NIPS 1995: Denver, CO, USA

David S. Touretzky, Michael Mozer, Michael E. Hasselmo (Eds.): Advances in Neural Information Processing Systems 8, NIPS, Denver, CO, November 27-30, 1995. MIT Press 1996, ISBN 0-262-20107-0 BibTeX

@proceedings{DBLP:conf/nips/1995,
  editor    = {David S. Touretzky and
               Michael Mozer and
               Michael E. Hasselmo},
  title     = {Advances in Neural Information Processing Systems 8, NIPS, Denver,
               CO, November 27-30, 1995},
  booktitle = {NIPS},
  publisher = {MIT Press},
  year      = {1996},
  isbn      = {0-262-20107-0},
  bibsource = {DBLP, http://dblp.uni-trier.de}
}

Cognitive Science

Joshua B. Tenenbaum:
Learning the Structure of Similarity. 3-9
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Alexandre Pouget, Terrence J. Sejnowski:
A Model of Spatial Representations in Parietal Cortex Explains Hemineglect. 10-16
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Gale Martin:
Human Reading and the Curse of Dimensionality. 17-23
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Mark Craven, Jude W. Shavlik:
Extracting Tree-Structured Representations of Trained Networks. 24-30
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René Gourley:
Harmony Networks Do Not Work. 31-37
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Hiroyuki Nakahara, Kenji Doya:
Dynamics of Attention as Near Saddle-Node Bifurcation Behavior. 38-44
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Kevin J. Cherkauer, Jude W. Shavlik:
Rapid Quality Estimation of Neural Network Input Representations. 45-51
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Susan L. McCabe, Michael J. Denham:
A Model of Auditory Streaming. 52-58
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Neuroscience

A. David Redish, David S. Touretzky:
Modeling Interactions of the Rat's Place and Head Direction Systems. 61-67
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Wyeth Bair, Ehud Zohary, Christof Koch:
Correlated Neuronal Response: Time Scales and Mechanisms. 68-74
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Charles F. Stevens, Anthony M. Zador:
Information through a Spiking Neuron. 75-81
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Rasmus S. Petersen, John G. Taylor:
Reorganisation of Somatosensory Cortex after Tactile Training. 82-88
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Olivier J. M. D. Coenen, Terrence J. Sejnowski:
A Dynamical Moedl of Context Dependencies for the Vestibulo-Ocular Reflex. 89-95
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Samuel R. H. Joseph, David J. Willshaw:
The Role of Activity in Synaptic Competition at the Neuromuscular Junction. 96-102
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Charles F. Stevens, Anthony M. Zador:
When is an Integrate-and-fire Neuron like a Poisson Neuron? 103-109
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Christopher L. Fry:
How Perception Guides Production in Birdsong Learning. 110-116
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Amir A. Handzel, Tamar Flash:
The Geometry of Eye Rotations and Listing's Law. 117-123
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Richard Kempter, Wulfram Gerstner, J. Leo van Hemmen, Hermann Wagner:
Temporal coding in the sub-millisecond range: Model of barn owl auditory pathway. 124-130
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Michael E. Hasselmo, Milos Cekic:
Cholinergic suppression of transmission may allow combined associative memory function and self-organization in the neocortex. 131-137
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Andrew G. Barto, James C. Houk:
A Predictive Switching Model of Cerebellar Movement Control. 138-144
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Scott Makeig, Anthony J. Bell, Tzyy-Ping Jung, Terrence J. Sejnowski:
Independent Component Analysis of Electroencephalographic Data. 145-151
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Hugh T. Blair:
Simualtion of a Thalamocortical Circuit for Computing Directional Heading in the Rat. 152-158
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S. Yasui, T. Furukawa, M. Yamada, T. Saito:
Plasticity of Center-Surround Opponent Receptive Fields in Real and Artificial Neural Systems of Vision. 159-165
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Theory

Jonathan Baxter:
Learning Model Bias. 169-175
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Shun-ichi Amari, Noboru Murata, Klaus-Robert Müller, M. Finke, Howard Hua Yang:
Statistical Theory of Overtraining - Is Cross-Validation Asymptotically Effective? 176-182
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Michael J. Kearns:
A Bound on the Error of Cross Validation Using the Approximation and Estimation Rates, with Consequences for the Training-Test Split. 183-189
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Peter Sollich, Anders Krogh:
Learning with ensembles: How overfitting can be useful. 190-196
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Pascal Koiran, Eduardo D. Sontag:
Neural Networks with Quadratic VC Dimension. 197-203
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Bhaskar DasGupta, Eduardo D. Sontag:
Sample Complexity for Learning Recurrent Perceptron Mappings. 204-210
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Wolfgang Maass:
On the Computational Power of Noisy Spiking Neurons. 211-217
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Siegfried Bös:
A Realizable Learning Task which Exhibits Overfitting. 218-224
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Stefan M. Rüger:
Stable Dynamic Parameter Adaption. 225-231
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Robert R. Snapp, Tong Xu:
Estimating the Bayes Risk from Sample Data. 232-238
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Visakan Kadirkamanathan, Maha Kadirkamanathan:
Recursive Estimation of Dynamic Modular RBF Networks. 239-245
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Vasken Bohossian, Jehoshua Bruck:
On Neural Networks with Minimal Weights. 246-252
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Anthony C. C. Coolen, S. N. Laughton, D. Sherrington:
Modern Analytic Techniques to Solve the Dynamics of Recuurent Neural Networks. 253-259
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Yishay Mansour, Sigal Sahar:
Implementation Issues in the Fourier Transform Algorithm. 260-266
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John Shawe-Taylor, Jieyu Zhao:
Generalisation of A Class of Continuous Neural Networks. 267-273
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James W. Howse, Chaouki T. Abdallah, Gregory L. Heileman:
Gradient and Hamiltonian Dynamics Applied to Learning in Neural Networks. 274-280
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Michael DeWeese:
Optimization Principles for the Neural Code. 281-287
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Mario Marchand, Saeed Hadjifaradji:
Strong Unimodality and Exact Learning of Constant Depth µ-Perceptron Networks. 288-294
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Kenji Fukumizu:
Active Learning in Multilayer Perceptrons. 295-301
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David Saad, Sara A. Solla:
Dynamics of On-Line Gradient Descent Learning for Multilayer Neural Networks. 302-308
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David P. Helmbold, Jyrki Kivinen, Manfred K. Warmuth:
Worst-case Loss Bounds for Single Neurons. 309-315
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Peter Auer, Mark Herbster, Manfred K. Warmuth:
Exponentially many local minima for single neurons. 316-322
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Ansgar H. L. West, David Saad:
Adaptive Back-Propagation in On-Line Learning of Multilayer Networks. 323-329
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Geoffrey J. Goodhill, Steven Finch, Terrence J. Sejnowski:
Optimizing Cortical Mappings. 330-336
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Anke Meyer-Bäse:
Quadratic-Type Lyapunov Functions for Competitive Neural Networks with Different Time-Scales. 337-343
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Adam Kowalczyk, Jacek Szymanski, Peter L. Bartlett, Robert C. Williamson:
Examples of learning curves from a modified VC-formalism. 344-350
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Steve R. Waterhouse, David MacKay, Anthony J. Robinson:
Bayesian Methods for Mixtures of Experts. 351-357
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Serguei A. Semenov, Irina B. Shuvalova:
Some results on convergent unlearning algorithm. 358-364
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Robert H. Dodier:
Geometry of Early Stopping in Linear Networks. 365-371
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Xin Wang, Arun K. Jagota, Fernanda Botelho, Max H. Garzon:
Absence of Cycles in Symmetric Neural Networks. 372-378
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Algorithms and Architectures

Yoram Singer:
Adaptive Mixture of Probabilistic Transducers. 381-387
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Yochai Konig, Hervé Bourlard, Nelson Morgan:
REMAP: Recursive Estimation and Maximization of A Posteriori Probabilities - Application to Transition-Based Connectionist Speech Recognition. 388-394
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Yoshua Bengio, Francois Gingras:
Recurrent Neural Networks for Missing or Asynchronous Data. 395-401
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Stephen M. Omohundro:
Family Discovery. 402-408
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Trevor Hastie, Robert Tibshirani:
Discriminant Adaptive Nearest Neighbor Classification and Regression. 409-415
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Marcelo Blatt, Shai Wiseman, Eytan Domany:
Clustering data through an analogy to the Potts model. 416-422
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Atsushi Sato, Keiji Yamada:
Generalized Learning Vector Quantization. 423-429
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Ari Juels, Martin Wattenberg:
Stochastic Hillclimbing as a Baseline Mathod for Evaluating Genetic Algorithms. 430-436
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Lucas C. Parra:
Symplectic Nonlinear Component Analysis. 437-443
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Lei Xu:
A Unified Learning Scheme: Bayesian-Kullback Ying-Yang Machines. 444-450
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Pierre Baldi, Kurt Hornik:
Universal Approximnation and Learning of Trajectories Using Oscillators. 451-457
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Lizhong Wu, John E. Moody:
A Smoothing Regularizer for Recurrent Neural Networks. 458-464
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Christopher M. Bishop, Markus Svensén, Christopher K. I. Williams:
EM Optimization of Latent-Variables Density Models. 465-471
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Zoubin Ghahramani, Michael I. Jordan:
Factorial Hidden Markov Models. 472-478
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Harris Drucker, Corinna Cortes:
Boosting Decision Trees. 479-485
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Lawrence K. Saul, Michael I. Jordan:
Exploiting Tractable Substructures in Intractable Networks. 486-492
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Salah El Hihi, Yoshua Bengio:
Hierarchical Recurrent Neural Networks for Long-Term Dependencies. 493-499
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Reimar Hofmann, Volker Tresp:
Discovering Structure in Continuous Variables Using Bayesian Networks. 500-506
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Geoffrey E. Hinton, Michael Revow:
Using Pairs of Data-Points to Define Splits for Decision Trees. 507-513
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Christopher K. I. Williams, Carl Edward Rasmussen:
Gaussian Processes for Regression. 514-520
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Morten With Pedersen, Lars Kai Hansen, Jan Larsen:
Pruning with generalization based weight saliencies: gamma-OBD, gamma-OBS. 521-527
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Tommi Jaakkola, Lawrence K. Saul, Michael I. Jordan:
Fast Learning by Bounding Likelihoods in Sigmoid Type Belief Networks. 528-534
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David W. Opitz, Jude W. Shavlik:
Generating Accurate and Diverse Members of a Neural-Network Ensemble. 535-541
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Dirk Ormoneit, Volker Tresp:
Improved Gaussian Mixture Density Estimates Using Bayesian Penalty Terms and Network Averaging. 542-548
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Thomas P. Rebotier, Jeffrey L. Elman:
Explorations with the Dynamic Wave Model. 549-555
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Gary William Flake:
The Capacity of a Bump. 556-562
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Nicol N. Schraudolph, Terrence J. Sejnowski:
Tempering Backpropagation Networks: Not All Weights are Created Equal. 563-569
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Jörg A. Walter, Helge Ritter:
Investment Learning with Hierarchical PSOMs. 570-576
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Tsungnan Lin, Bill G. Horne, Peter Tiño, C. Lee Giles:
Learning long-term dependencies is not as difficult with NARX networks. 577-583
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Steve R. Waterhouse, Anthony J. Robinson:
Constructive Algorithms for Hierarchical Mixtures of Experts. 584-590
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David J. Miller, Ajit V. Rao, Kenneth Rose, Allen Gersho:
An Information-theoretic Learning Algorithm for Neural Network Classification. 591-597
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Carl Edward Rasmussen:
A Practical Monte Carlo Implementation of Bayesian Learning. 598-604
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Stefan Schaal, Christopher G. Atkeson:
From Isolation to Cooperation: An Alternative View of a System of Experts. 605-611
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Stefan C. Kremer:
Finite State Automata that Recurrent Cascade-Correlation Cannot Represent. 612-618
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John Wawrzynek, Krste Asanovic, Brian Kingsbury, James Beck, David Johnson, Nelson Morgan:
SPERT-II: A Vector Microprocessor System and its Application to Large Problems in Backpropagation Training. 619-625
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Steven Gold, Anand Rangarajan:
Softassign versus Softmax: Benchmarks in Combinatorial Optimization. 626-632
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Dimitris I. Tsioutsias, Eric Mjolsness:
A Mulitscale Attentional Framework for Relaxation Neural Networks. 633-639
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Sebastian Thrun:
Is Learning The n-th Thing Any Easier Than Learning The First? 640-646
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Geoffrey G. Towell:
Using Unlabeled Data for Supervised Learning. 647-653
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Jeffrey C. Jackson, Mark Craven:
Learning Sparse Perceptrons. 654-660
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Brendan J. Frey, Geoffrey E. Hinton, Peter Dayan:
Does the Wake-sleep Algorithm Produce Good Density Estimators? 661-667
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Implementations

André van Schaik, Eric Fragnière, Eric A. Vittoz:
Improved Silicon Cochlea using Compatible Lateral Bipolar Transistors. 671-677
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Shih-Chii Liu, Kwabena Boahen:
Adaptive Retina with Center-Surround Receptive Field. 678-684
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Tadashi Shibata, Tsutomu Nakai, Tatsuo Morimoto, Ryu Kaihara, Takeo Yamashita, Tadahiro Ohmi:
Neuron-MOS Temporal Winner Search Hardware for Fully-Parallel Data Processing. 685-691
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R. Timothy Edwards, Gert Cauwenberghs:
Analog VLSI Processor Implementing the Continuous Wavelet Transform. 692-698
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John Lazzaro, John Wawrzynek:
Silicon Models for Auditory Scene Analysis. 699-705
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Ralph Etienne-Cummings, Jan Van der Spiegel, Paul Mueller:
VLSI Model of Primate Visual Smooth Pursuit. 706-712
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Steven Rehfuss, Dan W. Hammerstrom:
Model Matching and SFMD Computation. 713-719
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Giacomo Indiveri, Jörg Kramer, Christof Koch:
Parallel analog VLSI architectures for computation of heading direction and time-to-contact. 720-726
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Speech and Signal Processing

Leslie S. Smith:
Onset-based Sound Segmentation. 729-735
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Yoonsuck Choe, Joseph Sirosh, Risto Miikkulainen:
Laterally Interconnected Self-Organizing Maps in Hand-Written Digit Recognition. 736-742
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Andrew W. Senior, Anthony J. Robinson:
Forward-backward retraining of recurrent neural networks. 743-749
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Dan Kershaw, Anthony J. Robinson, Mike Hochberg:
Context-Dependent Classes in a Hybrid Recurrent Network-HMM Speech Recognition System. 750-756
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Shun-ichi Amari, Andrzej Cichocki, Howard Hua Yang:
A New Learning Algorithm for Blind Signal Separation. 757-763
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Bernard Lemarié, Michel Gilloux, Manuel Leroux:
Handwritten Word Recognition using Contextual Hybrid Radial Basis Function Network/Hidden Markov Models. 764-770
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Ethem Alpaydin:
Selective Attention for Handwritten Digit Recognition. 771-777
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Alexander Shustorovich, Christopher W. Thrasher:
Kodak Imagelink^TM OCR Alphanumeric Handprint Module. 778-784
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Steve Lawrence, Ah Chung Tsoi, Andrew D. Back:
The Gamma MLP for Speech Phoneme Recognition. 785-791
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Vision

Suguna Pappu, Steven Gold, Anand Rangarajan:
A Framework for Non-rigid Matching and Correspondence. 795-801
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Ernst Niebur, Christof Koch:
Control of Selective Visual Attention: Modeling the Where Pathway. 802-808
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William R. Softky:
Unsupervised Pixel-prediction. 809-815
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Jonathan A. Marshall, Richard K. Alley, Robert S. Hubbard:
Learning to Predict Visibility and Invisibility from Occlusion Events. 816-822
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Marian Stewart Bartlett, Paul A. Viola, Terrence J. Sejnowski, Beatrice A. Golomb, Jan Larsen, Joseph C. Hager, Paul Ekman:
Classifying Facial Action. 823-829
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Rajesh P. N. Rao, Gregory J. Zelinsky, Mary M. Hayhoe, Dana H. Ballard:
Modeling Saccadic Targeting in Visual Search. 830-836
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Alexander Grunewald:
A model of transparent motion and non-transparent motion aftereffects. 837-843
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Luiz Pessoa, William D. Ross:
A Neural Network Model of 3-D Lightness Perception. 844-850
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Paul A. Viola, Nicol N. Schraudolph, Terrence J. Sejnowski:
Empirical Entropy Manipulation for Real-World Problems. 851-857
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Trevor Darrell, Alex Pentland:
Active Gesture Recognition using Learned Visual Attention. 858-864
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Bartlett W. Mel:
SEEMORE: A View-Based Approach to 3-D Object Recognition Using Multiple Visual Cues. 865-871
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Applications

Henry A. Rowley, Shumeet Baluja, Takeo Kanade:
Human Face Detection in Visual Scenes. 875-881
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Bambang Parmanto, Paul W. Munro, Howard R. Doyle:
Improving Committee Diagnosis with Resampling Techniques. 882-888
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Yoky Matsuoka:
Primitive Manipulation Learning with Connectionism. 889-895
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Peter Stone, Manuela M. Veloso:
Beating a Defender in Robotic Soccer: Memory-Based Learning of a Continuous Function. 896-902
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Enno Littmann, Andrea Drees, Helge Ritter:
Visual gesture-based robot guidance with a modular neural system. 903-909
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Marwan A. Jabri, Raymond J. Wang:
A Novel Channel Selection System in Cochlear Implants Using Artificial Neural Network. 910-916
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Anders Krogh, Soren Kamaric Riis:
Prediction of Beta Sheets in Proteins. 917-923
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Thomas Petsche, Angelo Marcantonio, Christian Darken, Stephen Jose Hanson, Gary M. Kuhn, N. Iwan Santoso:
A Neural Network Autoassociator for Induction Motor Failure Prediction. 924-930
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Scott Makeig, Tzyy-Ping Jung, Terrence J. Sejnowski:
Using Feedforward Neural Networks to Monitor Alertness from Changes in EEG Correlation and Coherence. 931-937
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John C. Platt, Timothy P. Allen:
A Neural Network Classifier for the I100 OCR Chip. 938-944
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Samuel P. M. Choi, Dit-Yan Yeung:
Predictive Q-Routing: A Memory-based Reinforcement Learning Approach to Adaptive Traffic Control. 945-951
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Ralph Neuneier:
Optimal Asset Allocation using Adaptive Dynamic Programming. 952-958
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Rich Caruana, Shumeet Baluja, Tom M. Mitchell:
Using the Future to Sort Out the Present: Rankprop and Multitask Learning for Medical Risk Evaluation. 959-965
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Asriel E. Levin:
Stock Selection via Nonlinear Multi-Factor Models. 966-972
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Peter K. Campbell, Michael Dale, Herman L. Ferrá, Adam Kowalczyk:
Experiments with Neural Networks for Real Time Implementation of Control. 973-979
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Alistair Ferguson, Theo Sabisch, Paul Kaye, Laurence C. Dixon, Hamid Bolouri:
High-Speed Airborne Particle Monitoring Using Artificial Neural Networks. 980-986
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Control

Jun Tani, Naohiro Fukumura:
A Dynamical Systems Approach for a Learnable Autonomous Robot. 989-995
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Jefferson A. Coelho Jr., R. Sitaraman, Roderic A. Grupen:
Parallel Optimization of Motion Controllers via Policy Iteration. 996-1002
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Marina Meila, Michael I. Jordan:
Learning Fine Motion by Markov Mixtures of Experts. 1003-1009
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Ssu-Hsin Yu, Anuradha M. Annaswamy:
Neural Control for Nonlinear Dynamic Systems. 1010-1016
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Robert H. Crites, Andrew G. Barto:
Improving Elevator Performance Using Reinforcement Learning. 1017-1023
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Wei Zhang, Thomas G. Dietterich:
High-Performance Job-Shop Scheduling With A Time-Delay TD-lambda Network. 1024-1030
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Geoffrey B. Jackson, Alan F. Murray:
Competence Acquisition in an Autonomous Mobile Robot using Hardware Neural Techniques. 1031-1037
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Richard S. Sutton:
Generalization in Reinforcement Learning: Successful Examples Using Sparse Coarse Coding. 1038-1044
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Benjamin Van Roy, John N. Tsitsiklis:
Stable LInear Approximations to Dynamic Programming for Stochastic Control Problems with Local Transitions. 1045-1051
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Geoffrey J. Gordon:
Stable Fitted Reinforcement Learning. 1052-1058
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Peter Dayan, Satinder P. Singh:
Improving Policies without Measuring Merits. 1059-1065
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Andrew W. Moore, Jeff G. Schneider:
Memory-based Stochastic Optimization. 1066-1072
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Kenji Doya:
Temporal Difference Learning in Continuous Time and Space. 1073-1079
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Philip N. Sabes, Michael I. Jordan:
Reinforcement Learning by Probability Matching. 1080-1086
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