NIPS 1992:
Denver,
CO,
USA
Stephen Jose Hanson, Jack D. Cowan, C. Lee Giles (Eds.):
Advances in Neural Information Processing Systems 5, [NIPS Conference, Denver, Colorado, USA, November 30 - December 3, 1992].
Morgan Kaufmann 1993, ISBN 1-55860-274-7 BibTeX
@proceedings{DBLP:conf/nips/1992,
editor = {Stephen Jose Hanson and
Jack D. Cowan and
C. Lee Giles},
title = {Advances in Neural Information Processing Systems 5, [NIPS Conference,
Denver, Colorado, USA, November 30 - December 3, 1992]},
booktitle = {NIPS},
publisher = {Morgan Kaufmann},
year = {1993},
isbn = {1-55860-274-7},
bibsource = {DBLP, http://dblp.uni-trier.de}
}
Part 1:
Learning and Generalization
- Nathan Intrator:
On the Use of Projection Pursuit Constraints for Training Neural Networks.
3-10
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- Andreas Stolcke, Stephen M. Omohundro:
Hidden Markov Model} Induction by Bayesian Model Merging.
11-18
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- Kai-Yeung Siu, Vwani P. Roychowdhury, Thomas Kailath:
Computing with Almost Optimal Size Neural Networks.
19-26
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- Janet Wiles, Mark Ollila:
Intersecting Regions: The Key to Combinatorial Structure in Hidden Unit Space.
27-33
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- Tony Plate:
Holographic Recurrent Networks.
34-41
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- Harris Drucker, Robert E. Schapire, Patrice Simard:
Improving Performance in Neural Networks Using a Boosting Algorithm.
42-49
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- Patrice Simard, Yann LeCun, John S. Denker:
Efficient Pattern Recognition Using a New Transformation Distance.
50-58
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- Kai-Yeung Siu, Vwani P. Roychowdhury:
Optimal Depth Neural Networks for Multiplication and Related Problems.
59-64
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- Sreerupa Das, C. Lee Giles, Guo-Zheng Sun:
Using Prior Knowledge in a {NNPDA} to Learn Context-Free Languages.
65-72
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- Yaser S. Abu-Mostafa:
A Method for Learning From Hints.
73-80
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- Charles W. Anderson:
Q-Learning with Hidden-Unit Restarting.
81-88
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- J. Stephen Judd, Paul W. Munro:
Nets with Unreliable Hidden Nodes Learn Error-Correcting Codes.
89-96
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Part 2:
Architectures and Algorithms
- Richard K. Belew:
Interposing an Ontogenetic Model Between Genetic Algorithms and Neural Networks.
99-106
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- J. Jeffrey Mahoney, Raymond J. Mooney:
Combining Neural and Symbolic Learning to Revise Probabilistic Rule Bases.
107-114
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- Mark B. Ring:
Learning Sequential Tasks by Incrementally Adding Higher Orders.
115-122
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- Bernd Fritzke:
Kohonen Feature Maps and Growing Cell Structures - a Performance Comparison.
123-130
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- Brian V. Bonnlander, Michael Mozer:
Metamorphosis Networks: An Alternative to Constructive Models.
131-138
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- Eric I. Chang, Richard Lippmann:
A Boundary Hunting Radial Basis Function Classifier which Allocates Centers Constructively.
139-146
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- Isabelle Guyon, Bernhard E. Boser, Vladimir Vapnik:
Automatic Capacity Tuning of Very Large VC-Dimension Classifiers.
147-155
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- Yann LeCun, Patrice Simard, Barak A. Pearlmutter:
Automatic Learning Rate Maximization in Large Adaptive Machines.
156-163
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- Babak Hassibi, David G. Stork:
Second Order Derivatives for Network Pruning: Optimal Brain Surgeon.
164-171
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- Richard S. Zemel, Christopher K. I. Williams, Michael Mozer:
Directional-Unit Boltzmann Machines.
172-179
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- Guo-Zheng Sun, Hsing-Hen Chen, Yee-Chun Lee:
Time Warping Invariant Neural Networks.
180-187
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- Enno Littmann, Helge Ritter:
Generalization Abilities of Cascade Network Architecture.
188-195
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- Gerhard Paass:
Assessing and Improving Neural Network Predictions by the Bootstrap Algorithm.
196-203
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- Lorien Y. Pratt:
Discriminability-Based Transfer between Neural Networks.
204-211
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- Barry Flower, Marwan A. Jabri:
Summed Weight Neuron Perturbation: An O(N) Improvement Over Weight Perturbation.
212-219
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- Virginia R. de Sa, Dana H. Ballard:
A Note on Learning Vector Quantization.
220-227
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- William Finnoff, Ferdinand Hergert, Hans-Georg Zimmermann:
Extended Regularization Methods for Nonconvergent Model Selection.
228-235
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- Bill Baird, Todd Troyer, Frank H. Eeckman:
Synchronization and Grammatical Inference in an Oscillating Elman Net.
236-243
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- Gert Cauwenberghs:
A Fast Stochastic Error-Descent Algorithm for Supervised Learning and Optimization.
244-251
Electronic Edition (link) BibTeX
Part 3:
Control,
Navigation,
and Planning
Part 4:
Visual Processing
- Suzanna Becker:
Learning to Categorize Objects Using Temporal Coherence.
361-368
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- Steven J. Nowlan, Terrence J. Sejnowski:
Filter Selection Model for Generating Visual Motion Signals.
369-376
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- Edward Stern, Ad Aertsen, Eilon Vaadia, Shaul Hochstein:
Stimulus Encoding by Multidimensional Receptive Fields in Single Cells and Cell Populations in V1 of Awake Monkey.
377-384
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- Suthep Madarasmi, Daniel Kersten, Ting-Chuen Pong:
The Computation of Stereo Disparity for Transparent and for Opaque Surfaces.
385-392
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- Subutai Ahmad, Volker Tresp:
Some Solutions to the Missing Feature Problem in Vision.
393-400
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- Joachim Utans, Gene Gindi:
Improving Convergence in Hierarchical Matching Networks for Object Recognition.
401-408
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- Carlos D. Brody:
A Model of Feedback to the Lateral Geniculate Nucleus.
409-416
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- Kevin E. Martin, Jonathan A. Marshall:
Unsmearing Visual Motion: Development of Long-Range Horizontal Intrinsic Connections.
417-424
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- Hayit Greenspan, Rodney M. Goodman:
Remote Sensing Image Analysis via a Texture Classification Neural Network.
425-432
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- Markus Lappe, Josef P. Rauschecker:
Computation of Heading Direction from Optic Flow in Visual Cortex.
433-440
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- Gale Martin, Mosfeq Rashid, David Chapman, James A. Pittman:
Learning to See Where and What: Training a Net to Make Saccades and Recognize Handwritten Characters.
441-447
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Part 5:
Stochastic Learning and Analysis
- Todd K. Leen, John E. Moody:
Weight Space Probability Densities in Stochastic Learning: I. Dynamics and Equilibria.
451-458
Electronic Edition (link) BibTeX
- William Finnoff:
Diffusion Approximations for the Constant Step Size Backpropagation Algorithm and Resistance to Local Minima.
459-466
Electronic Edition (link) BibTeX
- Lei Xu, Alan L. Yuille:
Self-Organizing Rules for Robust Principal Component Analysis.
467-474
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- Radford M. Neal:
Bayesian Learning via Stochastic Dynamics.
475-482
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- Yoav Freund, H. Sebastian Seung, Eli Shamir, Naftali Tishby:
Information, Prediction, and Query by Committee.
483-490
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- Alan F. Murray, Peter J. Edwards:
Synaptic Weight Noise During MLP Learning Enhances Fault-Tolerance, Generalization and Learning Trajectory.
491-498
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- Nicol N. Schraudolph, Terrence J. Sejnowski:
Unsupervised Discrimination of Clustered Data via Optimization of Binary Information Gain.
499-506
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- Genevieve B. Orr, Todd K. Leen:
Weight Space Probability Densities in Stochastic Learning: II. Transients and Basin Hopping Times.
507-514
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- Satoru Shiono, Satoshi Yamada, Michio Nakashima, Kenji Matsumoto:
Information Theoretic Analysis of Connection Structure from Spike Trains.
515-522
Electronic Edition (link) BibTeX
- Holm Schwarze, John A. Hertz:
Statistical Mechanics of Learning in a Large Committee Machine.
523-530
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- John W. Miller, Rodney M. Goodman:
Probability Estimator from a Database Using a Gibbs Energy Model.
531-538
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- David Wolpert:
On the Use of Evidence in Neural Networks.
539-546
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Part 6:
Network Dynamics and Chaos
Part 7:
Theory and Analysis
Part 8:
Speech and Signal Processing
- Michael Cohen, Horacio Franco, Nelson Morgan, David E. Rumelhart, Victor Abrash:
Context-Dependent Multiple Distribution Phonetic Modeling with MLPs.
649-657
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- Makoto Hirayama, Eric Vatikiotis-Bateson, Kiyoshi Honda, Yasuharu Koike, Mitsuo Kawato:
Physiologically Based Speech Synthesis.
658-665
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- Weimin Liu, Andreas G. Andreou, Moise H. Goldstein Jr.:
Analog Cochlear Model for Multiresolution Speech Analysis.
666-673
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- Wei-Tsih Lee, John C. Pearson:
A Hybrid Linear/Nonlinear Approach to Channel Equalization Problems.
674-681
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- Yochai Konig, Nelson Morgan, Chuck Wooters, Victor Abrash, Michael Cohen, Horacio Franco:
Modeling Consistency in a Speaker Independent Continuous Speech Recognition System.
682-687
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- José Carlos Príncipe, Abir Zahalka:
Transient Signal Detection with Neural Networks: The Search for the Desired Signal.
688-695
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- Joe Tebelskis, Alex Waibel:
Performance Through Consistency: MS-TDNN's for Large Vocabulary Continuous Speech Recognition.
696-703
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- George Zavaliagkos, Ying Zhao, Richard M. Schwartz, John Makhoul:
A Hybrid Neural Net System for State-of-the-Art Continuous Speech Recognition.
704-711
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- Hermann Hild, Alex Waibel:
Connected Letter Recognition with a Multi-State Time Delay Neural Network.
712-719
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Part 9:
Applications
- Markus Schenkel, H. Weissman, Isabelle Guyon, C. Nohl, Donnie Henderson:
Recognition-Based Segmentation of On-Line Hand-Printed Words.
723-730
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- Esther Levin, Roberto Pieraccini:
Planar Hidden Markov Modeling: From Speech to Optical Character Recognition.
731-738
Electronic Edition (link) BibTeX
- Jen-Lun Yuan, Terrence Fine:
Forecasting Demand for Electric Power.
739-746
Electronic Edition (link) BibTeX
- Pierre Baldi, Yves Chauvin, Tim Hunkapiller, Marcella A. McClure:
Hidden Markov Models in Molecular Biology: New Algorithms and Applications.
747-754
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- Charles R. Rosenberg, Jacob Erel, Henri Atlan:
A Neural Network that Learns to Interpret Myocardial Planar Thallium Scintigrams.
755-762
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Part 10:
Implementations
- Janeen Anderson, John C. Platt, David Kirk:
An Analog VLSI Chip for Radial Basis Functions.
765-772
Electronic Edition (link) BibTeX
- Stephen Churcher, Donald J. Baxter, Alister Hamilton, Alan F. Murray, H. Martin Reekie:
Generic Analog Neural Computation - The Epsilon Chip.
773-780
Electronic Edition (link) BibTeX
- Rahul Sarpeshkar, Wyeth Bair, Christof Koch:
Visual Motion Computation in Analog VLSI Using Pulses.
781-788
Electronic Edition (link) BibTeX
- David B. Kirch, Douglas Kerns, Kurt W. Fleischer, Alan H. Barr:
Analog VLSI Implementation of Gradient Descent.
789-796
Electronic Edition (link) BibTeX
- Alexander Linden, Thomas Sudbrak, Christoph Tietz, F. Weber:
An Object-Oriented Framework for the Simulation of Neural Networks.
797-804
Electronic Edition (link) BibTeX
- Eros Pasero, Riccardo Zecchina:
Attractor Neural Networks with Local Inhibition: From Statistical Physics to a Digitial Programmable Integrated Circuit.
805-812
Electronic Edition (link) BibTeX
- Sylvie Renaud-Le Masson, Gwendal Le Masson, Eve Marder, L. F. Abbott:
Hybrid Circuits of Interacting Computer Model and Biological Neurons.
813-819
Electronic Edition (link) BibTeX
- John Lazzaro, John Wawrzynek, Misha Mahowald, Massimo Sivilotti, Dave Gillespie:
Silicon Auditory Processors as Computer Peripherals.
820-827
Electronic Edition (link) BibTeX
- Christof Koch, Binnal Mathur, Shih-Chii Liu, John G. Harris, Jin Luo, Massimo Sivilotti:
Object-Based Analog VLSI Vision Circuits.
828-835
Electronic Edition (link) BibTeX
- Joshua Alspector, Ronny Meir, B. Yuhas, Anthony Jayakumar, D. Lippe:
A Parallel Gradient Descent Method for Learning in Analog VLSI Neural Networks.
836-844
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Part 11:
Cognitive Science
Part 12:
Computational and Theoretical Neurobiology
- Kenji Doya, Mary E. T. Boyle, Allen I. Selverston:
Maaping Between Neural and Physical Activities of the Lobster Gastric Mill.
913-920
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- Mark E. Nelson:
A Neural Model of Descending Gain Control in the Electrosensory System.
921-928
Electronic Edition (link) BibTeX
- Neil Burgess, John O'Keefe, Michael Recce:
Using Hippocampal `Plane Cells' for Navigation, Exploiting Phase Coding.
929-936
Electronic Edition (link) BibTeX
- Mark A. Gluck, Catherine Myers:
Adaptive Stimulus Representations: A Computational Theory of Hippocampal-Region Functions.
937-944
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- Itay Gat, Naftali Tishby:
Statistical Modeling of Cell Assemblies Activities in Associative Cortex of Behaving Monkeys.
945-952
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- Ralph Linsker:
Deriving Receptive Fields Using an Optimal Encoding Criterion.
953-960
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- Olivier J. M. D. Coenen, Terrence J. Sejnowski, Stephen G. Lisberger:
Biologically Plausible Local Learning Rules for the Adaptation of the Vestibulo-Ocular Reflex.
961-968
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- P. Read Montague, Peter Dayan, Steven J. Nowlan, Terrence J. Sejnowski:
Using Aperiodic Reinforcement for Directed Self-Organization During Development.
969-976
Electronic Edition (link) BibTeX
- Klaus Pawelzik, Hans-Ulrich Bauer, J. Deppisch, Theo Geisel:
How Oscillatory Neuronal Responses Reflect Bistability and Switching of the Hidden Assembly Dynamics.
977-984
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- Geoffrey J. Goodhill:
Topography and Ocular Dominance with Positive Correlations.
985-992
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- Frank Moss, André Longtin:
Statistical and Dynamical Interpretation of ISIH Data from Periodically Stimulated Sensory Neurons.
993-1000
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- John G. Milton, Po Hsiang Chu, Jack D. Cowan:
Spiral Waves in Integrate-and-Fire Neural Networks.
1001-1006
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- Lance C. Walton, David L. Bisset:
Parametrizing Feature Sensitive Cell Formation in Linsker Networks in the Auditory System.
1007-1013
Electronic Edition (link) BibTeX
- Lina Massone:
A Recurrent Neural Network for Generation of Occular Saccades.
1014-1021
Electronic Edition (link) BibTeX
- Christiane Linster, David Marsan, Claudine Masson, Michel Kerszberg, Gérard Dreyfus, Léon Personnaz:
A Formal Model of the Insect Olfactory Macroglomerulus: Simulations and Analytic Results.
1022-1029
Electronic Edition (link) BibTeX
- William E. Skaggs, Bruce L. McNaughton, Katalin M. Gothard:
An Information-Theoretic Approach to Deciphering the Hippocampal Code.
1030-1037
Electronic Edition (link) BibTeX
Copyright © Sat May 16 23:31:29 2009
by Michael Ley (ley@uni-trier.de)
