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ORCIDNIPS 1990: Denver, CO, USA
- Richard Lippmann, John E. Moody, David S. Touretzky:
Advances in Neural Information Processing Systems 3, [NIPS Conference, Denver, Colorado, USA, November 26-29, 1990]. Morgan Kaufmann 1991, ISBN 1-55860-184-8
Part 1: Neurobiology
- Jack D. Cowan, A. E. Friedman:
Studies of a Model for the Development and Regeneration of Eye-Brain Maps. 3-10 - Klaus Obermayer, Helge J. Ritter, Klaus Schulten:
Development and Spatial Structure of Cortical Feature Maps: A Model Study. 11-17 - Shigeru Tanaka:
Interaction Among Ocularity, Retinotopy and On-center/Off-center Pathways. 18-25 - Jack D. Cowan, A. E. Friedman:
Simple Spin Models for the Development of Ocular Dominance Columns and Iso-Orientation Patches. 26-31 - Thomas J. Anastasio:
A Recurrent Neural Network Model of Velocity Storage in the Vestibulo-Ocular Reflex. 32-38 - Thomas H. Brown, Zachary F. Mainen, Anthony M. Zador, Brenda J. Claiborne:
Self-organization of Hebbian Synapses in Hippocampal Neurons. 39-45 - Michael E. Hasselmo, Brooke P. Anderson, James M. Bower:
Cholinergic Modulation May Enhance Cortical Associative Memory Function. 46-52
Part 2: Neuro-Dynamics
- Thomas B. Kepler, L. F. Abbott, Eve Marder:
Order Reduction for Dynamical Systems Describing the Behavior of Complex Neurons. 55-61 - Jack D. Cowan:
Stochastic Neurodynamics. 62-69 - Todd K. Leen:
Dynamics of Learning in Recurrent Feature-Discovery Networks. 70-76 - Eric Mjolsness, Willard L. Miranker:
A Lagrangian Approach to Fixed Points. 77-83 - Wulfram Gerstner:
Associative Memory in a Network of 'Biological' Neurons. 84-90 - Bill Baird, Frank H. Eeckman:
CAM Storage of Analog Patterns and Continuous Sequences with 3N2 Weights. 91-97 - Charles M. Marcus, F. R. Waugh, Robert M. Westervelt:
Connection Topology and Dynamics in Lateral Inhibition Networks. 98-104 - Patrice Y. Simard, Jean Pierre Raysz, Bernard Victorri:
Shaping the State Space Landscape in Recurrent Networks. 105-112 - Nikzad Benny Toomarian, Jacob Barhen:
Adjoint-Functions and Temporal Learning Algorithms in Neural Networks. 113-120
Part 3: Oscillations
- Ernst Niebur, Daniel M. Kammen, Christof Koch, Daniel L. Ruderman, Heinz G. Schuster:
Phase-coupling in Two-Dimensional Networks of Interacting Oscillators. 123-129 - André Longtin:
Oscillation Onset in Neural Delayed Feedback. 130-136 - Leonid Kruglyak, William Bialek:
Analog Computation at a Critical Point. 137-144
Part 4: Temporal Reasoning
- Esther Levin:
Modeling Time Varying Systems Using Hidden Control Neural Architecture. 147-154 - Ulrich Bodenhausen, Alex Waibel:
The Tempo 2 Algorithm: Adjusting Time-Delays By Supervised Learning. 155-161 - Bert de Vries, José Carlos Príncipe:
A Theory for Neural Networks with Time Delays. 162-168 - Einar Sørheim:
ART2/BP Architecture for Adaptive Estimation of Dynamic Processes. 169-175 - Andreas V. M. Herz, Zhaoping Li, J. Leo van Hemmen:
Statistical Mechanics of Temporal Association in Neural Networks. 176-182 - Anthony Kuh, Thomas Petsche, Ronald L. Rivest:
Learning Time-Varying Concepts. 183-189 - Scott E. Fahlman:
The Recurrent Cascade-Correlation Architecture. 190-196
Part 5: Speech
- Joe Tebelskis, Alex Waibel, Bojan Petek, Otto Schmidbauer:
Continuous Speech Recognition by Linked Predictive Neural Networks. 199-205 - Robert B. Allen, Candace A. Kamm:
A Recurrent Neural Network for Word Identification from Continuous Phoneme Strings. 206-212 - Hervé Bourlard, Nelson Morgan, Chuck Wooters:
Connectionist Approaches to the Use of Markov Models for Speech Recognition. 213-219 - Mark A. Fanty, Ronald A. Cole:
Spoken Letter Recognition. 220-226 - Ken-ichi Iso, Takao Watanabe:
Speech Recognition Using Demi-Syllable Neural Prediction Model. 227-233 - John S. Bridle, Stephen J. Cox:
RecNorm: Simultaneous Normalisation and Classification Applied to Speech Recognition. 234-240 - Nathan Intrator:
Exploratory Feature Extraction in Speech Signals. 241-247 - Hong C. Leung, James R. Glass, Michael S. Phillips, Victor Zue:
Phonetic Classification and Recognition Using the Multi-Layer Perceptron. 248-254 - Victor Zue, James R. Glass, David Goodine, Lynette Hirschman, Hong C. Leung, Michael S. Phillips, Joseph Polifroni, Stephanie Seneff:
From Speech Recognition to Spoken Language Understanding. 255-261 - Khalid Choukri:
Speech Recognition Using Connectionist Approaches. 262-269
Part 6: Signal Processing
- Herbert L. Roitblat, Patrick W. B. Moore, Paul E. Nachtigall, Ralph H. Penner:
Natural Dolphin Echo Recognition Using an Integrator Gateway Network. 273-279 - David C. Tam:
Signal Processing by Multiplexing and Demultiplexing in Neurons. 282-288 - John C. Pearson, Clay Spence, Ronald Sverdlove:
Applications of Neural Networks in Video Signal Processing. 289-295
Part 7: Visual Processing
- Richard S. Zemel, Geoffrey E. Hinton:
Discovering Viewpoint-Invariant Relationships That Characterize Objects. 299-305 - Volker Tresp:
A Neural Network Approach for Three-Dimensional Object Recognition. 306-312 - Shelly D. D. Goggin, Kristina M. Johnson, Karl E. Gustafson:
A Second-Order Translation, Rotation and Scale Invariant Neural Network. 313-319 - Martin I. Sereno, Margaret E. Sereno:
Learning to See Rotation and Dilation with a Hebb Rule. 320-327 - Alireza Khotanzad, Ying-Wung Lee:
Stereopsis by a Neural Network Which Learns the Constraints. 327-334 - Amnon Shashua, Shimon Ullman:
Grouping Contours by Iterated Pairing Networks. 335-341 - Ennio Mingolla:
Neural Dynamics of Motion Segmentation and Grouping. 342-348 - H. Taichi Wang, Bimal Mathur, Christof Koch:
A Multiscale Adaptive Network Model of Motion Computation in Primates. 349-355 - Daphna Weinshall:
Qualitative Structure From Motion. 356-362 - William Bialek, Daniel L. Ruderman, A. Zee:
Optimal Sampling of Natural Images. 363-369 - Andrew W. Moore, John Allman, Geoffrey C. Fox, Rodney M. Goodman:
A VLSI Neural Network for Color Constancy. 370-376 - Fred Rieke, W. Geoffrey Owen, William Bialek:
Optimal Filtering in the Salamander Retina. 377-383 - Jeffrey L. Teeters, Frank H. Eeckman, Frank S. Werblin:
A Four Neuron Circuit Accounts for Change Sensitive Inhibition in Salamander Retina. 384-390 - Josef Skrzypek:
Feedback Synapse to Cone and Light Adaptation. 391-398 - Wyeth Bair, Christof Koch:
An Analog VLSI Chip for Finding Edges from Zero-crossings. 399-405 - Timothy K. Horiuchi, John Lazzaro, Andrew Moore, Christof Koch:
A Delay-Line Based Motion Detection Chip. 406-412
Part 8: Control and Navigation
- Charles Schley, Yves Chauvin, Van Henkle, Richard M. Golden:
Neural Networks Structured for Control Application to Aircraft Landing. 415-421 - Lionel Tarassenko, Michael Brownlow, Gillian Marshall, Jan Tombs, Alan F. Murray:
Real-Time Autonomous Robot Navigation Using VLSI Neural Networks. 422-428 - Dean Pomerleau:
Rapidly Adapting Artificial Neural Networks for Autonomous Navigation. 429-435 - Masazumi Katayama, Mitsuo Kawato:
Learning Trajectory and Force Control of an Artificial Muscle Arm. 436-442 - Robert C. Frye, Kevin D. Cummings, Edward A. Rietman:
Proximity Effect Corrections in Electron Beam Lithography. 443-449 - Sebastian Thrun, Knut Möller, Alexander Linden:
Planning with an Adaptive World Model. 450-456 - Jonathan Bachrach:
A Connectionist Learning Control Architecture for Navigation. 457-463 - Peter Dayan:
Navigating Through Temporal Difference. 464-470 - Richard S. Sutton:
Integrated Modeling and Control Based on Reinforcement Learning. 471-478 - Aloke Guha:
A Reinforcement Learning Variant for Control Scheduling. 479-485 - Bruce E. Rosen, James M. Goodwin, Jacques J. Vidal:
Adaptive Range Coding. 486-492 - Rodolfo A. Milito, Isabelle Guyon, Sara A. Solla:
Neural Network Implementation of Admission Control. 493-499 - Jürgen Schmidhuber:
Reinforcement Learning in Markovian and Non-Markovian Environments. 500-506 - Randall D. Beer, G. J. Kacmarcik, Roy E. Ritzmann, Hillel J. Chiel:
A Model of Distributed Sensorimotor Control in the Cockroach Escape Turn. 507-513 - William E. Faller, Marvin W. Luttges:
Flight Control in the Dragonfly: A Neurobiological Simulation. 514-520
Part 9: Applications
- Henrik Fredholm, Henrik Bohr, Jakob Bohr, Søren Brunak, Rodney M. J. Cotterill, Benny Lautrup, Steffen B. Petersen:
A Novel Approach to Prediction of the 3-Dimensional Structures. 523-529 - Michiel O. Noordewier, Geoffrey G. Towell, Jude W. Shavlik:
Training Knowledge-Based Neural Networks to Recognize Genes. 530-536 - Kenneth A. Marko:
Neural Network Application to Diagnostics. 537-543 - John L. Perry, Douglas R. Baumgardt:
Lg Depth Estimation and Ripple Fire Characterization. 544-550 - Joseph E. Collard:
A B-P ANN Commodity Trader. 551-556 - James D. Keeler, David E. Rumelhart, Wee Kheng Leow:
Integrated Segmentation and Recognition of Hand-Printed Numerals. 557-563 - Garrison W. Cottrell, Janet Metcalfe:
EMPATH: Face, Emotion, and Gender Recognition Using Holons. 564-571 - Beatrice A. Golomb, David T. Lawrence, Terrence J. Sejnowski:
SEXNET: A Neural Network Identifies Sex From Human Faces. 572-579 - Yoichi Hayashi:
A Neural Expert System with Automated Extraction of Fuzzy If-Then Rules. 578-584 - Ruth Erlanson, Yaser S. Abu-Mostafa:
Analog Neural Networks as Decoders. 585-588
Part 10: Language and Cognition
- Geraldine Legendre, Yoshiro Miyata, Paul Smolensky:
Distributed Recursive Structure Processing. 591-597 - Paul W. Munro, Mary Tabasko:
Translating Locative Prepositions. 598-604 - Michael Gasser, Chan-Do Lee:
A Short-Term Memory Architecture for the Learning of Morphophonemic Rules. 605-611 - David S. Touretzky, Deirdre W. Wheeler:
Exploiting Syllable Structure in a Connectionist Phonology Model. 612-618 - Jordan B. Pollack:
Language Induction by Phase Transition in Dynamical Recognizers. 619-626 - Michael Mozer:
Discovering Discrete Distributed Representations. 627-634 - Janet Wiles, Michael S. Humphreys, John D. Bain, Simon Dennis:
Direct Memory Access Using Two Cues. 635-641 - Eytan Ruppin, Yehezkel Yeshurun:
An Attractor Neural Network Model of Recall and Recognition. 642-648 - John K. Kruschke:
ALCOVE: A Connectionist Model of Human Category Learning. 649-655 - Stephen Jose Hanson, Mark A. Gluck:
Spherical Units as Dynamic Consequential Regions. 656-664 - Roger N. Shepard, Sheila Kannappan:
Connectionist Implementation of a Theory of Generalization. 665-671
Part 11: Local Basis Funtions
- Jerome H. Friedman:
Adaptive Spline Networks. 675-683 - Stephen H. Lane, Marshall Flax, David Handelman, Jack Gelfand:
Multi-Layer Perceptrons with B-Spline Receptive Field Functions. 684-692 - Stephen M. Omohundro:
Bumptrees for Efficient Function, Constraint and Classification Learning. 693-699 - Terence D. Sanger:
Basis-Function Trees as a Generalization of Local Variable Selection Methods. 700-706 - Sherif M. Botros, Christopher G. Atkeson:
Generalization Properties of Radial Basis Functions. 707-713 - John C. Platt:
Leaning by Combining Memorization and Gradient Descent. 714-720 - Visakan Kadirkamanathan, Mahesan Niranjan, Frank Fallside:
Sequential Adaptation of Radial Basis Function Networks. 721-727 - Avijit Saha, Jim Christian, Dun-Sung Tang, Chuan-lin Wu:
Oriented Non-Radial Basis Functions for Image Coding and Analysis. 728-734 - Pierre Baldi:
Computing with Arrays of Bell-Shaped and Sigmoid Functions. 735-742 - Yagyensh C. Pati, Perinkulam S. Krishnaprasad:
Discrete Affine Wavelet Transforms. 743-749 - Federico Girosi, Tomaso A. Poggio, Bruno Caprile:
Extensions of a Theory of Networks for Approximation and Learning. 750-756 - Bartlett W. Mel, Stephen M. Omohundro:
How Receptive Field Parameters Affect Neural Learning. 757-763
Part 12: Learning Systems
- Robert A. Jacobs, Michael I. Jordan:
A Competitive Modular Connectionist Architecture. 767-773 - Steven J. Nowlan, Geoffrey E. Hinton:
Evaluation of Adaptive Mixtures of Competing Experts. 774-780 - Léon Bottou, Patrick Gallinari:
A Framework for the Cooperation of Learning Algorithms. 781-788 - Michael Mozer, Todd Soukup:
Connectionist Music Composition Based on Melodic and Stylistic Constraints. 789-796 - Eric I. Chang, Richard Lippmann:
Using Genetic Algorithms to Improve Pattern Classification Performance. 797-803 - Ron Keesing, David G. Stork:
Evolution and Learning in Neural Networks. 804-810 - Terrence Fine:
Designing Linear Threshold Based Neural Network Pattern Classifiers. 811-817 - Padhraic Smyth:
On Stochastic Complexity and Admissible Models for Neural Network Classifiers. 818-824 - Ajay Gupta, Wolfgang Maass:
Efficient Design of Boltzmann Machines. 825-831 - Christian Darken, John E. Moody:
Note on Learning Rate Schedules for Stochastic Optimization. 832-838 - John S. Baras, Anthony LaVigna:
Convergence of a Neural Network Classifier. 839-845 - Griff L. Bilbro, David E. van den Bout:
Learning Theory and Experiments with Competitive Networks. 846-852 - John S. Denker, Yann LeCun:
Transforming Neural-Net Output Levels to Probability Distributions. 853-859 - John F. Kolen, Jordan B. Pollack:
Back Propagation is Sensitive to Initial Conditions. 860-867 - Michael L. Rossen:
Closed-Form Inversion of Backpropagation Networks. 868-872
Part 13: Learning and Generalization
- Andreas S. Weigend, David E. Rumelhart, Bernardo A. Huberman:
Generalization by Weight-Elimination with Application to Forecasting. 875-882 - Sanjay Biswas, Santosh S. Venkatesh:
The Devil and the Network. 883-889 - Yves Chauvin:
Generalization Dynamics in LMS Trained Linear Networks. 890-896 - Anders Krogh, John A. Hertz:
Dynamics of Generalization in Linear Perceptrons. 897-903 - Eric B. Baum, Kevin J. Lang:
Constructing Hidden Units Using Examples and Queries. 904-910 - David A. Cohn, Gerald Tesauro:
Can Neural Networks Do Better Than the Vapnik-Chervonenkis Bounds? 911-917 - Yann LeCun, Ido Kanter, Sara A. Solla:
Second Order Properties of Error Surfaces. 918-924 - Barak A. Pearlmutter, Ronald Rosenfeld
:
Chaitin-Kolmogorov Complexity and Generalization in Neural Networks. 925-931 - Robert R. Snapp, Demetri Psaltis, Santosh S. Venkatesh:
Asymptotic Slowing Down of the Nearest-Neighbor Classifier. 932-938 - Eduardo D. Sontag:
Remarks on Interpolation and Recognition Using Neural Nets. 939-945 - Robert C. Williamson:
epsilon-Entropy and the Complexity of Feedforward Neural Networks. 946-952 - Vwani P. Roychowdhury, Alon Orlitsky, Kai-Yeung Siu, Thomas Kailath:
On the Circuit Complexity of Neural Networks. 953-959
Part 14: Performance Comparisons
- Ah Chung Tsoi, R. A. Pearson:
Comparison of Three Classification Techniques: CART, C4.5 and Multi-Layer Perceptrons. 963-969 - Kenney Ng, Richard Lippmann:
Practical Characteristics of Neural Network and Conventional Patterns Classifiers. 970-976 - Richard Rohwer:
Time Trials on Second-Order and Variable-Learning-Rate Algorithms. 977-983 - Wesley E. Snyder, Daniel Nissman, David E. van den Bout, Griff L. Bilbro:
Kohonen Networks and Clustering. 984-990
Part 15: VLSI
- Mark A. Holler:
VLSI Implementations of Learning and Memory Systems. 993-1000 - Alan H. Kramer, Chi-Kai Sin, Robert R. Chu, Pink K. Ko:
Compact EEPROM-based Weight Functions. 1001-1007 - Daniel B. Schwartz, Vijay K. Samalam:
An Analog VLSI Splining Network. 1008-1014 - Joshua Alspector, Robert B. Allen, Anthony Jayakumar, Torsten Zeppenfeld, Ronny Meir:
Relaxation Networks for Large Supervised Learning Problems. 1015-1021 - W. Thomas Miller III, Brian A. Box, Erich C. Whitney, James M. Glynn:
Design and Implementation of a High Speed CMAC Neural Network. 1022-1027 - Hal McCartor:
Back Propagation Implementation. 1028-1031 - Hans Peter Graf, R. Janow, Donnie Henderson, R. Lee:
Reconfigurable Neural Net Chip with 32K Connections. 1032-1038 - Michael L. Chuang, Alice M. Chiang:
Simulation of the Neocognitron on a CCD Parallel Processing Architecture. 1039-1045 - Matthew S. Melton, Tan Phan, Douglas S. Reeves, David E. van den Bout:
VLSI Implementation of TInMANN. 1046-1052
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