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ORCIDNIPS 1987: Denver, CO, USA
- Dana Z. Anderson:
Neural Information Processing Systems, Denver, Colorado, USA, 1987. American Institue of Physics 1988, ISBN 0-88318-569-5 - Yaser S. Abu-Mostafa:
Connectivity Versus Entropy. 1-8 - Joshua Alspector, Robert B. Allen, Victor Hu, Srinagesh Satyanarayana:
Stochastic Learning Networks and their Electronic Implementation. 9-21 - Amir F. Atiya:
Learning on a General Network. 22-30 - Les E. Atlas, Toshiteru Homma, Robert J. Marks II:
An Artificial Neural Network for Spatio-Temporal Bipolar Patterns: Application to Phoneme Classification. 31-40 - Pierre Baldi, Santosh S. Venkatesh:
On Properties of Networks of Neuron-Like Elements. 41-51 - Eric B. Baum, Frank Wilczek:
Supervised Learning of Probability Distributions by Neural Networks. 52-61 - William Baxter, Bruce Dow:
Centric Models of the Orientation Map in Primary Visual Cortex. 62-71 - J. Bernasconi:
Analysis and Comparison of Different Learning Algorithms for Pattern Association Problems. 72-81 - Lyle J. Borg-Graham:
Simulations Suggest Information Processing Roles for the Diverse Currents in Hippocampal Neurons. 82-94 - James M. Bower, Amir F. Atiya:
Optimal Neural Spike Classification. 95-102 - James M. Bower, Yiu-Fai Wong, Jashojiban Banik:
Neural Networks for Template Matching: Application to Real-Time Classification of the Action Potentials of Real Neurons. 103-113 - James M. Bower, Matthew A. Wilson:
A Computer Simulation of Olfactory Cortex with Functional Implications for Storage and Retrieval of Olfactory Information. 114-126 - Nathan H. Brown Jr.:
Neural Network Implementation Approaches for the Connection Machine. 127-136 - Jehoshua Bruck, Joseph W. Goodman:
On the Power of Neural Networks for Solving Hard Problems. 137-143 - David J. Burr:
Speech Recognition Experiments with Perceptrons. 144-153 - L. Richard Carley:
Presynaptic Neural Information Processing. 154-163 - John Y. Cheung, Massoud Omidvar:
Mathematical Analysis of Learning Behavior of Neuronal Models. 164-173 - Tzi-Dar Chiueh, Rodney M. Goodman:
A Neural Network Classifier Based on Coding Theory. 174-183 - Philip A. Chou:
The Capacity of the Kanerva Associative Memory is Exponential. 184-191 - Joshua Chover:
Phase Transitions in Neural Networks. 192-200 - Darryl D. Coon, A. G. Unil Perera:
New Hardware for Massive Neural Networks. 201-210 - Amir Dembo, Ofer Zeitouni:
High Density Associative Memories. 211-218 - John S. Denker, Ben S. Wittner:
Network Generality, Training Required, and Precision Required. 219-222 - Mark Derthick, Joe Tebelskis:
'Ensemble' Boltzmann Units have Collective Computational Properties like those of Hopfield and Tank Neurons. 223-232 - Gérard Dreyfus, Isabelle Guyon, Jean-Pierre Nadal, Léon Personnaz:
High Order Neural Networks for Efficient Associative Memory Design. 233-241 - Frank H. Eeckman:
The Sigmoid Nonlinearity in Prepyriform Cortex. 242-248 - Enis Ersü, Henning Tolle:
Hierarchical Learning Control - An Approach with Neuron-Like Associative Memories. 249-261 - Manuel F. Fernández:
On Tropistic Processing and Its Applications. 262-269 - Eberhard E. Fetz:
Correlational Strength and Computational Algebra of Synaptic Connections Between Neurons. 270-277 - Michael Fleisher:
The Hopfield Model with Multi-Level Neurons. 278-289 - Michael T. Gately:
Cycles: A Simulation Tool for Studying Cyclic Neural Networks. 290-296 - Paolo Gaudiano:
Temporal Patterns of Activity in Neural Networks. 297-300 - C. Lee Giles
, R. D. Griffin, T. Maxwell:
Encoding Geometric Invariances in Higher-Order Neural Networks. 301-309 - Richard M. Golden:
Probabilistic Characterization of Neural Model Computations. 310-316 - Richard Granger, Jose A. Ambros-Ingerson, Howard Henry, Gary Lynch:
Partitioning of Sensory Data by a Cortical Network. 317-337 - Dan W. Hammerstrom:
The Connectivity Analysis of Simple Association. 338-347 - Stephen Jose Hanson, David J. Burr:
Minkowski-r Back-Propagation: Learning in Connectionist Models with Non-Euclidian Error Signals. 348-357 - Geoffrey E. Hinton, James L. McClelland:
Learning Representations by Recirculation. 358-366 - James C. Houk:
Schema for Motor Control Utilizing a Network Model of the Cerebellum. 367-376 - Ken Hsu, David Brady, Demetri Psaltis:
Experimental Demonstrations of Optical Neural Computers. 377-386 - William Y. Huang, Richard Lippmann:
Neural Net and Traditional Classifiers. 387-396 - Ju-Seog Jang, Soo-Young Lee, Sang-Yung Shin:
An Optimization Network for Matrix Inversion. 397-401 - Jagmeet S. Kanwal:
How the Catfish Tracks Its Prey: An Interactive 'Pipelined' Processing System May Direct Foraging via Reticulospinal Neurons. 402-411 - James D. Keeler:
Capacity for Patterns and Sequences in Kanerva's SDM as Compared to Other Associative Memory Models. 412-421 - Christof Koch, Jin Luo, Carver Mead, James Hutchinson:
Computing Motion Using Resistive Networks. 422-431 - Anthony Kuh:
Performance Measures for Associative Memories that Learn and Forget. 432-441 - Alan S. Lapedes, Robert M. Farber:
How Neural Nets Work. 442-456 - Clifford Lau, Vicente Honrubia:
Distributed Neural Information Processing in the Vestibulo-Ocular System. 457-466 - Dietrich Lehmann, Daniel Brandeis, A. Horst, H. Ozaki, I. Pal:
Spontaneous and Information-Triggered Segments of Series of Human Brain Electric Field Maps. 467-473 - Harrison MonFook Leong:
Optimization with Artificial Neural Network Systems: A Mapping Principle and a Comparison to Gradient Based Methods. 474-484 - Ralph Linsker:
Towards an Organizing Principle for a Layered Perceptual Network. 485-494 - Hendricus G. Loos:
Reflexive Associative Memories. 495-504 - Bruce A. MacDonald:
Connecting to the Past. 505-514 - Stuart Mackie, Hans Peter Graf, Daniel B. Schwartz, John S. Denker:
Microelectronic Implementations of Connectionist Neural Networks. 515-523 - Charles M. Marcus, Robert M. Westervelt:
Basins of Attraction for Electronic Neural Networks. 524-533 - Robert J. Marks II, Les E. Atlas, Seho Oh, James A. Ritcey:
The Performance of Convex Set Projection Based Neural Networks. 534-543 - Bartlett W. Mel:
MURPHY: A Robot that Learns by Doing. 544-553 - Anthony N. Michel, Jay A. Farrell, Wolfgang Porod:
Stability Results for Neural Networks. 554-563 - Alexander Moopenn, Harry Langenbacher, A. P. Thakoor, S. K. Khanna:
Programmable Synaptic Chip for Electronic Neural Networks. 564-572 - Alan F. Murray, Anthony V. W. Smith, Zoe F. Butler:
Bit-Serial Neural Networks. 573-583 - André J. Noest:
Phasor Neural Networks. 584-591 - Thomas Petsche, Bradley W. Dickinson:
A Trellis-Structured Neural Network. 592-601 - Fernando J. Pineda:
Generalization of Back propagation to Recurrent and Higher Order Neural Networks. 602-611 - John C. Platt, Alan H. Barr:
Constrained Differential Optimization. 612-621 - Tomaso A. Poggio, Anya C. Hurlbert:
Learning a Color Algorithm from Examples. 622-631 - Anthony J. Robinson, F. Failside:
Static and Dynamic Error Propagation Networks with Application to Speech Coding. 632-641 - Bruce E. Rosen, James M. Goodwin, Jacques J. Vidal:
Learning by State Recurrence Detection. 642-651 - Ronald Rosenfeld, David S. Touretzky:
Scaling Properties of Coarse-Coded Symbol Memories. 652-661 - F. H. Schuling, H. A. K. Mastebroek, W. H. Zaagman:
An Adaptive and Heterodyne Filtering Procedure for the Imaging of Moving Objects. 662-673 - Christopher L. Scofield, Douglas L. Reilly, Charles Elbaum, Leon N. Cooper:
Pattern Class Degeneracy in an Unrestricted Storage Density Memory. 674-682 - Christopher L. Scofield:
A Mean Field Theory of Layer IV of Visual Cortex and Its Application to Artificial Neural Networks. 683-692 - J. F. Shepanski, S. A. Macy:
Teaching Artificial Neural Systems to Drive: Manual Training Techniques for Autonomous Systems. 693-700 - Ralph M. Siegel:
Discovering Structure from Motion in Monkey, Man and Machine. 701-708 - Ronald H. Silverman, Andrew S. Noetzel:
Time-Sequential Self-Organization of Hierarchical Neural Networks. 709-714 - Alexander Singer, John P. Donoghue:
A Computer Simulation of Cerebral Neocortex: Computational Capabilities of Nonlinear Neural Networks. 715-729 - Paul Smolensky:
Analysis of Distributed Representation of Constituent Structure in Connectionist Systems. 730-739 - Andreas Stafylopatis, Marios D. Dikaiakos, D. Kontoravdis:
Spatial Organization of Neural Networks: A Probabilistic Modeling Approach. 740-749 - W. Scott Stornetta, Tad Hogg, Bernardo A. Huberman:
A Dynamical Approach to Temporal Pattern Processing. 750-759 - Guo-Zheng Sun, Yee-Chun Lee, Hsing-Hen Chen:
A Novel Net that Learns Sequential Decision Process. 760-766 - Hisashi Suzuki, Suguru Arimoto:
Self-Organization of Associative Database and Its Applications. 767-774 - Gene A. Tagliarini, Edward W. Page:
A Neural-Network Solution to the Concentrator Assignment Problem. 775-782 - Manoel Fernando Tenorio:
Using Neural Networks to Improve Cochlear Implant Speech Perception. 783-793 - Gerald Tesauro, Terrence J. Sejnowski:
A 'Neural' Network that Learns to Play Backgammon. 794-803 - Sherryl Tomboulian:
Introduction to a System for Implementing Neural Net Connections on SIMD Architectures. 804-813 - Mario P. Vecchi, Jawad A. Salehi:
Neuromorphic Networks Based on Sparse Optical Orthogonal Codes. 814-823 - Jacques J. Vidal, John Haggerty:
Synchronization in Neural Nets. 824-829 - Harry Wechsler, George Lee Zimmerman:
Invariant Object Recognition Using a Distributed Associative Memory. 830-839 - Richard C. Windecker:
Learning in Networks of Nondeterministic Adaptive Logic Elements. 840-849 - Ben S. Wittner, John S. Denker:
Strategies for Teaching Layered Networks Classification Tasks. 850-859 - John L. Wyatt Jr., David L. Standley:
A Method for the Design of Stable Lateral Inhibition Networks that is Robust in the Presence of Circuit Parasitics. 860-868
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