jose@LEARNING.SIEMENS.COM (Steve Hanson) (09/28/90)
We had inadvertently excluded some of the posters from the preliminary program. We apologize for any confusion that may have caused. --Steve Hanson Below is a complete and correct version of the NIPS preliminary program. ------------------------------------------- NIPS 1990 Preliminary Program, November 26-29, Denver, Colorado Monday, November 26, 1990 12:00 PM: Registration Begins 6:30 PM: Reception and Conference Banquet 8:30 PM: After Banquet Talk, "Cortical Memory Systems in Humans", by Antonio Damasio. Tuesday, November 27, 1990 7:30 AM: Continental Breakfast 8:30 AM: Oral Session 1: Learning and Memory 10:30 AM: Break 11:00 AM: Oral Session 2: Navigation and Planning 12:35 PM: Poster Preview Session I, Demos 2:30 PM: Oral Session 3: Temporal and Real Time Processing 4:10 PM: Break 4:40 PM: Oral Session 4: Representation, Learning, and Generalization I 6:40 PM: Free 7:30 PM: Refreshments and Poster Session I Wednesday, November 28, 1990 7:30 AM: Continental Breakfast 8:30AM: Oral Session 5: Visual Processing 10:20 AM: Break 10:50 AM: Oral Session 6: Speech Processing 12:20 PM: Poster Preview Session II, Demos 2:30 PM: Oral Session 7: Representation, Learning, and Generalization II 4:10 PM: Break 4:40 PM: Oral Session 8: Control 6:40 PM: Free 7:30 PM: Refreshments and Poster Session II Thursday, November 29, 1990 7:30 AM: Continental Breakfast 8:30 AM: Oral Session 9: Self-Organization and Unsupervised Learning 10:20 AM: Break 10:50 AM: Session Continues 12:10 PM: Conference Adjourns 5:00 PM Reception and Registration for Post-Conference Workshop (Keystone, CO) Friday, November 30 -- Saturday, December 1, 1990 Post-Conference Workshops at Keystone ------------------------------------------------------------------------------ ORAL PROGRAM Monday, November 26, 1990 12:00 PM: Registration Begins 6:30 PM: Reception and Conference Banquet 8:30 PM: After Banquet Talk, "Cortical Memory Systems in Humans", by Antonio Damasio. Tuesday, November 27, 1990 7:30 AM: Continental Breakfast ORAL SESSION 1: LEARNING AND MEMORY Session Chair: John Moody, Yale University. 8:30 AM: "Multiple Components of Learning and Memory in Aplysia", by Thomas Carew. 9:00 AM: "VLSI Implementations of Learning and Memory Systems: A Review", by Mark Holler. 9:30 AM: "A Short-Term Memory Architecture for the Learning of Morphophonemic Rules", by Michael Gasser and Chan-Do Lee. 9:50 AM "Short Term Active Memory: A Recurrent Network Model of the Neural Mechanism", by David Zipser. 10:10 AM "Direct Memory Access Using Two Cues: Finding the Intersection of Sets in a Connectionist Model", by Janet Wiles, Michael Humphreys and John Bain. 10:30 AM Break ORAL SESSION 2: NAVIGATION AND PLANNING Session Chair: Lee Giles, NEC Research. 11:00 AM "Real-Time Autonomous Robot Navigation Using VLSI Neural Networks", by Alan Murray, Lionel Tarassenko and Michael Brownlow. 11:20 AM "Planning with an Adaptive World Model" by Sebastian B. Thrun, Knutt Moller and Alexander Linden . 11:40 AM "A Connectionist Learning Control Architecture for Navigation", by Jonathan Bachrach. 12:00 PM Spotlight on Language: Posters La1 and La3. 12:10 PM Spotlight on Applications: Posters App1, App6, App7, App10, and App11. 12:35 PM Poster Preview Session I, Demos ORAL SESSION 3: TEMPORAL AND REAL TIME PROCESSING Session Chair: Josh Alspector, Bellcore 2:30 PM "Learning and Adaptation in Real Time Systems", by Carver Mead. 3:00 PM "Applications of Neural Networks in Video Signal Processing", by John Pearson. 3:30 PM "Predicting the Future: A Connectionist Approach", by Andreas S. Weigend, Bernardo Huberman and David E. Rumelhart. 3:50 PM "Algorithmic Musical Composition with Melodic and Stylistic Constraints", by Michael Mozer and Todd Soukup. 4:10 PM Break ORAL SESSION 4: REPRESENTATION, LEARNING, AND GENERALIZATION I Session Chair: Gerry Tesauro, IBM Research Labs. 4:40 PM "An Overview of Representation and Convergence Results for Multilayer Feedforward Networks", by Hal White . 5:10 PM "A Simplified Linear-Threshold-Based Neural Network Pattern Classifier", by Terrence L. Fine. 5:30 PM "A Novel approach to predicition of the 3-dimensional structures of protein backbones by neural networks", by H. Bohr, J. Bohr, S. Brunak, R.M.J. Cotterill, H. Fredholm, B. Lautrup and S.B. Petersen. 5:50 PM "On the Circuit Complexity of Neural Networks", by Vwani Roychowdhury, Kai- Yeung Siu, Alon Orlitsky and Thomas Kailath . 6:10 PM Spotlight on Learning and Generalization: Posters LG2, LG3, LG8, LS2, LS5, and LS8. 6:40 PM Free 7:30 PM Refreshments and Poster Session I Wednesday, November 28, 1990 7:30 AM Continental Breakfast ORAL SESSION 5: VISUAL PROCESSING Session Chair: Yann Le Cun, AT&T Bell Labs 8:30 AM "Neural Dynamics of Motion Segmentation", by Ennio Mingolla. 9:00 AM "VLSI Implementation of a Network for Color Constancy", by Andrew Moore, John Allman, Geoffrey Fox and Rodney Goodman. 9:20 AM "Optimal Filtering in the Salamander Retina", by Fred Rieke, Geoffrey Owen and William Bialek. 9:40 AM "Grouping Contour Elements Using a Locally Connected Network", by Amnon Shashua and Shimon Ullman. 10:00 AM Spotlight on Visual Motion Processing: Posters VP3, VP6, VP9, and VP12. 10:20 AM Break ORAL SESSION 6: SPEECH PROCESSING Session Chair: Richard Lippmann, MIT Lincoln Labs 10:50 AM "From Speech Recognition to Understanding: Development of the MIT, SUMMIT, and VOYAGER Systems", by James Glass. 11:20 PM "Speech Recognition using Connectionist Approaches", by K.Chouki, S. Soudoplatoff, A. Wallyn, F. Bimbot and H. Valbret. 11:40 AM "Continuous Speech Recognition Using Linked Predictive Neural Networks", by Joe Tebelskis, Alex Waibel and Bojan Petek. 12:00 PM Spotlight on Speech and Signal Processing: Posters Sig1, Sig2, Sp2, and Sp7. 12:20 PM Poster Preview Session II, Demos ORAL SESSION 7: REPRESENTATION, LEARNING AND GENERALIZATION II Session Chair: Steve Hanson, Siemens Research. 2:30 PM "Learning and Understanding Functions of Many Variables Through Adaptive Spline Networks", by Jerome Friedman. 3:00 PM "Connectionist Modeling of Generalization and Classification", by Roger Shepard. 3:30 PM "Bumptrees for Efficient Function, Constraint, and Classification Learning", by Stephen M.Omohundro. 3:50 PM "Generalization Properties of Networks using the Least Mean Square Algorithm", by Yves Chauvin. 4:10 PM Break ORAL SESSION 8: CONTROL Session Chair: David Touretzky, Carnegie-Mellon University. 4:40 PM "Neural Network Application to Diagnostics and Control of Vehicle Control Systems", by Kenneth Marko. 5:10 PM "Neural Network Models Reveal the Organizational Principles of the Vestibulo- Ocular Reflex and Explain the Properties of its Interneurons", by T.J. Anastasio. 5:30 PM "A General Network Architecture for Nonlinear Control Problems", by Charles Schley, Yves Chauvin, Van Henkle and Richard Golden. 5:50 PM "Design and Implementation of a High Speed CMAC Neural Network Using Programmable CMOS Logic Cell Arrays", by W. Thomas Miller, Brain A. Box, Erich C. Whitney and James M. Glynn. 6:10 PM Spotlight on Control: Posters CN2, CN6, and CN7. 6:25 PM Spotlight on Oscillations: Posters Osc1, Osc2, and Osc3. 6:40 PM Free 7:30 PM Refreshments and Poster Session II Thursday, November 29, 1990 7:30 AM Continental Breakfast ORAL SESSION 9: SELF ORGANIZATION AND UNSUPERVISED LEARNING Session Chair: Terry Sejnowki, The Salk Institute. 8:30 AM "Self-Organization in a Developing Visual Pattern", by Martha Constantine-Paton. 9:00 AM "Models for the Development of Eye-Brain Maps", by Jack Cowan. 9:20 AM "VLSI Implementation of TInMANN", by Matt Melton, Tan Pahn and Doug Reeves. 9:40 AM "Fast Adaptive K-Means Clustering", by Chris Darken and John Moody. 10:00 AM "Learning Theory and Experiments with Competitive Networks", by Griff Bilbro and David Van den Bout. 10:20 AM Break 10:50 AM "Self-Organization and Non-Linear Processing in Hippocampal Neurons", by Thomas H. Brown, Zachary Mainen, Anthony Zador and Brenda Claiborne. 11:10 AM "Weight-Space Dynamics of Recurrent Hebbian Networks", by Todd K. Leen. 11:30 AM "Discovering and Using the Single Viewpoint Constraint", by Richard S. Zemel and Geoffrey Hinton. 11:50 AM "Task Decompostion Through Competition in A Modular Connectionist Architecture: The What and Where Vision Tasks", by Robert A. Jacobs, Michael Jordan and Andrew Barto. 12:10 PM Conference Adjourns 5:00 PM Post-Conference Workshop Begins (Keystone, CO) ------------------------------------------------------------------------------ POSTER PROGRAM POSTER SESSION I Tuesday, November 27 (* denotes poster spotlight) APPLICATIONS App1* "A B-P ANN Commodity Trader", by J.E. Collard. App2 "Analog Neural Networks as Decoders", by Ruth A. Erlanson and Yaser Abu- Mostafa. App3 "Proximity Effect Corrections in Electron Beam Lithography Using a Neural Network", by Robert C. Frye, Kevin Cummings and Edward Rietman. App4 "A Neural Expert System with Automated Extraction of Fuzzy IF-THEN Rules and Its Application to Medical Diagnosis", by Yoichi Hayashi. App5 "Integrated Segmentation and Recognition of Machine and Hand--printed Characters", by James D. Keeler, Eric Hartman and Wee-Hong Leow. App6* "Training Knowledge-Based Neural Networks to Recognize Genes in DNA Sequences", by Michael O. Noordewier, Geoffrey Towell and Jude Shavlik. App7* "Seismic Event Identification Using Artificial Neural Networks", by John L. Perry and Douglas Baumgardt. App8 "Rapidly Adapting Artificial Neural Networks for Autonomous Navigation", by Dean A. Pomerleau. App9 "Sequential Adaptation of Radial Basis Function Neural Networks and its Application to Time-series Prediction", by V. Kadirkamanathan, M. Niranjan and F. Fallside. App10* "EMPATH: Face, Emotion, and Gender Recognition Using Holons", by Garrison W. Cottrell and Janet Metcalf. App11* "Sexnet: A Neural Network Identifies Sex from Human Faces", by B. Golomb, D. Lawrence and T.J. Sejnowski. EVOLUTION AND LEARNING EL1 "Using Genetic Algorithm to Improve Pattern Classification Performance", by Eric I. Chang and Richard P. Lippmann. EL2 "Evolution and Learning in Neural Networks: The Number and Distribution of Learning Trials Affect the Rate of Evolution", by Ron Kessing and David Stork. LANGUAGE La1* "Harmonic Grammar", by Geraldine Legendre, Yoshiro Miyata and Paul Smolensky. La2 "Translating Locative Prepostions", by Paul Munro and Mary Tabasko. La3* "Language Acquisition via Strange Automata", by Jordon B. Pollack. La4 "Exploiting Syllable Structure in a Connectionist Phonology Model", by David S. Touretzky and Deirdre Wheeler. LEARNING AND GENERALIZATION LG1 "Generalization Properties of Radial Basis Functions", by Sherif M.Botros and C.G. Atkeson. LG2* "Neural Net Algorithms That Learn In Polynomial Time From Examples and Queries", by Eric Baum. LG3* "Looking for the gap: Experiments on the cause of exponential generalization", by David Cohn and Geral Tesauro. LG4 "Dynamics of Generalization in Linear Perceptrons ", by A. Krogh and John Hertz. LG5 "Second Order Properties of Error Surfaces, Learning Time, and Generalization", by Yann LeCun, Ido Kanter and Sara Solla. LG6 "Kolmogorow Complexity and Generalization in Neural Networks", by Barak A. Pearlmutter and Ronal Rosenfeld. LG7 "Learning Versus Generalization in a Boolean Neural Network", by Johathan Shapiro. LG8* "On Stochastic Complexity and Admissible Models for Neural Network Classifiers", by Padhraic Smyth. LG9 "Asympotic slowing down of the nearest-neighbor classifier", by Robert R. Snapp, Demetri Psaltis and Santosh Venkatesh. LG10 "Remarks on Interpolation and Recognition Using Neural Nets", by Eduardo D. Sontag. LG11 "Epsilon-Entropy and the Complexity of Feedforward Neural Networks", by Robert C. Williamson. LEARNING SYSTEMS LS1 "Analysis of the Convergence Properties of Kohonen's LVQ", by John S. Baras and Anthony LaVigna. LS2* "A Framework for the Cooperation of Learning Algorithms", by Leon Bottou and Patrick Gallinari. LS3 "Back-Propagation is Sensitive to Initial Conditions", by John F. Kolen and Jordan Pollack. LS4 "Discovering Discrete Distributed Representations with Recursive Competitive Learning", by Michael C. Mozer. LS5* "From Competitive Learning to Adaptive Mixtures of Experts", by Steven J. Nowlan and Geoffrey Hinton. LS6 "ALCOVE: A connectionist Model of Category Learning", by John K. Kruschke. LS7 "Transforming NN Output Activation Levels to Probability Distributions", by John S. Denker and Yann LeCunn. LS8* "Closed-Form Inversion of Backropagation Networks: Theory and Optimization Issues", by Michael L. Rossen. LOCALIZED BASIS FUNCTIONS LBF1 "Computing with Arrays of Bell Shaped Functions Bernstein Polynomials and the Heat Equation", by Pierre Baldi. LBF2 "Function Approximation Using Multi-Layered Neural Networks with B-Spline Receptive Fields", by Stephen H. Lane, David Handelman, Jack Gelfand and Marshall Flax. LBF3 "A Resource-Allocating Neural Network for Function Interpolation" by John Platt. LBF4 "Adaptive Range Coding", by B.E. Rosen, J.M. Goodwin and J.J. Vidal. LBF5 "Oriented Nonradial Basis Function Networks for Image Coding and Analysis", by Avi Saha, Jim christian, D.S. Tang and Chuan-Lin Wu. LBF6 "A Tree-Structured Network for Approximation on High-Dimensional Spaces", by T. Sanger. LBF7 "Spherical Units as Dynamic Reconfigurable Consequential Regions and their Implications for Modeling Human Learning and Generalization", by Stephen Jose Hanson and Mark Gluck. LBF8 "Feedforward Neural Networks: Analysis and Synthesis Using Discrete Affine Wavelet Transformations", by Y.C. Pati and P.S. Krishnaprasad. LBF9 "A Network that Learns from Unreliable Data and Negative Examples", by Fredico Girosi, Tomaso Poggio and Bruno Caprile. LBF10 "How Receptive Field Parameters Affect Neural Learning", by Bartlett W. Mel and Stephen Omohundro. MEMORY SYSTEMS MS1 "The Devil and the Network: What Sparsity Implies to Robustness and Memory", by Sanjay Biswas and Santosh Venkatesh. MS2 "Cholinergic modulation selective for intrinsic fiber synapses may enhance associative memory properties of piriform cortex", by Michael E. Hasselmo, Brooke Anderson and James Bower. MS3 "Associative Memory in a Network of 'Biological' Neurons", by Wulfram Gerstner. MS4 "A Learning Rule for Guaranteed CAM Storage of Analog Patterns and Continuous Sequences in a Network of 3N^2 Weights", by William Baird. VLSI IMPLEMENTATIONS VLSI1 "A Highly Compact Linear Weight Function Based on the use of EEPROMs", by A. Krammer, C.K. Sin, R. Chu and P.K. Ko. VLSI2 "Back Propagation Implementation on the Adaptive Solutions Neurocomputer Chip", Hal McCartor. VLSI3 "Analog Non-Volatile VLSI Neural Network Chip and Back-Propagation Training", by Simon Tam, Bhusan Gupta, Hernan A. Castro and Mark Holler. VLSI4 "An Analog VLSI Splining Circuit", by D.B. Schwartz and V.K. Samalam. VLSI5 "Reconfigurable Neural Net Chip with 32k Connections", by H.P.Graf and D. Henderson. VLSI6 "Relaxation Networks for Large Supervised Learning Problems", by Joshua Alspector, Robert Allan and Anthony Jayakumare. POSTER SESSION II Wednesday, November 28 (* denotes poster spotlight) CONTROL AND NAVIGATION CN1 "A Reinforcement Learning Variant for Control Scheduling", by Aloke Guha. CN2* "Learning Trajectory and Force Control of an Artificial Muscle Arm by Parallel- Hierarchical Neural Network Model", by Masazumi Katayama and Mitsuo Kawato. CN3 "Identification and Control of a Queueing System with Neural Networks", by Rodolfo A. Milito, Isabelle Guyon and Sara Solla. CN4 "Conditioning And Spatial Learning Tasks", by Peter Dayan. CN5 "Reinforcement Learning in Non-Markovian Environments", by Jurgen Schmidhuber. CN6* "A Model for Distributed Sensorimotor Control of the Cockroach Escape Turn", by Randall D. Beer, Gary Kacmarcik, Roy Ritzman and Hillel Chiel. CN7* "Flight Control in the Dragonfly: A Neurobiological Simulation", by W.E. Faller and M.W. Luttges. CN8 "Integrated Modeling and Control Based on Reinforcement Learning and Dynamic Programming", by Richard S. Sutton. DEVELOPMENT Dev1 "Development of the Spatial Structure of Cortical Feature Maps: A Model Study", by K. Obermayer and H. Ritter and K. Schulten. Dev2 "Interaction Among Ocular Dominance, Retinotopic Order and On-Center/Off- Center Pathways During Development", by Shiqeru Tanaka. Dev3 "Simple Spin Models for the development of Ocular Dominance and Iso-Orientation Columns", by Jack Cowan. NEURODYNAMICS ND1 "Reduction of Order for Systems of Equations Describing the Behavior of Complex Neurons", by T.B.Kepler, L.F. Abbot and E. Marder. ND2 "An Attractor Neural Network Model of Recall and Recognition", by E. Ruppin, Y. Yeshurun. ND3 "Stochastic Neurodynamics", by Jack Cowan. ND4 "A Method for the Efficient Design of Boltzman Machines for Classification Problems", by Ajay Gupta and Wolfgang Maass. ND5 "Analog Neural Networks that are Parallel and Stable", by C.M. Marcus, F.R. Waugh and R.M. Westervelt. ND6 "A Lagrangian Approach to Fixpoints ", by Eric Mjolsness and Willard Miranker. ND7 "Shaping the State Space Landscape in Recurrent Networks", by Patrice Y. Simard, Jean Pierre Raysz and Bernard Victorri. ND8 "Adjoint-Operators and non-Adiabatic Learning Algorithms in Neural Networks", by N. Toomarian and J. Barhen. OSCILLATIONS Osc1* "Connectivity and Oscillations in Two Dimensional Models of Neural Populations", by Daniel M. Kammen, Ernst Niebur and Christof Koch. Osc2* "Oscillation Onset in Neural Delayed Feedback", by Andre Longtin. Osc3* "Analog Computation at a Critical Point: A Novel Function for Neuronal Oscillations? ", by Leonid Kruglyak. PERFORMANCE COMPARISONS PC1 "Comparison of three classification techniques, Cart, C4.5 and multi-layer perceptions", by A.C. Tsoi and R.A. Pearson. PC2 "A Comparative Study of the Practical Characteristics of Neural Network and Conventional Pattern Classifiers", by Kenny Ng and Richard Lippmann. PC3 "Time Trials on Second-Order and Variable-Learning-Rate Algorithms", by Richard Rohwer. PC4 "Kohonen Networks and Clustering: Comparative Performance in Color Clusterng", by Wesley Snyder, Daniel Nissman, David Van den Bout and Griff Bilbro. SIGNAL PROCESSING Sig1* "Natural Dolphin Echo Recognition Using An Integrator Gateway Network", by H. L. Roitblat, P.W.B. Moore, R.H. Penner and P.E. Nachtigall. Sig2* "Signal Processing by Multiplexing and Demultiplexing in Neurons", by David C. Tam. SPEECH PROCESSING Sp1 "A Temporal Neural Network for Word Identification from Continuous Phoneme Strings", by Robert B. Allen and Candace Kamm. Sp2* "Connectionist Approaches to the use of Markov Models for Speech Recognition", by H.Bourlard and N. Morgan. Sp3 "The Temp 2 Algorithm: Adjusting Time-Delays by Supervised Learning", by Ulrich Bodenhausen. Sp4 "Spoken Letter Recognition", by Mark Fanty and Ronald A.Cole. Sp5 "Speech Recognition Using Demi-Syllable Neural Prediction Model", by Ken-ichi Iso and Takao Watanabe. Sp6 "RECNORM: Simultaneous Normalisation and Classification Applied to Speech Recognition", by John S. Bridle and Steven Cox. Sp7* "Exploratory Feature Extraction in Speech Signals", by Nathan Intrator. SP8 "Detection and Classification of Phonemes Using Context-Independent Error Back- Propagation", by Hong C. Leung, James R. Glass, Michael S. Phillips and Victor W. Zue. TEMPORAL PROCESSING TP1 "Modeling Time Varying Systems Using a Hidden Control Neural Network Architecture", by Esther Levin. TP2 "A New Neural Network Model for Temporal Processing", by Bert de Vries and Jose Principe. TP3 "ART2/BP architecture for adaptive estimation of dynamic processes", by Einar Sorheim. TP4 "Statistical Mechanics of Temporal Association in Neural Networks with Delayed Interaction", by Andreas V.M. Herz, Zahoping Li, Wulfram Gerstner and J. Leo van Hemmen. TP5 "Learning Time Varying Concepts", by Anthony Kuh and Thomas Petsche. TP6 "The Recurrent Cascade-Correlation Architecture" by Scott E. Fahlman. VISUAL PROCESSING VP1 "Steropsis by Neural Networks Which Learn the Constraints", by Alireza Khotanzad and Ying-Wung Lee. VP2 "A Neural Network Approach for Three-Dimensional Object Recognition", by Volker Tresp. VP3* "A Multiresolution Network Model of Motion Computation in Primates", by H. Taichi Wang, Bimal Mathur and Christof Koch. VP4 "A Second-Order Translation, Rotation and Scale Invariant Neural Network ", by Shelly D.D.Goggin, Kristina Johnson and Karl Gustafson. VP5 "Optimal Sampling of Natural Images: A Design Principle for the Visual System?", by William Bialek, Daniel Ruderman and A. Zee. VP6* "Learning to See Rotation and Dilation with a Hebb Rule", by Martin I. Sereno and Margaret E. Sereno. VP7 "Feedback Synapse to Cone and Light Adaptation", by Josef Skrzypek. VP8 "A Four Neuron Circuit Accounts for Change Sensitive Inhibition in Salamander Retina", by J.L. Teeters, F. H. Eeckman, G.W. Maguire, S.D. Eliasof and F.S. Werblin. VP9* "Qualitative structure from motion", by Daphana Weinshall. VP10 "An Analog VLSI Chip for Finding Edges from Zero-Crossings", by Wyeth Bair. VP11 "A CCD Parallel Processing Architecture and Simulation of CCD Implementation of the Neocognitron", by Michael Chuang. VP12* "A Correlation-based Motion Detection Chip", by Timothy Horiuchi, John Lazzaro, Andy Moore and Christof Koch. -------