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ORCIDNIPS 1988: Denver, CO, USA
- David S. Touretzky:
Advances in Neural Information Processing Systems 1, [NIPS Conference, Denver, Colorado, USA, 1988]. Morgan Kaufmann 1989, ISBN 1-55860-015-9
Part 1: Learning and Generalization
- Mark A. Gluck, M. Pavel, Van Henkle:
Constraints on Adaptive Networks for Modeling Human Generalization. 2-10 - Terence D. Sanger:
An Optimality Principle for Unsupervised Learning. 11-19 - David H. Ackley:
Associative Learning via Inhibitory Search. 20-28 - John E. Moody:
Fast Learning in Multi-Resolution Hierarchies. 29-39 - Alan H. Kramer, Alberto L. Sangiovanni-Vincentelli:
Efficient Parallel Learning Algorithms for Neural Networks. 40-48 - Lawrence Davis:
Mapping Classifier Systems Into Neural Networks. 49-56 - Manoel Fernando Tenorio, Wei-Tsih Lee:
Self Organizing Neural Networks for the Identification Problem. 57-64 - Pierre Baldi:
Linear Learning: Landscapes and Algorithms. 65-72 - Tal Grossman, Ronny Meir, Eytan Domany:
Learning by Choice of Internal Representations. 73-80 - Eric B. Baum, David Haussler:
What Size Net Gives Valid Generalization? 81-90 - Griff L. Bilbro, Reinhold Mann, Thomas K. Miller III, Wesley E. Snyder, David E. van den Bout, Mark W. White:
Optimization by Mean Field Annealing. 91-98 - Gerald Tesauro:
Connectionist Learning of Expert Preferences by Comparison Training. 99-106 - Michael Mozer, Paul Smolensky:
Skeletonization: A Technique for Trimming the Fat from a Network via Relevance Assessment. 107-115 - Eyal Yair, Allen Gersho:
The Boltzmann Perceptron Network: A Multi-Layered Feed-Forward Network Equivalent to the Boltzmann Machine. 116-123 - Richard Lippmann, Paul Beckman:
Adaptive Neural Net Preprocessing for Signal Detection in Non-Gaussian Noise. 124-132 - Sharad Singhal, Lance Wu:
Training Multilayer Perceptrons with the Extende Kalman Algorithm. 133-140 - Yann LeCun, Conrad C. Galland, Geoffrey E. Hinton:
GEMINI: Gradient Estimation Through Matrix Inversion After Noise Injection. 141-148 - Patrice Y. Simard, Mary B. Ottaway, Dana H. Ballard:
Fixed Point Analysis for Recurrent Networks. 149-159 - Subutai Ahmad, Gerald Tesauro:
Scaling and Generalization in Neural Networks: A Case Study. 160-168 - Raoul Tawel:
Does the Neuron "Learn" Like the Synapse? 169-176 - Stephen Jose Hanson, Lorien Y. Pratt:
Comparing Biases for Minimal Network Construction with Back-Propagation. 177-185 - Ralph Linsker:
An Application of the Principle of Maximum Information Preservation to Linear Systems. 186-194 - David B. Parker, Mark A. Gluck, Eric S. Reifsnider:
Learning with Temporal Derivatives in Pulse-Coded Neuronal Systems. 195-203
Part 2: Application
- Hong C. Leung, Victor Zue:
Applications of Error Back-Propagation to Phonetic Classification. 206-214 - Alex Waibel:
Consonant Recognition by Modular Construction of Large Phonemic Time-Delay Neural Networks. 215-223 - Yoshua Bengio, Régis Cardin, Renato de Mori, Piero Cosi:
Use of Multi-Layered Networks for Coding Speech with Phonetic Features. 224-231 - Mitsuo Komura, Akio Tanaka:
Speech Production Using A Neural Network with a Cooperative Learning Mechanism. 232-239 - Erich J. Smythe:
Temporal Representations in a Connectionist Speech System. 240-247 - Richard Fozzard, Gary Bradshaw, Louis Ceci:
A Connectionist Expert System that Actually Works. 248-255 - Rodney M. Goodman, John W. Miller, Padhraic Smyth:
An Information Theoretic Approach to Rule-Based Connectionist Expert Systems. 256-263 - Martine Naillon, Jean-Bernard Theeten:
Neural Approach for TV Image Compression Using a Hopfield Type Network. 264-271 - Bernd-Peter Paris, Geoffrey C. Orsak, Mahesh K. Varanasi, Behnaam Aazhang:
Neural Net Receivers in Multiple Access-Communications. 272-280 - Stanley C. Ahalt, Frederick D. Garber, Ismail Jouny, Ashok K. Krishnamurthy:
Performance of Synthetic Neural Network Classification of Noisy Radar Signals. 281-288 - Allen M. Waxman, Michael Seibert, Robert K. Cunningham, Jian Wu:
Neural Analog Diffusion-Enhancement Layer and Spatio-Temporal Grouping in Early Vision. 289-296 - Anya C. Hurlbert, Tomaso A. Poggio:
A Network for Image Segmentation Using Color. 297-304 - Dean Pomerleau:
ALVINN: An Autonomous Land Vehicle in a Neural Network. 305-313 - Phillip Alvelda, A. Miguel San Martin:
Neural Network Star Pattern Recognition for Spacecraft Attitude Determination and Control. 314-322 - John S. Denker, W. R. Gardner, Hans Peter Graf, Donnie Henderson, Richard E. Howard, Wayne E. Hubbard, Lawrence D. Jackel, Henry S. Baird, Isabelle Guyon:
Neural Network Recognizer for Hand-Written Zip Code Digits. 323-331 - Yoshihiro Mori, Kazuhiko Yokosawa:
Neural Networks that Learn to Discriminate Similar Kanji Characters. 332-339 - Timothy S. Wilkinson, Dorothy A. Mighell, Joseph W. Goodman:
Backpropagation and Its Application to Handwritten Signature Verification. 340-347 - Bartlett W. Mel:
Further Explorations in Visually-Guided Reaching: Making MURPHY Smarter. 348-355 - Kenneth Y. Goldberg, Barak A. Pearlmutter:
Using Backpropagation with Temporal Windows to Learn the Dynamics of the CMU Direct-Drive Arm II. 356-363
Part 3: Neurobiology
- Clay Spence, John C. Pearson, J. J. Gelfand, R. M. Peterson, W. E. Sullivan:
Neuronal Maps for Sensory-Motor Control in the Barn Owl. 366-374 - Kenneth D. Miller, Joseph B. Keller, Michael P. Stryker:
Models of Ocular Dominance Column Formation: Analytical and Computational Results. 375-383 - Sylvie Ryckebusch, James M. Bower, Carver Mead:
Modeling Small Oscillating Biological Networks in Analog VLSI. 384-393 - Patric K. Stanton, Terrence J. Sejnowski:
Storing Covariance by the Associative Long-Term Potentation and Depression of Synaptic Strengths in the Hippocampus. 394-401 - Zhaoping Li, John J. Hopfield:
Modeling the Olfactory Bulb - Coupled Nonlinear Oscillators. 402-409 - Michael G. Paulin, Mark E. Nelson, James M. Bower:
Neural Control of Sensory Acquisition: The Vestibulo-Ocular Reflex. 410-418 - Daniel L. Alkon, Francis K. H. Quek, Thomas P. Vogl:
Computer Modeling of Associative Learning. 419-435 - Brian Rasnow, Christopher Assad, Mark E. Nelson, James M. Bower:
Simulation and Measurement of the Electric Fields Generated by Weakly Electric Fish. 436-443 - Jun Zhang, John P. Miller:
A Model for Resolution Enhancement (Hyperacuity) in Sensory Representation. 444-450 - Shigeru Tanaka:
Theory of Self-Organization of Cortical Maps. 451-458 - Bill Baird:
A Bifurcation Theory Approach to the Programming of Periodic Attractors in Network Models of Olfactory Cortex. 459-467 - Martin I. Sereno:
Learning the Solution to the Aperture Problem for Pattern Motion with a Hebb Rule. 468-476 - Norberto M. Grzywacz, Franklin R. Amthor:
A Computationally Robust Anatomical Model for Retinal Directional Selectivity. 477-484 - Matthew A. Wilson, Upinder S. Bhalla, John D. Uhley, James M. Bower:
GENESIS: A System for Simulating Neural Networks. 485-492
Part 4: Structured Networks
- Avrim Blum, Ronald L. Rivest:
Training a 3-Node Neural Network is NP-Complete. 494-501 - Hervé Bourlard, Christian Wellekens:
Links Between Markov Models and Multilayer Perceptrons. 502-510 - Moshe Kam, Roger S.-K. Cheng:
Convergence and Pattern-Stabilization in the Boltzmann Machine. 511-518 - Yves Chauvin:
A Back-Propagation Algorithm with Optimal Use of Hidden Units. 519-526 - Jordan B. Pollack:
Implications of Recursive Distributed Representations. 527-536 - Eugene Santos Jr.:
A Massively Parallel Self-Tuning Context-Free Parser. 537-544 - Trent E. Lange, Michael G. Dyer:
Dynamic, Non-Local Role Bindings and Inferencing in a Localist Network for Natural Language Understanding. 545-552 - James A. Hendler:
Spreading Activation over Distributed Microfeatures. 553-559 - Alexandr B. Kirillov, Galina Borisyuk, Roman Borisyuk, Ye. I. Kovalenko, V. I. Makarenko, V. A. Chulaevsky, V. I. Kryukov:
A Model of Neural Oscillator for a Unified Submodule. 560-567 - Charles M. Marcus, Robert M. Westervelt:
Dynamics of Analog Neural Networks with Time Delay. 568-576 - Randall D. Beer, Hillel J. Chiel, Leon Sterling:
Heterogeneous Neural Networks for Adaptive Behavior in Dynamic Environments. 577-585 - David Rogers:
Statistical Prediction with Kanerva's Sparse Distributed Memory. 586-593 - Griff L. Bilbro, Wesley E. Snyder:
Range Image Restoration Using Mean Field Annealing. 594-601 - Jared Leinbach:
Automatic Local Annealing. 602-609 - V. I. Kryukov:
"Neurolocator", A Model of Attention. 610-617 - Eric Mjolsness, Gene Gindi, P. Anandan:
Neural Networks for Model Matching and Perceptual Organization. 618-625 - David S. Touretzky:
Analyzing the Energy Landscapes of Distributed Winner-Take-All Networks. 626-633 - E. Majani, Ruth Erlanson, Yaser S. Abu-Mostafa:
On the K-Winners-Take-All Network. 634-642 - David Servan-Schreiber, Axel Cleeremans, James L. McClelland:
Learning Subsequential Structure in Simple Recurrent Networks. 643-652 - C. L. Winter:
An Adaptive Network That Learns Sequences of Transitions. 653-660
Part 5: Implementation
- David Feld, Joe Eisenberg, Edwin Lewis:
A Passive Shared Element Analog Electrical Cochlea. 662-670 - Alister Hamilton, Alan F. Murray, Lionel Tarassenko:
Programmable Analog Pulse-Firing Neural Networks. 671-677 - Jack L. Meador, Clint S. Cole:
A Low-Power CMOS Circuit Which Emulates Temporal Electrical Properties of Neurons. 678-686 - John G. Harris:
An Analog VLSI Chip for Thin-Plate Surface Interpolation. 687-694 - Bahram Nabet, Robert B. Darling, Robert B. Pinter:
Analog Implementation of Shunting Neural Networks. 695-702 - John Lazzaro, Sylvie Ryckebusch, Misha Mahowald, Carver Mead:
Winner-Take-All Networks of O(N) Complexity. 703-711 - Paul Mueller, Jan Van der Spiegel, David Blackman, Timothy Chiu, Thomas Clare, Joseph Dao, Christopher Donham, Tzu-pu Hsieh, Marc Loinaz:
A Programmable Analog Neural Computer and Simulator. 712-719 - Tobi Delbrück, Carver Mead:
An Electronic Photoreceptor Sensitive to Small Changes in Intensity. 720-727 - Martin J. Johnson, Nigel M. Allinson, Kevin J. Moon:
Digital Realisation of Self-Organizing Maps. 728-738 - James R. Mann, Sheldon Gilbert:
An Analog Self-Organizing Neural Network Chip. 739-747 - Joshua Alspector, Bhusan Gupta, Robert B. Allen:
Performance of a Stochastic Learning Microchip. 748-760 - Daniel B. Schwartz, Richard E. Howard, Wayne E. Hubbard:
Adaptive Neural Networks Using MOS Charge Storage. 761-768 - Allan Hartstein, Roger H. Koch:
A Self-Learning Neural Network. 769-776 - Mark R. Walker, Siamack Haghighi, A. Afghan, Lex A. Akers:
Training a Limited-Interconnect, Synthetic Neural IC. 777-784 - Andreas G. Andreou:
Electronic Receptors for Tactile/Haptic Sensing. 785-792
Appendix: Summaries of Invited Talks
- Valentino Braitenberg:
Neural Architecture. 794 - M. Konishi:
Song Learning in Birds. 795 - John S. Bridle:
Speech Recognition: Statistical and Neural Information Processing Approaches. 796-801 - John P. Miller:
Cricket Wind Detection. 802-807
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