Book
Neural Information Processing Systems (NIPS 1987)
Edited by:
D. Anderson
- Bit-Serial Neural Networks Alan Murray, Anthony Smith, Zoe Butler
- Connectivity Versus Entropy Yaser Abu-Mostafa
- The Hopfield Model with Multi-Level Neurons Michael Fleisher
- How Neural Nets Work Alan Lapedes, Robert Farber
- Spatial Organization of Neural Networks: A Probabilistic Modeling Approach Andreas Stafylopatis, Marios Dikaiakos, D. Kontoravdis
- A Neural-Network Solution to the Concentrator Assignment Problem Gene Tagliarini, Edward Page
- LEARNING BY STATE RECURRENCE DETECTION Bruce Rosen, James Goodwin, Jacques Vidal
- Stability Results for Neural Networks Anthony Michel, Jay Farrell, Wolfgang Porod
- Introduction to a System for Implementing Neural Net Connections on SIMD Architectures Sherryl Tomboulian
- Optimization with Artificial Neural Network Systems: A Mapping Principle and a Comparison to Gradient Based Methods Harrison Leong
- Optimal Neural Spike Classification James Bower, Amir Atiya
- REFLEXIVE ASSOCIATIVE MEMORIES Hendricus G. Loos
- The Performance of Convex Set Projection Based Neural Networks Robert Marks, Les Atlas, Seho Oh, James Ritcey
- Speech Recognition Experiments with Perceptrons David Burr
- On Properties of Networks of Neuron-Like Elements Pierre Baldi, Santosh Venkatesh
- Ensemble' Boltzmann Units have Collective Computational Properties like those of Hopfield and Tank Neurons Mark Derthick, Joe Tebelskis
- On Tropistic Processing and Its Applications Manuel Fernández
- Neuromorphic Networks Based on Sparse Optical Orthogonal Codes Mario Vecchi, Jawad Salehi
- A 'Neural' Network that Learns to Play Backgammon Gerald Tesauro, Terrence J. Sejnowski
- Learning Representations by Recirculation Geoffrey E. Hinton, James McClelland
- A Computer Simulation of Cerebral Neocortex: Computational Capabilities of Nonlinear Neural Networks Alexander Singer, John Donoghue
- PATTERN CLASS DEGENERACY IN AN UNRESTRICTED STORAGE DENSITY MEMORY Christopher Scofield, Douglas L. Reilly, Charles Elbaum, Leon Cooper
- Strategies for Teaching Layered Networks Classification Tasks Ben Wittner, John Denker
- Invariant Object Recognition Using a Distributed Associative Memory Harry Wechsler, George Zimmerman
- Cycles: A Simulation Tool for Studying Cyclic Neural Networks Michael Gately
- Learning on a General Network Amir Atiya
- Neural Net and Traditional Classifiers William Huang, Richard P. Lippmann
- Scaling Properties of Coarse-Coded Symbol Memories Ronald Rosenfeld, David Touretzky
- Synchronization in Neural Nets Jacques Vidal, John Haggerty
- A NEURAL NETWORK CLASSIFIER BASED ON CODING THEORY Tzi-Dar Chiueh, Rodney Goodman
- Microelectronic Implementations of Connectionist Neural Networks Stuart Mackie, Hans Graf, Daniel Schwartz, John Denker
- Analysis of Distributed Representation of Constituent Structure in Connectionist Systems Paul Smolensky
- Hierarchical Learning Control - An Approach with Neuron-Like Associative Memories Enis Ersü, Henning Tolle
- Presynaptic Neural Information Processing L. Carley
- An Optimization Network for Matrix Inversion Ju-Seog Jang, Soo-Young Lee, Sang-Yung Shin
- Basins of Attraction for Electronic Neural Networks Charles Marcus, R. Westervelt
- Programmable Synaptic Chip for Electronic Neural Networks Alexander Moopenn, H. Langenbacher, A. Thakoor, S. Khanna
- Learning a Color Algorithm from Examples Tomaso A. Poggio, Anya Hurlbert
- Generalization of Back propagation to Recurrent and Higher Order Neural Networks Fernando Pineda
- Neural Network Implementation Approaches for the Connection Machine Nathan Brown
- On the Power of Neural Networks for Solving Hard Problems Jehoshua Bruck, Joseph Goodman
- HOW THE CATFISH TRACKS ITS PREY: AN INTERACTIVE "PIPELINED" PROCESSING SYSTEM MAY DIRECT FORAGING VIA RETICULOSPINAL NEURONS Jagmeet S. Kanwal
- Phasor Neural Networks André Noest
- Computing Motion Using Resistive Networks Christof Koch, Jin Luo, Carver Mead, James Hutchinson
- Experimental Demonstrations of Optical Neural Computers Ken Hsu, David Brady, Demetri Psaltis
- MURPHY: A Robot that Learns by Doing Bartlett Mel
- SPONTANEOUS AND INFORMATION-TRIGGERED SEGMENTS OF SERIES OF HUMAN BRAIN ELECTRIC FIELD MAPS D. Lehmann, D. Brandeis, A. Horst, H. Ozaki, I. Pal
- Simulations Suggest Information Processing Roles for the Diverse Currents in Hippocampal Neurons Lyle Borg-Graham
- An Artificial Neural Network for Spatio-Temporal Bipolar Patterns: Application to Phoneme Classification Les Atlas, Toshiteru Homma, Robert Marks
- Teaching Artificial Neural Systems to Drive: Manual Training Techniques for Autonomous Systems J. F. Shepanski, S. A. Macy
- Correlational Strength and Computational Algebra of Synaptic Connections Between Neurons Eberhard Fetz
- Discovering Structure from Motion in Monkey, Man and Machine Ralph Siegel
- Static and Dynamic Error Propagation Networks with Application to Speech Coding A. Robinson, F. Fallside
- Schema for Motor Control Utilizing a Network Model of the Cerebellum James Houk
- Distributed Neural Information Processing in the Vestibulo-Ocular System Clifford Lau, Vicente Honrubia
- Time-Sequential Self-Organization of Hierarchical Neural Networks Ronald Silverman, Andrew Noetzel
- A Method for the Design of Stable Lateral Inhibition Networks that is Robust in the Presence of Circuit Parasitics John Wyatt, D. Standley
- Constrained Differential Optimization John Platt, Alan Barr
- Encoding Geometric Invariances in Higher-Order Neural Networks C. Giles, R. Griffin, T. Maxwell
- A Novel Net that Learns Sequential Decision Process Guo-Zheng Sun, Yee-Chun Lee, Hsing-Hen Chen
- Mathematical Analysis of Learning Behavior of Neuronal Models John Cheung, Massoud Omidvar
- New Hardware for Massive Neural Networks Darryl Coon, A. Perera
- An Adaptive and Heterodyne Filtering Procedure for the Imaging of Moving Objects F. Schuling, H. Mastebroek, W. Zaagman
- Phase Transitions in Neural Networks Joshua Chover
- Using Neural Networks to Improve Cochlear Implant Speech Perception Manoel Tenorio
- Self-Organization of Associative Database and Its Applications Hisashi Suzuki, Suguru Arimoto
- Temporal Patterns of Activity in Neural Networks Paolo Gaudiano
- Network Generality, Training Required, and Precision Required John Denker, Ben Wittner
- High Order Neural Networks for Efficient Associative Memory Design Gérard Dreyfus, Isabelle Guyon, Jean-Pierre Nadal, Léon Personnaz
- The Capacity of the Kanerva Associative Memory is Exponential Philip Chou
- The Sigmoid Nonlinearity in Prepyriform Cortex Frank Eeckman
- Probabilistic Characterization of Neural Model Computations Richard Golden
- Learning in Networks of Nondeterministic Adaptive Logic Elements Richard Windecker
- HIGH DENSITY ASSOCIATIVE MEMORIES Amir Dembo, Ofer Zeitouni
- A Mean Field Theory of Layer IV of Visual Cortex and Its Application to Artificial Neural Networks Christopher Scofield
- Neural Networks for Template Matching: Application to Real-Time Classification of the Action Potentials of Real Neurons James Bower, Yiu-Fai Wong, Jashojiban Banik
- Capacity for Patterns and Sequences in Kanerva's SDM as Compared to Other Associative Memory Models James Keeler
- The Connectivity Analysis of Simple Association Dan Hammerstrom
- Performance Measures for Associative Memories that Learn and Forget Anthony Kuh
- Centric Models of the Orientation Map in Primary Visual Cortex William Baxter, Bruce Dow
- A Computer Simulation of Olfactory Cortex with Functional Implications for Storage and Retrieval of Olfactory Information James Bower, Matthew Wilson
- Towards an Organizing Principle for a Layered Perceptual Network Ralph Linsker
- A Trellis-Structured Neural Network Thomas Petsche, Bradley Dickinson
- Supervised Learning of Probability Distributions by Neural Networks Eric Baum, Frank Wilczek
- Stochastic Learning Networks and their Electronic Implementation Joshua Alspector, Robert Allen, Victor Hu, Srinagesh Satyanarayana
- Connecting to the Past Bruce MacDonald
- PARTITIONING OF SENSORY DATA BY A CORTICAL NETWORK Richard Granger, Jose Ambros-Ingerson, Howard Henry, Gary Lynch
- A Dynamical Approach to Temporal Pattern Processing W. Stornetta, Tad Hogg, Bernardo Huberman
- Minkowski-r Back-Propagation: Learning in Connectionist Models with Non-Euclidian Error Signals Stephen Hanson, David Burr
- Analysis and Comparison of Different Learning Algorithms for Pattern Association Problems J. Bernasconi
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