tanaka
• Simple Spin Models for the Development of Ocular Dominance Columns and Iso-Orientation Patches J.D. Cowan, A. E. Friedman
• A Recurrent Neural Network Model of Velocity Storage in the Vestibulo-Ocular Reflex Thomas J. Anastasio
• Self-organization of Hebbian Synapses in Hippocampal Neurons Thomas H. Brown, Zachary F. Mainen, Anthony M. Zador, Brenda J. Claiborne
• Cholinergic Modulation May Enhance Cortical Associative Memory Function Michael E. Hasselmo, Brooke P. Anderson, James M. Bower
• Order Reduction for Dynamical Systems Describing the Behavior of Complex Neurons Thomas B. Kepler, L. F. Abbott, Eve Marder
• Stochastic Neurodynamics J.D. Cowan
• Dynamics of Learning in Recurrent Feature-Discovery Networks Todd K. Leen
• A Lagrangian Approach to Fixed Points Eric Mjolsness, Willard L. Miranker
• Associative Memory in a Network of `Biological' Neurons Wulfram Gerstner
• CAM Storage of Analog Patterns and Continuous Sequences with 3N2 Weights Bill Baird, Frank Eeckman
• Connection Topology and Dynamics in Lateral Inhibition Networks C.M Marcus, F. R. Waugh, R. M. Westervelt
• Shaping the State Space Landscape in Recurrent Networks Patrice Simard, Jean Pierre Raysz, Bernard Victorri
• Adjoint-Functions and Temporal Learning Algorithms in Neural Networks N. Toomarian, J. Barhen
• Phase-coupling in Two-Dimensional Networks of Interacting Oscillators Ernst Niebur, Daniel M. Kammen, Christof Koch, Daniel L. Ruderman, Heinz G. Schuster
• Oscillation Onset in Neural Delayed Feedback André Longtin
• Analog Computation at a Critical Point: A Novel Function for Neuronal Oscillations? Leonid Kruglyak, William Bialek
• Modeling Time Varying Systems Using Hidden Control Neural Architecture Esther Levin
• The Tempo 2 Algorithm: Adjusting Time-Delays By Supervised Learning Ulrich Bodenhausen, Alex Waibel
• A Theory for Neural Networks with Time Delays Bert de Vries, José Carlos Príncipe
• ART2/BP architecture for adaptive estimation of dynamic processes Einar Sørheim
• Statistical Mechanics of Temporal Association in Neural Networks Andreas V. M. Herz, Zhaoping Li, J. Leo van Hemmen
• Learning Time-varying Concepts Anthony Kuh, Thomas Petsche, Ronald L. Rivest
• The Recurrent Cascade-Correlation Architecture Scott E. Fahlman
• Continuous Speech Recognition by Linked Predictive Neural Networks Joe Tebelskis, Alex Waibel, Bojan Petek, Otto Schmidbauer
• A Recurrent Neural Network for Word Identification from Continuous Phoneme Strings Robert B. Allen, Candace A. Kamm
• Connectionist Approaches to the Use of Markov Models for Speech Recognition Hervé Bourlard, Nelson Morgan, Chuck Wooters
• Spoken Letter Recognition Mark Fanty, Ronald Cole
• Speech Recognition Using Demi-Syllable Neural Prediction Model Ken-ichi Iso, Takao Watanabe
• RecNorm: Simultaneous Normalisation and Classification applied to Speech Recognition John S. Bridle, Stephen J. Cox
• Exploratory Feature Extraction in Speech Signals Nathan Intrator
• Phonetic Classification and Recognition Using the Multi-Layer Perceptron Hong C. Leung, James R. Glass, Michael S. Phillips, Victor W. Zue
• From Speech Recognition to Spoken Language Understanding: The Development of the MIT SUMMIT and VOYAGER Systems Victor Zue, James Glass, David Goodine, Lynette Hirschman, Hong Leung, Michael Phillips, Joseph Polifroni, Stephanie Seneff
• Speech Recognition Using Connectionist Approaches Khalid Choukri
• Natural Dolphin Echo Recognition Using an Integrator Gateway Network Herbert L. Roitblat, Patrick W. B. Moore, Paul E. Nachtigall, Ralph H. Penner
• Signal Processing by Multiplexing and Demultiplexing in Neurons David C. Tam
• Applications of Neural Networks in Video Signal Processing John C. Pearson, Clay D. Spence, Ronald Sverdlove
• Discovering Viewpoint-Invariant Relationships That Characterize Objects Richard S. Zemel, Geoffrey E. Hinton
• A Neural Network Approach for Three-Dimensional Object Recognition Volker Tresp
• A Second-Order Translation, Rotation and Scale Invariant Neural Network Shelly D. D. Goggin, Kristina M. Johnson, Karl E. Gustafson
• Learning to See Rotation and Dilation with a Hebb Rule Martin I. Sereno, Margaret E. Sereno
• Stereopsis by a Neural Network Which Learns the Constraints Alireza Khotanzad, Ying-Wung Lee
• Grouping Contours by Iterated Pairing Network Amnon Shashua, Shimon Ullman
• Neural Dynamics of Motion Segmentation and Grouping Ennio Mingolla
• A Multiscale Adaptive Network Model of Motion Computation in Primates H. Taichi Wang, Bimal Mathur, Christof Koch
• Qualitative structure from motion Daphna Weinshall
• Optimal Sampling of Natural Images: A Design Principle for the Visual System William Bialek, Daniel L. Ruderman, A. Zee
• A VLSI Neural Network for Color Constancy Andrew W. Moore, John Allman, Geoffrey Fox, Rodney Goodman
• Optimal Filtering in the Salamander Retina Fred Rieke, W. Geoffrey Owen, William Bialek
• A four neuron circuit accounts for change sensitive inhibition in salamander retina Jeffrey L. Teeters, Frank H. Eeckman, Frank S. Werblin
• Feedback Synapse to Cone and Light Adaptation Josef Skrzypek
• An Analog VLSI Chip for Finding Edges from Zero-crossings Wyeth Bair, Christof Koch
• A Delay-Line Based Motion Detection Chip Tim Horiuchi, John Lazzaro, Andrew Moore, Christof Koch
• Neural Networks Structured for Control Application to Aircraft Landing Charles Schley, Yves Chauvin, Van Henkle, Richard Golden
• Real-time autonomous robot navigation using VLSI neural networks Lionel Tarassenko, Michael Brownlow, Gillian Marshall, Jan Tombs, Alan Murray
• Rapidly Adapting Artificial Neural Networks for Autonomous Navigation Dean Pomerleau
• Learning Trajectory and Force Control of an Artificial Muscle Arm by Parallel-hierarchical Neural Network Model Masazumi Katayama, Mitsuo Kawato
• Proximity Effect Corrections in Electron Beam Lithography Using a Neural Network Robert C. Frye, Kevin D. Cummings, Edward A. Rietman
• Planning with an Adaptive World Model Sebastian Thrun, Knut Möller, Alexander Linden
• A Connectionist Learning Control Architecture for Navigation Jonathan R. Bachrach
• Navigating through Temporal Difference Peter Dayan
• Integrated Modeling and Control Based on Reinforcement Learning and Dynamic Programming Richard S. Sutton
• A Reinforcement Learning Variant for Control Scheduling Aloke Guha
• Adaptive Range Coding Bruce E. Rosen, James M. Goodwin, Jacques J. Vidal
• Neural Network Implementation of Admission Control Rodolfo A. Milito, Isabelle Guyon, Sara A. Solla
• Reinforcement Learning in Markovian and Non-Markovian Environments Juergen Schmidhuber
• A Model of Distributed Sensorimotor Control in the Cockroach Escape Turn R.D. Beer, G. J. Kacmarcik, R.E. Ritzmann, H.J. Chiel
• Flight Control in the Dragonfly: A Neurobiological Simulation William E. Faller, Marvin W. Luttges
• A Novel Approach to Prediction of the 3-Dimensional Structures of Protein Backbones by Neural Networks Henrik Fredholm, Henrik Bohr, Jakob Bohr, Søren Brunak, Rodney M. J. Cotterill, Benny Lautrup, Steffen B. Petersen
• Training Knowledge-Based Neural Networks to Recognize Genes in DNA Sequences Michiel O. Noordewier, Geoffrey G. Towell, Jude W. Shavlik
• Neural Network Application to Diagnostics and Control of Vehicle Control Systems Kenneth A. Marko
• Lg Depth Estimation and Ripple Fire Characterization Using Artificial Neural Networks John L. Perry, Douglas R. Baumgardt
• A B-P ANN Commodity Trader Joseph E. Collard
• Integrated Segmentation and Recognition of Hand-Printed Numerals James D. Keeler, David E. Rumelhart, Wee Kheng Leow
• EMPATH: Face, Emotion, and Gender Recognition Using Holons Garrison W. Cottrell, Janet Metcalfe
• SEXNET: A Neural Network Identifies Sex From Human Faces B.A. Golomb, D.T. Lawrence, T.J. Sejnowski
• A Neural Expert System with Automated Extraction of Fuzzy If-Then Rules and Its Application to Medical Diagnosis Yoichi Hayashi
• Analog Neural Networks as Decoders Ruth Erlanson, Yaser Abu-Mostafa
• Distributed Recursive Structure Processing Geraldine Legendre, Yoshiro Miyata, Paul Smolensky
• Translating Locative Prepositions Paul W. Munro, Mary Tabasko
• A Short-Term Memory Architecture for the Learning of Morphophonemic Rules Michael Gasser, Chan-Do Lee
• Exploiting Syllable Structure in a Connectionist Phonology Model David S. Touretzky, Deirdre W. Wheeler
• Language Induction by Phase Transition in Dynamical Recognizers Jordan B. Pollack
• Discovering Discrete Distributed Representations with Iterative Competitive Learning Michael C. Mozer
• Direct memory access using two cues: Finding the intersection of sets in a connectionist model Janet Wiles, Michael S. Humphreys, John D. Bain, Simon Dennis
• An Attractor Neural Network Model of Recall and Recognition Eytan Ruppin, Yehezkel Yeshurun
• ALCOVE: A Connectionist Model of Human Category Learning John K. Kruschke
• Spherical Units as Dynamic Consequential Regions: Implications for Attention, Competition and Categorization Stephen Jose Hanson, Mark A. Gluck
• Connectionist Implementation of a Theory of Generalization Roger N. Shepard, Sheila Kannappan
• Adaptive Spline Networks Jerome H. Friedman
• Multi-Layer Perceptrons with B-Spline Receptive Field Functions Stephen H. Lane, Marshall Flax, David Handelman, Jack Gelfand
• Bumptrees for Efficient Function, Constraint and Classification Learning Stephen M. Omohundro
• Basis-Function Trees as a Generalization of Local Variable Selection Methods for Function Approximation Terence D. Sanger
• Generalization Properties of Radial Basis Functions Sherif M. Botros, Christopher G. Atkeson
• Leaning by Combining Memorization and Gradient Descent John C. Platt
• Sequential Adaptation of Radial Basis Function Neural Networks and its Application to Time-series Prediction V. Kadirkamanathan, M. Niranjan, F. Fallside
• Oriented Non-Radial Basis Functions for Image Coding and Analysis Avijit Saha, Jim Christian, Dun-Sung Tang, Wu Chuan-Lin
• Computing with Arrays of Bell-Shaped and Sigmoid Functions Pierre Baldi
• Discrete Affine Wavelet Transforms For Anaylsis And Synthesis Of Feedfoward Neural Networks Y. C. Pati, P. S. Krishnaprasad
• Extensions of a Theory of Networks for Approximation and Learning: Outliers and Negative Examples Federico Girosi, Tomaso Poggio, Bruno Caprile
• How Receptive Field Parameters Affect Neural Learning Bartlett W. Mel, Stephen M. Omohundro
• A competitive modular connectionist architecture Robert A. Jacobs, Michael I. Jordan
• Evaluation of Adaptive Mixtures of Competing Experts Steven J. Nowlan, Geoffrey E. Hinton
• A Framework for the Cooperation of Learning Algorithms Léon Bottou, Patrick Gallinari
• Connectionist Music Composition Based on Melodic and Stylistic Constraints Michael C. Mozer, Todd Soukup
• Using Genetic Algorithms to Improve Pattern Classification Performance Eric I. Chang, Richard P. Lippmann
• Evolution and Learning in Neural Networks: The Number and Distribution of Learning Trials Affect the Rate of Evolution Ron Keesing, David G. Stork
• Designing Linear Threshold Based Neural Network Pattern Classifiers Terrence L. Fine
• On Stochastic Complexity and Admissible Models for Neural Network Classifiers Padhraic Smyth
• A Method for the Efficient Design of Boltzmann Machines for Classiffication Problems Ajay Gupta, Wolfgang Maass
• Note on Learning Rate Schedules for Stochastic Optimization Christian Darken, John E. Moody
• Convergence of a Neural Network Classifier John S. Baras, Anthony LaVigna
• Learning Theory and Experiments with Competitive Networks Griff L. Bilbro, David E. van den Bout
• Transforming Neural-Net Output Levels to Probability Distributions John S. Denker, Yann LeCun
• Back Propagation is Sensitive to Initial Conditions John F. Kolen, Jordan B. Pollack
• Closed-Form Inversion of Backpropagation Networks: Theory and Optimization Issues Michael L. Rossen
• Generalization by Weight-Elimination with Application to Forecasting Andreas S. Weigend, David E. Rumelhart, Bernardo A. Huberman
• The Devil and the Network: What Sparsity Implies to Robustness and Memory Sanjay Biswas, Santosh S. Venkatesh
• Generalization Dynamics in LMS Trained Linear Networks Yves Chauvin
• Dynamics of Generalization in Linear Perceptrons Anders Krogh, John A. Hertz
• Constructing Hidden Units using Examples and Queries Eric B. Baum, Kevin J. Lang
• Can neural networks do better than the Vapnik-Chervonenkis bounds? David Cohn, Gerald Tesauro
• Second Order Properties of Error Surfaces: Learning Time and Generalization Yann LeCun, Ido Kanter, Sara A. Solla
• Chaitin-Kolmogorov Complexity and Generalization in Neural Networks Barak A. Pearlmutter, Ronald Rosenfeld
• Asymptotic slowing down of the nearest-neighbor classifier Robert R. Snapp, Demetri Psaltis, Santosh S. Venkatesh
• Remarks on Interpolation and Recognition Using Neural Nets Eduardo D. Sontag
• e-Entropy and the Complexity of Feedforward Neural Networks Robert C. Williamson
• On the Circuit Complexity of Neural Networks V. P. Roychowdhury, K. Y. Siu, A. Orlitsky, T. Kailath
• Comparison of three classification techniques: CART, C4.5 and Multi-Layer Perceptrons A. C. Tsoi, R. A. Pearson
• A Comparative Study of the Practical Characteristics of Neural Network and Conventional Pattern Classifiers Kenney Ng, Richard P. Lippmann
• Time Trials on Second-Order and Variable-Learning-Rate Algorithms Richard Rohwer
• Kohonen Networks and Clustering: Comparative Performance in Color Clustering Wesley Snyder, Daniel Nissman, David Van den Bout, Griff Bilbro
• VLSI Implementations of Learning and Memory Systems: A Review Mark A. Holler
• Compact EEPROM-based Weight Functions A. Kramer, C. K. Sin, R. Chu, P. K. Ko
• An Analog VLSI Splining Network Daniel B. Schwartz, Vijay K. Samalam
• Relaxation Networks for Large Supervised Learning Problems Joshua Alspector, Robert B. Allen, Anthony Jayakumar, Torsten Zeppenfeld, Ronny Meir
• Design and Implementation of a High Speed CMAC Neural Network Using Programmable CMOS Logic Cell Arrays W. Thomas Miller III, Brian A. Box, Erich C. Whitney, James M. Glynn
• Back Propagation Implementation on the Adaptive Solutions CNAPS Neurocomputer Chip Hal McCartor
• Reconfigurable Neural Net Chip with 32K Connections H. P. Graf, R. Janow, D. Henderson, R. Lee
• Simulation of the Neocognitron on a CCD Parallel Processing Architecture Michael L. Chuang, Alice M. Chiang
• VLSI Implementation of TInMANN Matt Melton, Tan Phan, Doug Reeves, Dave Van den Bout