Advances in Neural Information Processing Systems 5 (NIPS 1992)

• Parameterising Feature Sensitive Cell Formation in Linsker Networks in the Auditory System Lance Walton, David Bisset
• Learning Spatio-Temporal Planning from a Dynamic Programming Teacher: Feed-Forward Neurocontrol for Moving Obstacle Avoidance Gerald Fahner, Rolf Eckmiller
• Hidden Markov Models in Molecular Biology: New Algorithms and Applications Pierre Baldi, Yves Chauvin, Tim Hunkapiller, Marcella McClure
• Statistical and Dynamical Interpretation of ISIH Data from Periodically Stimulated Sensory Neurons John K. Douglass, Frank Moss, André Longtin
• Spiral Waves in Integrate-and-Fire Neural Networks John Milton, Po Chu, Jack Cowan
• Adaptive Stimulus Representations: A Computational Theory of Hippocampal-Region Function Mark Gluck, Catherine E. Myers
• Computing with Almost Optimal Size Neural Networks Kai-Yeung Siu, Vwani Roychowdhury, Thomas Kailath
• Q-Learning with Hidden-Unit Restarting Charles Anderson
• Synaptic Weight Noise During MLP Learning Enhances Fault-Tolerance, Generalization and Learning Trajectory Alan Murray, Peter Edwards
• Rational Parametrizations of Neural Networks Uwe Helmke, Robert C. Williamson
• Directional-Unit Boltzmann Machines Richard Zemel, Christopher Williams, Michael C. Mozer
• Stimulus Encoding by Multidimensional Receptive Fields in Single Cells and Cell Populations in V1 of Awake Monkey Edward Stern, Ad Aertsen, Eilon Vaadia, Shaul Hochstein
• On the Use of Projection Pursuit Constraints for Training Neural Networks Nathan Intrator
• Assessing and Improving Neural Network Predictions by the Bootstrap Algorithm Gerhard Paass
• Self-Organizing Rules for Robust Principal Component Analysis Lei Xu, Alan L. Yuille
• Intersecting regions: The Key to combinatorial structure in hidden unit space Janet Wiles, Mark Ollila
• A Parallel Gradient Descent Method for Learning in Analog VLSI Neural Networks J. Alspector, R. Meir, B. Yuhas, A. Jayakumar, D. Lippe
• A Model of Feedback to the Lateral Geniculate Nucleus Carlos Brody
• History-Dependent Attractor Neural Networks Isaac Meilijson, Eytan Ruppin
• Single-Iteration Threshold Hamming Networks Isaac Meilijson, Eytan Ruppin, Moshe Sipper
• Reinforcement Learning Applied to Linear Quadratic Regulation Steven Bradtke
• The Computation of Stereo Disparity for Transparent and for Opaque Surfaces Suthep Madarasmi, Daniel Kersten, Ting-Chuen Pong
• Forecasting Demand for Electric Power Jen-Lun Yuan, Terrence Fine
• Visual Motion Computation in Analog VLSI Using Pulses Rahul Sarpeshkar, Wyeth Bair, Christof Koch
• Learning Control Under Extreme Uncertainty Vijaykumar Gullapalli
• Efficient Pattern Recognition Using a New Transformation Distance Patrice Simard, Yann LeCun, John Denker
• Planar Hidden Markov Modeling: From Speech to Optical Character Recognition Esther Levin, Roberto Pieraccini
• Global Regularization of Inverse Kinematics for Redundant Manipulators David DeMers, Kenneth Kreutz-Delgado
• Object-Based Analog VLSI Vision Circuits Christof Koch, Binnal Mathur, Shih-Chii Liu, John Harris, Jin Luo, Massimo Sivilotti
• Perceiving Complex Visual Scenes: An Oscillator Neural Network Model that Integrates Selective Attention, Perceptual Organisation, and Invariant Recognition Rainer Goebel
• Second order derivatives for network pruning: Optimal Brain Surgeon Babak Hassibi, David Stork
• Automatic Learning Rate Maximization by On-Line Estimation of the Hessian's Eigenvectors Yann LeCun, Patrice Simard, Barak Pearlmutter
• Computation of Heading Direction from Optic Flow in Visual Cortex Markus Lappe, Josef Rauschecker
• Statistical Modeling of Cell Assemblies Activities in Associative Cortex of Behaving Monkeys Itay Gat, Naftali Tishby
• Harmonic Grammars for Formal Languages Paul Smolensky
• Silicon Auditory Processors as Computer Peripherals John Lazzaro, John Wawrzynek, M. Mahowald, Massimo Sivilotti, Dave Gillespie
• Information, Prediction, and Query by Committee Yoav Freund, H. Sebastian Seung, Eli Shamir, Naftali Tishby
• Improving Convergence in Hierarchical Matching Networks for Object Recognition Joachim Utans, Gene Gindi
• A dynamical model of priming and repetition blindness Daphne Bavelier, Michael Jordan
• Unsupervised Discrimination of Clustered Data via Optimization of Binary Information Gain Nicol Schraudolph, Terrence J. Sejnowski
• On-Line Estimation of the Optimal Value Function: HJB- Estimators James Peterson
• Using Aperiodic Reinforcement for Directed Self-Organization During Development P. Montague, P. Dayan, S.J. Nowlan, A Pouget, T.J. Sejnowski
• A Connectionist Symbol Manipulator That Discovers the Structure of Context-Free Languages Michael C. Mozer, Sreerupa Das
• Analogy-- Watershed or Waterloo? Structural alignment and the development of connectionist models of analogy Dedre Gentner, Arthur Markman
• A Recurrent Neural Network for Generation of Occular Saccades Lina L.E. Massone
• Network Structuring and Training Using Rule-based Knowledge Volker Tresp, Jürgen Hollatz, Subutai Ahmad
• Hybrid Circuits of Interacting Computer Model and Biological Neurons Sylvie Masson, Gwendal Le Masson, Eve Marder, L. Abbott
• A Knowledge-Based Model of Geometry Learning Geoffrey Towell, Richard Lehrer
• Integration of Visual and Somatosensory Information for Preshaping Hand in Grasping Movements Yoji Uno, Naohiro Fukumura, Ryoji Suzuki, Mitsuo Kawato
• Kohonen Feature Maps and Growing Cell Structures - a Performance Comparison Bernd Fritzke
• A Neural Model of Descending Gain Control in the Electrosensory System Mark Nelson
• Memory-Based Reinforcement Learning: Efficient Computation with Prioritized Sweeping Andrew Moore, Christopher Atkeson
• Learning Fuzzy Rule-Based Neural Networks for Control Charles Higgins, Rodney Goodman
• Neural Network On-Line Learning Control of Spacecraft Smart Structures Christopher Bowman
• Hidden Markov Model Induction by Bayesian Model Merging Andreas Stolcke, Stephen Omohundro
• Statistical Mechanics of Learning in a Large Committee Machine Holm Schwarze, John Hertz
• An Information-Theoretic Approach to Deciphering the Hippocampal Code William Skaggs, Bruce McNaughton, Katalin Gothard
• Using hippocampal 'place cells' for navigation, exploiting phase coding Neil Burgess, John O'Keefe, Michael Recce
• Weight Space Probability Densities in Stochastic Learning: I. Dynamics and Equilibria Todd Leen, John Moody
• Discriminability-Based Transfer between Neural Networks L. Y. Pratt
• Learning Sequential Tasks by Incrementally Adding Higher Orders Mark Ring
• Topography and Ocular Dominance with Positive Correlations Geoffrey Goodhill
• A Hybrid Neural Net System for State-of-the-Art Continuous Speech Recognition G. Zavaliagkos, Y. Zhao, R. Schwartz, J. Makhoul
• A Formal Model of the Insect Olfactory Macroglomerulus: Simulations and Analytic Results Christiane Linster, David Marsan, Claudine Masson, Michel Kerszberg, Gérard Dreyfus, Léon Personnaz
• Using Prior Knowledge in a NNPDA to Learn Context-Free Languages Sreerupa Das, C. Giles, Guo-Zheng Sun
• A Method for Learning From Hints Yaser Abu-Mostafa
• Holographic Recurrent Networks Tony A. Plate
• Generalization Abilities of Cascade Network Architecture E. Littmann, H. Ritter
• Explanation-Based Neural Network Learning for Robot Control Tom M. Mitchell, Sebastian B. Thrun
• Some Solutions to the Missing Feature Problem in Vision Subutai Ahmad, Volker Tresp
• A Note on Learning Vector Quantization Virginia de, Dana Ballard
• Diffusion Approximations for the Constant Learning Rate Backpropagation Algorithm and Resistence to Local Minima William Finnoff
• Analog Cochlear Model for Multiresolution Speech Analysis Weimin Liu, Andreas Andreou, Moise Goldstein
• On Learning µ-Perceptron Networks with Binary Weights Mostefa Golea, Mario Marchand, Thomas Hancock
• A Boundary Hunting Radial Basis Function Classifier which Allocates Centers Constructively Eric Chang, Richard P. Lippmann
• Learning to See Where and What: Training a Net to Make Saccades and Recognize Handwritten Characters Gale Martin, Mosfeq Rashid, David Chapman, James Pittman
• How Oscillatory Neuronal Responses Reflect Bistability and Switching of the Hidden Assembly Dynamics K. Pawelzik, H.-U. Bauer, J. Deppisch, T. Geisel
• Summed Weight Neuron Perturbation: An O(N) Improvement Over Weight Perturbation Barry Flower, Marwan Jabri
• Extended Regularization Methods for Nonconvergent Model Selection W. Finnoff, F. Hergert, H. G. Zimmermann
• Synchronization and Grammatical Inference in an Oscillating Elman Net Bill Baird, Todd Troyer, Frank Eeckman
• Attractor Neural Networks with Local Inhibition: from Statistical Physics to a Digitial Programmable Integrated Circuit E. Pasero, R. Zecchina
• Metamorphosis Networks: An Alternative to Constructive Models Brian Bonnlander, Michael C. Mozer
• A Hybrid Linear/Nonlinear Approach to Channel Equalization Problems Wei-Tsih Lee, John Pearson
• Physiologically Based Speech Synthesis Makoto Hirayama, Eric Vatikiotis-Bateson, Kiyoshi Honda, Yasuharu Koike, Mitsuo Kawato
• Weight Space Probability Densities in Stochastic Learning: II. Transients and Basin Hopping Times Genevieve Orr, Todd Leen
• Performance Through Consistency: MS-TDNN's for Large Vocabulary Continuous Speech Recognition Joe Tebelskis, Alex Waibel
• Generic Analog Neural Computation - The EPSILON Chip Stephen Churcher, Donald Baxter, Alister Hamilton, Alan Murray, H. Reekie
• Analog VLSI Implementation of Multi-dimensional Gradient Descent David B. Kirk, Douglas Kerns, Kurt Fleischer, Alan Barr
• Improving Performance in Neural Networks Using a Boosting Algorithm Harris Drucker, Robert Schapire, Patrice Simard
• An Object-Oriented Framework for the Simulation of Neural Nets A. Linden, Th. Sudbrak, Ch. Tietz, F. Weber
• A Practice Strategy for Robot Learning Control Terence Sanger
• Modeling Consistency in a Speaker Independent Continuous Speech Recognition System Yochai Konig, Nelson Morgan, Chuck Wooters, Victor Abrash, Michael Cohen, Horacio Franco
• Learning to categorize objects using temporal coherence Suzanna Becker
• Learning Curves, Model Selection and Complexity of Neural Networks Noboru Murata, Shuji Yoshizawa, Shun-ichi Amari
• Optimal Depth Neural Networks for Multiplication and Related Problems Kai-Yeung Siu, Vwani Roychowdhury
• Time Warping Invariant Neural Networks Guo-Zheng Sun, Hsing-Hen Chen, Yee-Chun Lee
• Deriving Receptive Fields Using an Optimal Encoding Criterion Ralph Linsker
• Connected Letter Recognition with a Multi-State Time Delay Neural Network Hermann Hild, Alex Waibel
• Input Reconstruction Reliability Estimation Dean A. Pomerleau
• Mapping Between Neural and Physical Activities of the Lobster Gastric Mill Kenji Doya, Mary Boyle, Allen Selverston
• A Fast Stochastic Error-Descent Algorithm for Supervised Learning and Optimization Gert Cauwenberghs
• Nets with Unreliable Hidden Nodes Learn Error-Correcting Codes Stephen Judd, Paul Munro
• Unsmearing Visual Motion: Development of Long-Range Horizontal Intrinsic Connections Kevin Martin, Jonathan Marshall
• Remote Sensing Image Analysis via a Texture Classification Neural Network Hayit K. Greenspan, Rodney Goodman
• Filter Selection Model for Generating Visual Motion Signals Steven Nowlan, Terrence J. Sejnowski
• Non-Linear Dimensionality Reduction David DeMers, Garrison Cottrell
• Feudal Reinforcement Learning Peter Dayan, Geoffrey E. Hinton
• A Neural Network that Learns to Interpret Myocardial Planar Thallium Scintigrams Charles Rosenberg, Jacob Erel, Henri Atlan
• Learning Cellular Automaton Dynamics with Neural Networks N. Wulff, J A. Hertz
• Probability Estimation from a Database Using a Gibbs Energy Model John Miller, Rodney Goodman
• Word Space Hinrich Schütze
• An Analog VLSI Chip for Radial Basis Functions Janeen Anderson, John Platt, David B. Kirk
• Predicting Complex Behavior in Sparse Asymmetric Networks Ali Minai, William Levy
• Destabilization and Route to Chaos in Neural Networks with Random Connectivity Bernard Doyon, Bruno Cessac, Mathias Quoy, Manuel Samuelides
• Recognition-based Segmentation of On-Line Hand-printed Words M. Schenkel, H. Weissman, I. Guyon, C. Nohl, D. Henderson
• Some Estimates of Necessary Number of Connections and Hidden Units for Feed-Forward Networks Adam Kowalczyk
• The Power of Approximating: a Comparison of Activation Functions Bhaskar DasGupta, Georg Schnitger
• Neural Network Model Selection Using Asymptotic Jackknife Estimator and Cross-Validation Method Yong Liu
• Context-Dependent Multiple Distribution Phonetic Modeling with MLPs Michael Cohen, Horacio Franco, Nelson Morgan, David Rumelhart, Victor Abrash
• On the Use of Evidence in Neural Networks David Wolpert
• Automatic Capacity Tuning of Very Large VC-Dimension Classifiers I. Guyon, B. Boser, V. Vapnik
• Interposing an ontogenetic model between Genetic Algorithms and Neural Networks Richard Belew
• Bayesian Learning via Stochastic Dynamics Radford Neal
• Biologically Plausible Local Learning Rules for the Adaptation of the Vestibulo-Ocular Reflex Olivier Coenen, Terrence J. Sejnowski, Stephen Lisberger
• Combining Neural and Symbolic Learning to Revise Probabilistic Rule Bases J. Mahoney, Raymond Mooney
• Transient Signal Detection with Neural Networks: The Search for the Desired Signal José Príncipe, Abir Zahalka
• Information Theoretic Analysis of Connection Structure from Spike Trains Satoru Shiono, Satoshi Yamada, Michio Nakashima, Kenji Matsumoto