NIPS PROGRAM --Correction
Steve Hanson
jose at learning.siemens.com
Fri Sep 28 08:04:54 EDT 1990
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.
-------
More information about the Connectionists
mailing list