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ORCIDNIPS 1991: Denver, CO, USA
- John E. Moody, Stephen Jose Hanson, Richard Lippmann:
Advances in Neural Information Processing Systems 4, [NIPS Conference, Denver, Colorado, USA, December 2-5, 1991]. Morgan Kaufmann 1992, ISBN 1-55860-222-4
Neurobiology
- J. Allan Hobson, Adam N. Mamelak, Jeffrey P. Sutton:
Models Wanted: Must Fit Dimensions of Sleep and Dreaming. 3-10 - Mark Sydorenko, Eric D. Young:
Stationarity of Synaptic Coupling Strength Between Neurons with Nonstationary Discharge Properties. 11-18 - Peter Dayan, Geoffrey J. Goodhill:
Perturbing Hebbian Rules. 19-26 - Robert R. de Ruyter van Steveninck, William Bialek:
Statistical Reliability of a Blowfly Movement-Sensitive Neuron. 27-34 - Bartlett W. Mel:
The Clusteron: Toward a Simple Abstraction for a Complex Neuron. 35-42 - Öjvind Bernander, Christof Koch, Rodney J. Douglas:
Network Activity Determines Spatio-Temporal Integration in Single Cells. 43-50 - Anthony M. Zador, Brenda J. Claiborne, Thomas H. Brown:
Nonlinear Pattern Separation in Single Hippocampal Neurons with Active Dendritic Membrane. 51-58 - Anthony J. Bell:
Self-organization in Real Neurons: Anti-Hebb in 'Channel Space'? 59-66 - Adi R. Bulsara, E. W. Jacobs, Frank Moss:
Single Neuron Model: Response to Weak Modulation in the Presence of Noise. 67-74 - A. B. Bonds:
Dual Inhibitory Mechanisms for Definition of Receptive Field Characteristics in a Cat Striate Cortex. 75-82 - Klaus Obermayer, Klaus Schulten, Gary G. Blasdel:
A Comparison between a Neural Network Model for the Formation of Brain Maps and Experimental Data. 83-90 - Ron Keesing, David G. Stork, Carla J. Shatz:
Retinogeniculate Development: The Role of Competition and Correlated Retinal Activity. 91-97
Neuro-Dynamics
- James T. Buchanan:
Locomotion in a Lower Vertebrate: Studies of the Cellular Basis of Rhythmogenesis and Oscillator Coupling. 101-108 - Kenji Doya, Shuji Yoshizawa:
Adaptive Synchronization of Neural and Physical Oscillators. 109-116 - Heinz G. Schuster, Christof Koch:
Burst Synchronization without Frequency Locking in a Completely Solvable Neural Network Model. 117-124 - David Horn, Marius Usher:
Oscillatory Model of Short Term Memory. 125-132
Speech
- Patrick Haffner, Alex Waibel:
Multi-State Time Delay Networks for Continuous Speech Recognition. 135-142 - José Carlos Príncipe, Bert de Vries, Jyh-Ming Kuo, Pedro Guedes de Oliveira:
Modeling Applications with the Focused Gamma Net. 143-150 - Esther Levin, Roberto Pieraccini, Enrico Bocchieri:
Time-Warping Network: A Hybrid Framework for Speech Recognition. 151-158 - Elliot Singer, Richard Lippmann:
Improved Hidden Markov Models Speech Recognition Using Radial Basis Function Networks. 159-166 - Steve Renals, Nelson Morgan, Hervé Bourlard, Horacio Franco, Michael Cohen:
Connectionist Optimisation of Tied Mixture Hidden Markov Models. 167-174 - Yoshua Bengio, Renato de Mori, Giovanni Flammia, Ralf Kompe:
Neural Network - Gaussian Mixture Hybrid for Speech Recognition or Density Estimation. 175-182 - Alex Waibel, Ajay N. Jain, Arthur E. McNair, Joe Tebelskis, Louise Osterholtz, Hiroaki Saito, Otto Schmidbauer, Tilo Sloboda, Monika Woszczyna:
JANUS: Speech-to-Speech Translation Using Connectionist and Non-Connectionist Techniques. 183-190 - Makoto Hirayama, Eric Vatikiotis-Bateson, Mitsuo Kawato, Michael I. Jordan:
Forward Dynamics Modeling of Speech Motor Control Using Physiological Data. 191-198 - Mark A. Fanty, Ronald A. Cole, Krist Roginski:
English Alphabet Recognition with Telephone Speech. 199-206
Language
- Ajay N. Jain:
Generalization Performance in PARSEC - A Structured Connectionist Parsing Architecture. 209-216 - Gadi Pinkus:
Constructing Proofs in Symmetric Networks. 217-224 - Prahlad Gupta, David S. Touretzky:
A Connectionist Learning Approach to Analyzing Linguistic Stress. 225-232 - Ronald A. Sumida, Michael G. Dyer:
Propagation Filters in PDS Networks for Sequencing and Ambiguity Resolution. 233-240 - Yeshwant K. Muthusamy, Ronald A. Cole:
A Segment-Based Automatic Language Identification System. 241-248
Temporal Sequences
- Satinder Singh:
The Efficient Learning of Multiple Task Sequences. 251-258 - Gerald Tesauro:
Practical Issues in Temporal Difference Learning. 259-266 - Hermann Hild, Johannes Feulner, Wolfram Menzel:
HARMONET: A Neural Net for Harmonizing Chorales in the Style of J. S. Bach. 267-274 - Michael Mozer:
Induction of Multiscale Temporal Structure. 275-282 - Jeffrey P. Sutton, Adam N. Mamelak, J. Allan Hobson:
Network Model of State-Dependent Sequencing. 283-290 - Jürgen Schmidhuber:
Learning Unambiguous Reduced Sequence Descriptions. 291-298
Recurrent Networks
- Jerome T. Connor, Les E. Atlas, R. Douglas Martin:
Recurrent Networks and NARMA Modeling. 301-308 - Raymond L. Watrous, Gary M. Kuhn:
Induction of Finite-State Automata Using Second-Order Recurrent Networks. 309-317 - C. Lee Giles
, Clifford B. Miller, Dong Chen, Guo-Zheng Sun, Hsing-Hen Chen, Yee-Chun Lee:
Extracting and Learning an Unknown Grammar with Recurrent Neural Networks. 317-324 - Janet Wiles, Anthony Bloesch:
Operators and Curried Functions: Training and Analysis of Simple Recurrent Networks. 325-332 - Guo-Zheng Sun, Hsing-Hen Chen, Yee-Chun Lee:
Green's Function Method for Fast On-Line Learning Algorithm of Recurrent Neural Networks. 333-340 - Trent E. Lange:
Dynamically-Adaptive Winner-Take-All Networks. 341-348
Vision
- David A. Robinson:
Information Processing to Create Eye Movements. 351-355 - Emad N. Eskandar, Barry J. Richmond, John A. Hertz, Lance M. Optican, Troels W. Kjær:
Decoding of Neuronal Signals in Visual Pattern Recognition. 356-363 - Davi Geiger, Ricardo A. Marques Pereira:
Learning How to Teach or Selecting Minimal Surface Data. 364-371 - Suzanna Becker, Geoffrey E. Hinton:
Learning to Make Coherent Predictions in Domains with Discontinuities. 372-379 - Paul A. Viola, Stephen G. Lisberger, Terrence J. Sejnowski:
Recurrent Eye Tracking Network Using a Distributed Representation of Image Motion. 380-387 - Trevor Darrell, Alex Pentland:
Against Edges: Function Approximation with Multiple Support Maps. 388-395 - Paul R. Cooper, Peter N. Prokopowicz:
Markov Random Fields Can Bridge Levels of Abstraction. 396-403 - Amnon Shashua:
Illumination and View Position in 3D Visual Recognition. 404-411 - Alexandre Pouget, Stephen A. Fisher, Terrence J. Sejnowski:
Hierarchical Transformation of Space in the Visual System. 412-419 - Subutai Ahmad:
VISIT: A Neural Model of Covert Visual Attention. 420-427 - Eric Mjolsness:
Visual Grammars and Their Neural Nets. 428-435 - Michael Mozer, Richard S. Zemel, Marlene Behrmann:
Learning to Segment Images Using Dynamic Feature Binding. 436-443 - Hayit Greenspan, Rodney M. Goodman, Rama Chellappa:
Combined Neural Network and Rule-Based Framework for Probabilistic Pattern Recognition and Discovery. 444-451 - Ronen Basri, Shimon Ullman:
Linear Operator for Object Recognition. 452-459 - Nathan Intrator, Joshua I. Gold, Heinrich H. Bülthoff, Shimon Edelman:
3D Object Recognition Using Unsupervised Feature Extraction. 460-467
Optical Character Recognition
- Isabelle Guyon, Vladimir Vapnik, Bernhard E. Boser, Léon Bottou, Sara A. Solla:
Structural Risk Minimization for Character Recognition. 471-479 - Hans Peter Graf, Craig R. Nohl, Jan Ben:
Image Segmentation with Networks of Variable States. 480-487 - Ofer Matan, Christopher J. C. Burges, Yann LeCun, John S. Denker:
Multi-Digit Recognition Using a Space Displacement Neural Network. 488-495 - James D. Keeler, David E. Rumelhart:
A Self-Organizing Integrated Segmentation and Recognition Neural Net. 496-503 - Gale Martin, Mosfeq Rashid:
Recognizing Overlapping Hand-Printed Characters by Centered-Object Integrated Segmentation and Recognition. 504-511 - Geoffrey E. Hinton, Christopher K. I. Williams, Michael Revow:
Adaptive Elastic Models for Hand-Printed Character Recognition. 512-519
Control and Planning
- Tony J. Prescott, John E. W. Mayhew:
Obstacle Avoidance through Reinforcement Learning. 523-530 - Sebastian Thrun, Knut Möller:
Active Exploration in Dynamic Environments. 531-538 - Michael D. Lemmon:
Oscillatory Neural Fields for Globally Optimal Path Planning. 539-546 - Hiroaki Gomi, Mitsuo Kawato:
Recognition of Manipulated Objects by Motor Learning. 547-554 - Gary M. Scott, Jude W. Shavlik, W. Harmon Ray:
Refined PID Controllers Using Neural Networks. 555-562 - Carlos D. Brody:
Fast Learning with Predictive Forward Models. 563-570 - Andrew W. Moore:
Fast, Robust Adaptive Control by Learning only Forward Models. 571-578 - Patrice Y. Simard, Yann LeCun:
Reverse TDNN: An Architecture For Trajectory Generation. 579-588 - David DeMers, Kenneth Kreutz-Delgado:
Learning Global Direct Inverse Kinematics. 589-595 - Paul Dean, John E. W. Mayhew, Pat Langdon:
A Neural Net Model for Adaptive Control of Saccadic Accuracy by Primate Cerebellum and Brainstem. 595-602 - Thomas J. Anastasio:
Learning in the Vestibular System: Simulations of Vestibular Compensation Using Recurrent Back-Propagation. 603-610 - N. E. Berthier, Satinder P. Singh, Andrew G. Barto, James C. Houk:
A Cortico-Cerebellar Model that Learns to Generate Distributed Motor Commands to Control a Kinematic Arm. 611-618 - Ealan A. Henis, Tamar Flash:
A Computational Mechanism to Account for Averaged Modified Hand Trajectories. 619-626 - Menashe Dornay, Yoji Uno, Mitsuo Kawato, Ryoji Suzuki:
Simulation of Optimal Movements Using the Minimum-Muscle-Tension-Change Model. 627-634
Applications
- Marwan A. Jabri, Stephen Pickard, Philip Heng Wai Leong, Z. Chi, Barry Flower, Y. Xie:
ANN Board Classification for Heart Defibrillators. 637-644 - Armando Manduca, Paul Christy, Richard L. Ehman:
Neural Network Diagnosis of Avascular Necrosis from Magnetic Resonance Images. 645-650 - Rita Venturini, William W. Lytton, Terrence J. Sejnowski:
Neural Network Analysis of Event Related Potentials and Electroencephalogram Predicts Vigilance. 651-658 - Martin Röscheisen, Reimar Hofmann, Volker Tresp:
Neural Control for Rolling Mills: Incorporating Domain Theories to Overcome Data Deficiency. 659-666 - Padhraic Smyth, Jeff Mellstrom:
Fault Diagnosis of Antenna Pointing Systems Using Hybrid Neural Network and Signal Processing Models. 667-674 - Sylvie Thiria, Carlos Mejia, Fouad Badran, Michel Crépon:
Multimodular Architecture fir Remote Sensing Options. 675-682 - John E. Moody, Joachim Utans:
Principled Architecture Selection for Neural Networks: Application to Corporate Bond Rating Prediction. 683-690 - Sheri L. Gish, Mario Blaum:
Adaptive Development of Connectionist Decoders for Complex Error-Correcting Codes. 691-697 - Ah Chung Tsoi:
Application of Neural Network Methodology to the Modelling of the Yield Strength in a Steel Rolling Plate Mill. 698-705 - Donald T. Freeman:
Computer Recognition of Wave Location in Graphical Data by a Neural Network. 706-713 - Hilary Tunley:
A Neural Network for Motion Detection of Drift-Balanced Stimuli. 714-721 - Mark W. Goudreau, C. Lee Giles:
Neural Network Routing for Random Multistage Interconnection Networks. 722-729 - John C. Platt, Federico Faggin:
Networks for the Separation of Sources that Are Superimposed and Delayed. 730-737
Implementation
- Alice M. Chiang, Michael L. Chuang, Jeffrey R. LaFranchise:
CCD Neural Network Processors for Pattern Recognition. 741-747 - Charles F. Neugebauer, Amnon Yariv:
A Parallel Analog CCD/CMOS Signal Processor. 748-755 - Ronald G. Benson, Tobi Delbrück:
Direction Selective Silicon Retina that Uses Null Inhibition. 756-763 - Kwabena A. Boahen, Andreas G. Andreou:
A Contrast Sensitive Silicon Retina with Reciprocal Synapses. 764-772 - Eduard Säckinger, Bernhard E. Boser, Lawrence D. Jackel:
A Neurocomputer Board Based on the ANNA Neural Network Chip. 773-780 - Phil Kohn, Jeff A. Bilmes, Nelson Morgan, James Beck:
Software for ANN Training on a Ring Array Processor. 781-788 - David Blair Kirk, Kurt W. Fleischer, Lloyd Watts, Alan H. Barr:
Constrained Optimization Applied to the Parameter Setting Problem for Analog Circuits. 789-796 - John G. Harris:
Segmentation Circuits Using Constrained Optimization. 797-804 - Marc H. Cohen, Philippe O. Pouliquen, Andreas G. Andreou:
Analog LSI Implementation of an Auto-Adaptive Network for Real-Time Separation of Independent Signals. 805-812 - John Lazzaro:
Temporal Adaptation in a Silicon Auditory Nerve. 813-820 - Dana Z. Anderson, Claus Benkert, Verena Hebler, Ju-Seog Jang, Don Montgomery, Mark Saffman:
Optical Implementation of a Self-Organizing Feature Extractor. 821-828
Learning and Generalization
- Vladimir Vapnik:
Principles of Risk Minimization for Learning Theory. 831-838 - David J. C. MacKay:
Bayesian Model Comparison and Backprop Nets. 839-846 - John E. Moody:
The Effective Number of Parameters: An Analysis of Generalization and Regularization in Nonlinear Learning Systems. 847-854 - David Haussler, Michael J. Kearns, Manfred Opper, Robert E. Schapire:
Estimating Average-Case Learning Curves Using Bayesian, Statistical Physics and VC Dimension Methods. 855-862 - J. Stephen Judd:
Constant-Time Loading of Shallow 1-Dimensional Networks. 863-870 - Joshua Alspector, Anthony Jayakumar, Stephan Luna:
Experimental Evaluation of Learning in a Neural Microsystem. 871-878 - John Shawe-Taylor:
Threshold Network Learning in the Presence of Equivalences. 879-886 - Barak A. Pearlmutter:
Gradient Descent: Second Order Momentum and Saturating Error. 887-894 - Patrice Y. Simard, Bernard Victorri, Yann LeCun, John S. Denker:
Tangent Prop - A Formalism for Specifying Selected Invariances in an Adaptive Network. 895-903 - Alberto Bertoni, Paola Campadelli, Anna Morpurgo, Sandra Panizza:
Polynomial Uniform Convergence of Relative Frequencies to Probabilities. 904-911 - Yoav Freund, David Haussler:
Unsupervised Learning of Distributions of Binary Vectors Using 2-Layer Networks. 912-919 - Anthony Kuh, Thomas Petsche, Ronald L. Rivest:
Incrementally Learning Time-Varying Half Planes. 920-927 - Chuanyi Ji, Demetri Psaltis:
The VC-Dimension versus the Statistical Capacity of Multilayer Networks. 928-935 - Ying Zhao, Christopher G. Atkeson:
Some Approximation Properties of Projection Pursuit Learning Networks. 936-943 - Kai-Yeung Siu, Jehoshua Bruck:
Neural Computing with Small Weights. 944-949 - Anders Krogh, John A. Hertz:
A Simple Weight Decay Can Improve Generalization. 950-957 - Stephen M. Omohundro:
Best-First Model Merging for Dynamic Learning and Recognition. 958-965
Architectures and Algorithms
- Clayton McMillan, Michael Mozer, Paul Smolensky:
Rule Induction through Integrated Symbolic and Subsymbolic Processing. 969-976 - Geoffrey G. Towell, Jude W. Shavlik:
Interpretation of Artificial Neural Networks: Mapping Knowledge-Based Neural Networks into Rules. 977-984 - Michael I. Jordan, Robert A. Jacobs:
Hierarchies of Adaptive Experts. 985-992 - Steven J. Nowlan, Geoffrey E. Hinton:
Adaptive Soft Weight Tying using Gaussian Mixtures. 993-1000 - Paul W. Munro:
Repeat Until Bored: A Pattern Selection Strategy. 1001-1008 - Christian Darken, John E. Moody:
Towards Faster Stochastic Gradient Search. 1009-1016 - Nicol N. Schraudolph, Terrence J. Sejnowski:
Competitive Anti-Hebbian Learning of Invariants. 1017-1024 - Paul E. Stolorz:
Merging Constrained Optimisation with Deterministic Annealing to Solve Combinatorially Hard Problems. 1025-1032 - Petri Koistinen, Lasse Holmström:
Kernel Regression and Backpropagation Training With Noise. 1033-1039 - Robert C. Williamson, Peter L. Bartlett:
Splines, Rational Functions and Neural Networks. 1040-1047 - John Moody, Norman Yarvin:
Networks with Learned Unit Response Functions. 1048-1055 - Nicholas J. Redding, Tom Downs:
Learning in Feedforward Networks with Nonsmooth Functions. 1056-1063 - Terence D. Sanger, Richard S. Sutton, Christopher J. Matheus:
Iterative Construction of Sparse Polynomial Approximations. 1064-1071 - Mike Wynne-Jones:
Node Splitting: A Constructive Algorithm for Feed-Forward Neural Networks. 1072-1079 - Sowmya Ramachandran, Lorien Y. Pratt:
Information Measure Based Skeletonisation. 1080-1087 - David Rogers:
Data Analysis Using G/Splines. 1088-1095 - John S. Bridle, Anthony J. R. Heading, David J. C. MacKay:
Unsupervised Classifiers, Mutual Information and 'Phantom Targets'. 1096-1101 - Martin S. Glassman:
A Network of Localized Linear Discriminants. 1102-1109 - David J. Montana:
A Weighted Probabilistic Neural Network. 1110-1117 - Igor Grebert, David G. Stork, Ron Keesing, Steve Mims:
Network Generalization for Production: Learning and Producing Styled Letterforms. 1118-1124 - John B. Hampshire II, B. V. K. Vijaya Kumar:
Shooting Craps in Search of an Optimal Strategy for Training Connectionist Pattern Classifiers. 1125-1132 - Dietrich Wettschereck, Thomas G. Dietterich:
Improving the Performance of Radial Basis Function Networks by Learning Center Locations. 1133-1140 - Hans-Ulrich Bauer, Klaus Pawelzik, Theo Geisel:
A Topographic Product for the Optimization of Self-Organizing Feature Maps. 1141-1147
Performance Comparisions
- Jakob Bernasconi, Karl Gustafson:
Human and Machine 'Quick Modeling'. 1151-1158 - Jenq-Neng Hwang, Hang Li, Martin Mächler, R. Douglas Martin, Jim Schimert:
A Comparison of Projection Pursuit and Neural Network Regression Modeling. 1159-1166 - Leonard G. C. Hamey:
Benchmarking Feed-Forward Neural Networks: Models and Measures. 1167-1174
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