From: sef@sef-pmax.slisp.cs.cmu.edu
Newsgroups: comp.ai.neural-nets
Subject: NIPS*92 Conference Program
Date: 13 Oct 92 04:00:48 GMT
Organization: School of Computer Science, Carnegie Mellon

Here is the conference program for the upcoming NIPS conference in Denver.

===========================================================================


                         NIPS*92 Conference PROGRAM



All inquiries for registration to Conference, Tutorials or Workshop
should go to

	NIPS*92 Registration
	SIEMENS Research Center
	755 College Rd. East
	Princeton, NJ 08550

	phone 609-734-3383
	email kic@learning.siemens.com


ORAL PROGRAM:

Monday, November 30
	
	After Dinner Talk:
			Stuart Anstis, Psychology Department., UC San Diego
			"I Thought I saw it move:  The Psychology of Motion 				Perception."

Tuesday, December 1
	
	ORAL 1:  COMPLEXITY, LEARNING & GENERALIZATION [8:30--9:40]

	0.1.1.		T. Cover, Department of Elec. Eng., Stanford University
			"Complexity and Generalization in Neural Networks." 
			(Invited Talk)[8:30am]  

	0.1.2.		N. Intrator, Center for Neural Science, Brown University
			"Combining Exploratory Projection Pursuit and 
                        Projection Pursuit Regression with Application
to Neural Networks"
			[9:00am]

	0.1.3.		A, Stolcke & S. Omohundro, International Computer 
                        Science Institute, 			
                        Berkeley, CA "Hidden Markov Model Induction by 
                        Bayesian Model." [9:20am]

	0.1.4		K-Y Siu*, V. Roychowdhury%, T. Kailath+, 
			*Department of Elec. & Computer Eng., UC Irvine, 
			%School of Elec. Eng., Purdue University, 			
			+Information Systems Lab, Stanford University
			"Computing with Almost Optimal Size Neural Networks."
			[9:40am]
	
	ORAL 2:	 CONTROL, NAVIGATION & PLANNING

	0.2.1.		D. DeMers* & K. Kreutz-Delgado%, 
			*Dept. of Computer Science, UC San Diego,
			%Dept. of Elec. & Computer Eng. & Inst. for 
                        Neural Comp., UC San Diego
			"Global Regularization of Inverse Kinematics for 
                        Redundant Manipulators."  [10:30am]

	0.2.2		A. W. Moore & C. G. Atkeson, MIT Al Lab
			"Memory-based Reinforcement Learning:  
                        Efficient Computation with Prioritized Sweeping."  
                        [10:50am]

	0.2.3		P. Dayan* & G. E. Hinton%
			*CNL, The Salk Institute
			%Department of Computer Science, Univeristy of Toronto
			"Feudal Reinforcement Learning."  [11:10am]

	0.2.4		D. Pomerleau, School of Computer Science, CMU
			"Input Reconstruction Reliability Estimation."  
                        [11:30am]


	SPOTLIGHT 1:  COMPLEXITY, LEARNING & GENERALIZATION.  
			CONTROL, NAVIGATION & PLANNING.   [11:50-11:58am]

	ORAL 3: 	 VISUAL PROCESSING

	0.3.1.		S. Geman, Mathematics Department, Brown University
			"Interpretation-guided Segmentation and Recognition." 				           
     (Invited Talk)  [2:00pm]

	0.3.2.		S. Becker, Department of Computer Science, 
                         Univ. of Toronto
			"Learning to Categorize Objects Using 
                         Temporal Coherence."
			[2:30pm]

	0.3.3.		S. J Nowlan & T. J. Sejnowski, CNL, The Salk Institute
			"Filter Selection Model for Generating Visual Motion 				            
    Signals for Target Tracking."  [2:50pm]

	0.3.4.		E. Stern*, A. Aertsen%, E. Vaadia+ & S. Hochstein**
			*Department of Neurobiology, 
                        Hebrew University, Jerusalem
			%Inst. fur Neuroinformatik, Ruhr-Univ., Bochum, Germany
			+Department of Physiology, Hebrew University, 
                        Jerusalem **
			"Stimulus Encoding by Multi-Dimensional Receptive 
                        Fields in Single Cells and Cell Populations in V1 of 
                        Awake Monkey."  [3:10pm]

	ORAL 4:	 STOCHASTIC LEARNING AND ANALYSIS

	0.4.1.		T. K. Leen* & J. Moody %
			*CSE Department, Oregon Graduate Institute
			%Department of Computer Science, Yale University
			"Probability Densities and Equilibria in Stochastic 			i             
           Learning."   [4:00pm]

	0.4.2.		W. Finnoff, Siemens AG Corp. Res. & Dev., Munich, 
                        Germany
                        "Diffusion Approximations for the 
                        Constant Learning Rate Backpropagation Algorithm and 
                        Resistance to Local Minima."  [4:20pm]

	0.4.3.		L. Xu & A. Yuille, Division of Applied Sciences, 
                        Harvard Univ.
			"Self-Organization for Robust Principal 
                        Component Analysis by the Statistical Physics
Approach."  [4:40pm]

	SPOTLIGHT 2:	VISUAL PROCESSING   [5:00-5:12pm]

	SPOTLIGHT 3:	STOCHASTIC LEARNING & ANALYSIS  [5:15-5:35pm]



Wednesday, December 2
	
	ORAL 5:	COMPUTATIONAL AND THEORETICAL NEUROBIOLOGY

	0.11.1.	J. Rinzel, Mathematical Research Branch, NIH
			"Coupling Mechanisms and Rhythmogenesis in Neuron Models."  
                        (Invited Talk)  [8:30am]

	0.11.2.	K. Doya, M.E.T. Boyle, and A. I. Selverston
			Department of Biology, UC San Diego
			"Mapping between Neural and Physical Activities of the 				          
       Lobster Gastric Mill System."  [9:00am]

	0.11.3.	M. E. Nelson, Beckman Institute, University of Illinois
			"Neural Models of Adaptive Filtering Mechanisms in the 				          
       Electrosensory System."9:20am]

	0.11.4.	N. Burgess, J. O'Keefe and M. Reece
			Department of Anatomy, University College, London
			"Using Hippocampal 'Place Cells' for Navigation, 
                         Exploiting Phase Coding."  [9:40am]	

	
	0.11.5.	M. A. Gluck and C. E. Myers
			Center for Molecular and Behaviorial Neuroscience, 
                        Rutgers Univ.
			"Neural Bases of Adaptive Stimulus Representations:  A 				          
       Computational Theory of Hippocampal-Region Function."
			[10:00am]
	
	ORAL 6:	SPEECH AND SIGNAL PROCESSING

	0.6.1.		M. Cohen*, H. Franco*, N. Morgan%, D. Rumelhart+, and 
                        V. Abrash*
			*SRI Inst., Menlo Park, CA
			%ICSI, Berkeley, CA
			+Psychology Department, Stanford University, CA
			"Context-Dependent Multiple Distribution Phonetic 			i               
         Modeling with MLPS."   [10:50am]

	0.6.2.		M. Hirayama*, E. V. Bateson%, K. Honda%, Y. Koike* and 
                        M. Kawato*
			*ATR Human Inf. Proc. Res. Labs
			%ATR Auditory and Visual Perception Res. Labs., Kyoto, 
                        Japan
			"Physiologically Based Speech Synthesis."  [11:10am]

	0.6.3.		W. Liu, M. H. Goldstein, Jr. and A. G. Androu, 
			Dept. of Elec. & Comp. Eng., 
                        The Johns Hopskins University
			"Analog Cochlear Model for Multiresolution Speech Analysis."  [11:30am]
	
	SPOTLIGHT 4: COMPUTATIONAL AND THEORETICAL NEUROBIOLOGY.
	[11:50am-12:02pm]
	SPOTLIGHT 5: SPEECH AND SIGNAL PROCESSING.  [12:04-12:08pm]
					
	

	ORAL 7:	 COMPLEXITY, LEARNING & GENERALIZATION 2

	0.5.1.		S. Solla, AT&T Bell Labs
			"The Emergence of Generalization Ability in Learning 				            
     Machines."  (Invited Talk)  [2:00pm]

	0.5.2.		J. Wiles* & M Ollila%
			*Depts. of Computer Science & Psychology, Univ. of 				              
  Queensland, Australia
			%Vision Lab, CITRI, Dept. of Computer Science, 
                        Univ. of Melbourne, Australia
			"Intersecting Regions:  
                         The Key to Combinatorial Structure in 
                         Hidden Unit Space."  [2:30pm]

	0.5.3.		T. A. Plate, Department of Computer Science, 
                        Univ. of Toronto
			"Holographic Recurrent Networks." [2:50pm]
	
	0.5.4.		P. Simard, Y. LeCun & J. Denker, AT& T Bell Labs
			"Efficient Pattern Recognition Using a  
                        New Transformation Distance." [3:10pm]

	SPOTLIGHT 6:	COMPLEXITY, LEARNING & GENERALISATION 2
                        [3:30-3:42pm]

	ORAL 8:	IMPLEMENTATIONS
	
	0.8.1.		J. Platt, J. Anderson, & D. Kirk, Synaptics, Inc., 
                        San Jose, CA
			"An Analog VLSI Chip for Radial Basis Functions." 
                        [4:15pm]

	0.8.2.		H. P. Graf, E. Cosatto, E. Sackinger, and J. Snyder, 
                        AT&T Bell Labs
			"A Modular System with Multiple Neural Net Chips." 
                         [4:35pm]

	0.8.3.		D. J. Baxter, S. Churcher, A. Hamilton, A. F. Murray, 
                        and H. M. Rackie
			Department of Elec. Eng., University of Edinburgh, 
                        Scotland
			"The Edinburgh Pulse Stream Implementation of a 			i                 
      Learning-Oriented Network (Epsilon) Chip."  
                           [4:55pm]

	
	SPOTLIGHT 7: COGNITIVE SCIENCE,   [5:15-5-19pm]						
	SPOTLIGHT 8: IMPLEMENTATIONS, APPLICATIONS  [5:20-5:40pm]



Thursday, December 3
	
	ORAL 9:	PREDICTION
	
	0.9.1.		A. Lapedes, Theory Division, Los Alamos National 
                        Laboratory
			"Nonparametric Neural Networks for Prediction."  
                        (Invited Talk)  [8:30am]

	0.9.2.		M. Plutowski*, G. Cottrell%, and H. White+
			*Department of Computer Science & Engineering,
			%Inst. for Neural Comp. and 
                        Department of Computer Science & Eng.,
			+Inst. for Neural Comp. and 
                         Department of Economics, UCSD
			"Learning Mackey-Glass from 25 Examples, Plus or Minus 				2."  [9:00am]

	ORAL 10:	COGNITIVE SCIENCE

	0.10.1.	P. Smolensky
			Dept. of Computer Sci. and 
                        Inst. of Cog. Sci., Univ. of Colorado, Boulder
			"Harmonic Grammars for Formal Languages."  [9:20am]

	0.10.2.	D. Gentner & A. B. Markman
			Department of Psychology, Northwestern University
			"Analogy -- Watershed or Waterloo?  Structural Alignment 			         
       and the Development of 
                        Connectionist Models of Cognition."
			[9:40am]
	
	ORAL 11: APPLICATIONS
	
	0.7.1.		Dr. W. Baxt, UCSD Medical Center
			"The Application of the Artificial Neural Network to 				            
    Clinical Decision Making."  (Invited Talk)   [10:30am]

	0.7.2.		V. Tresp*, J. Moody%, and W-R. Delong+
			*Seimens AG, Central Research, Munich, Germany
			%Computer Science Department, Yale University
			+Seimens AG, Medical Eng. Group, Erlangen, Germany
			"Prediction and Control of the Glucose Metabolism of a 				          
       Diabetic."  [11:00am]

	0.7.3.		P. Baldi* & Y. Chavin%
			*JPL, Division of Biology, Cal Tech
			%Net-ID, Inc., and Psychology Department, 
                        Stanford University
			"Neural Networks for Finger Print Matching and 					                
Classification."  [11:20am]

	0.7.4.		M. Schenkel*, H. Weismann, I. Guyon, C. Nohl, 
                        D. Henderson, B. Bosser%, and L. Jackel
			AT&T Bell Labs
			*also ETH-Zunch, %also EECS Dept., UC Berkeley
			"TDNN Solutions for Recognizing On-Line Natural 					Handwriting."  
[11:40am]

	POSTER SPOTLIGHT TALKS  (4 Minute Talks)

	
	SPOTLIGHT 1:	COMPLEXITY, LEARNING & GENERALIZATION 1.
					CONTROL, NAVIGATION & PLANNING.
	
	P&S.1.1.	K-Y Siu* & V. Roychowdhury%
			*Department of Elec. & Comp. Eng., UC Irvine
			%School of Elec. Eng., Purdue University	
			"Optimal Depth Neural Networks for Multiplication and 				Related Problems."

	P&S.1.2.	T. M. Mitchell and S. B. Thrun
			School of Computer Science, CMU
			"Explanation-Based Neural Network Learning for Robot 				Control."

	
	SPOTLIGHT 2:	VISUAL PROCESSING

	P&S.2.1.	S. Madarasmi*, D. Kersten%, and T-C Pong*
			*Department of Computer Science,
			%Department of Psychology, University of Minnesota
			"Computation of Stereo Disparity for Transparent and 
                        for Opaque Surfaces."

	P&S.2.2.	S. Ahmad and V. Tresp
			Siemens Research, Munich, Germany
			"Some Solutions to the Missing Feature Problem in Vision."

	P&S.2.3.	J. Utans and G. Gindi
			Department of Elec. Eng., Yale University
			"Improving Convergence in Hierarchical Matching 			                  
       Networks for Object Recognition."


	
	SPOTLIGHT 3:  	STOCHASTIC LEARNING & ANALYSIS

	P&S.3.1.	R. M. Neal, Department of Computer Science, 
                        University of Toronto
			"Bayesian Learning via Stochastic Dynamics."

	P&S.3.2.	Y. Freund*, H. S. Seung%, and N. Tishby+
			*Comp. and Inf. Sci., UC Santa Cruz,
			%Racah Inst. of Physics, and Center for Neural Comp., 
                        Hebrew Univ., Jerusalem,
			+Department of Comp. Sci. and Center for Neural Comp., 
                        Hebrew Univ., Jerusalem
			"Accelerating Learning Using Query by Committee."


	P&S.3.3.	A. F. Murray, J. P. Edwards
			Department of Elec. Eng., University of Edinburgh, 
                        Scotland
			"Synaptic Weight Noise During MLP Learning 
                        Enhances Fault-Tolerance."

	P&S.3.4.	D. De Mers and G. Cottrell
			Department of Computer Science, UC San Diego
			"Non-Linear Dimensionality Reduction."

	P&S.3.5.	N. N. Schraudolph* and T. J. Sejnowski%
			*Computer Science & Engr. Department, UC San Diego
			%Computer Neurobiology Lab., The Salk Institute
			"Self-Stabilizing Hebbian Learning:  Beyond Principal 				Components."

	SPOTLIGHT 4: COMPUTATIONAL AND THEORETICAL NEUROBIOLOGY.
	
	P&S.4.1.	I. Gutterman and N. Tishby
			Department of Comp. Sci. and Center for 
                        Neural Computation, Hebrew University, Jerusalem
			"Statistical Modeling of Cell-Assemblies Activities 
                        in Prefrontal Cortex of Behaving Monkeys."

	P&S.4.2.	R. Linsker, IBM. TJ Watson Center, Yorktown Heights
			"Towards Unambiguous Derivation of Receptive Fields 
                        Using a New Optimal-Encoding Criterion."

	P&S.4.3.	O. Coenen*, T. J. Sejnowski*, and S. G. Lisberger%
			*Comp. Neurobiol. Lab., Howard Hughes Medical Inst., 
                        The Salk Institute, La Jolla, CA
			%Department of Physiology, Kick Center for Integrating 
                        Neuroscience, UCSF, CA
			"Biologically Plausible Learning Rules for 
                        the Vestibular-Ocular Reflex (VOR)."

	SPOTLIGHT 5: SPEECH AND SIGNAL PROCESSING.

	P&S.5.1.	M. Hild and A. Waibel, School of Computer Science, CMU
			"Connected Letter Recognition with a Multi-State 
                        Time Delay Neural Network."
	
	SPOTLIGHT 6:  	COMPLEXITY, LEARNING & GENERALIZATION 2

	P&S.6.1.	I. Guyon*, B. Boser%, and V. Vapnik*
			*AT&T Bell Labs, Holmdel, NJ
			%EE&CS Department, UC Berkeley
			"Automatic Capacity Tuning of Very Large 
                        VC-Dimension Classifiers"

	P&S.6.2.	P.Y. Simard*, Y. LeCun*, and B. Pearlmutter%
			*AT&T Bell Labs, Holmdel, NJ
			%Yale University
			"Local Computation of the Second Derivative 
                        Information in a Multi-Layer Network."
         
	P&S. 6.3	H. Drucker, R. Schapire & P. Simard, AT&T Bell Labs
			"Improving Performance in Neural Networks Using 
                        a Boosting Algorithm."
	
	SPOTLIGHT 7: COGNITIVE SCIENCE
	
	P&S.7.1.	M. C. Mozer and S. Das
			Department of Computer Science & Inst. of 
                        Cognitive Science, Univ. of Colorado, Boulder, CO
			"A Connectionist Chunker that Induces the Structure 
                        of Context-Free Languages."


	SPOTLIGHT 8: IMPLEMENTATIONS, APPLICATIONS, 	
	

	P&S.5.1.	J. Lazzaro*, J. Wawrzynck*, M. Mahowald%, 
                        M. Sivilotti+, D. Gillespie$
			*EE &CS, UC Berkeley
			%Computation and Neural Sciences, Cal Tech
			+Computer Science, Cal. Tech. and Tanner Research, 
                        Pasadena, CA
			$Computer Science, Cal. Tech. and Synaptics, San Jox, CA
			"Silicon Auditory Processors as Computer Peripherals."

	P&S.5.2.	C. Koch*, B. Mathur%, S-C Liu+, J. G. Harris+, J. Luo 
                        and M. Sivilotti$
			*Computation and Neural Systems, Cal. Tech.
			%Rockwell Intl. Science Center, Thousand Oaks, CA
			+Al Lab, MIT
			$Tanner Research, Pasadena, CA
			"Object-Based Analog VLSI Vision Circuits."

	P&S.5.3.	J. Alspector, R. Meir, B. Yuhas, A. Jayakumar
			Bellcore, Morristown, NJ
			"A Parallel Gradient Descent Method for Learning in 
                        Analog 	 VLSI Neural Networks."

	P&S.5.4.	A. C. Tsoi, D. S. C. So, and A. Sergejew
			Department of Elec. Eng., University of Queensland, 
                        Australia
			"Classification of Electroencephalogram Using Artificial 		          
               Neural Networks."

	P&S.5.5.	Y. Salu, Physics Department, and CSTEA, 
                        Howard University
			"Classification of Satelite Multi-Spectral Image 
                        Data by the Binary Diamond Neural Network."


NIPS '92 FINAL POSTER SESSIONS 1 & 2

TUESDAY EVENING:  SESSION 1

	COMPLEXITY, LEARNING AND GENERALIZATION 1
		
"Optimal Depth Neural Networks for Multiplication and Related Problems."
Kai-Yeung Siu, Department of Elec. & Comp. Eng, UC Irvine
Vwani Roychowdhury, School of Elec. Eng., Purdue University

"Initial Complexity of Large Networks and Its Effect on Generalization."
Chuanyi Ji, Department of Eled, Comp. & System Eng., Rensselaer
Polytechnic Inst., Troy, NY

"Using Hints to Successfully Learn Context-Free Grammars with a Neural
Network Pushdown Automaton."
Sreerupa Das, Dept. of Computer Science, Univ. of Colorado, Boulder, CO
C. Lee Giles, NEC Richard Institute, Princeton, NJ
Guo-Zheng Sun, Inst. for Advanced Computer Studies, Univ. of MD

"Interposing an Ontogenic Model Between Genetic Algorithms and Neural
Networks."
Richard K. Belew, Cognitive Comp. Science Research Group, UC San Diego

"Combining Neural and Symbolic Learning to Revise Probabilistic Rule Bases."
J. Jeffrey Mahoney and Raymond J. Mooney, Dept. of Computer Science,
University of Texas, Austin, TX

"Learning Sequential Tasks by Incrementally Adding Higher Orders."
Mark Ring, Dept. of Computer Sciences, University of Texas, Austin, TX

"Kohonen Feature Maps and Growing Cell Structures -- A Performance Comparison."
Bernard Fritzke, Universitat Erlangen-Nurnberg, Lehrstuhl fur
Programmiersprachen, Erlangen, Germany

"Latticed RBF Networks:  An Alternative to Constructive Methods."
Brian Bonnlander & Michael C. Mozer, Department of Computer Science &
Institute of Cognitive Science, University of Colorado, Boulder, CO

"A Boundary Hunting Radial Basis Function Classifier which Allocates
Centers Constructively."
Eric I. Chang & Richard P. Lippmann, MIT Lincoln Laboratory, Lexington, MA

"How Hints affect Learning"
Yaser Abu-Mostafa, Dept of Electrical Engineering & Computer Science,
California Institute of Technology, Pasadena, CA
CONTROL, NAVIGATION & PLANNING
"Explanation-Based Neural Network Learning for Robot Control."
Tom M. Mitchell & Sebastian B. Thrun, School of Computer Science,
Carnegie Mellon University, Pittsburgh, PA

"Reinforcement Learning Applied to Linear Quadratic Regulation."
Steven J. Bradtke, Department of Computer & Information Science,
University of Massachusetts, Amherst, MA

"Neural Network On-Line Learning Control of Spacecraft Smart Structure."
Dr. Christopher Bowman, Ball Aerospace Systems Group, Boulder, CO

"Integration of Visual and Somatosensory Information for Preshaping Hand
in Grasping Movements."
Yoji Uno*, Naohiro Fukumura%, Ryoji Suzuki%, and Mitsuo Kawato*
*ATR Human Information Processing Research Laboratories, Kyoto, Japan
%Faculty of Engineering, University of Tokyo, Tokyo, Japan

"On-Line Estimation of the Optimal Value Function:  HJB-Estimators."
James K. Peterson, Department of Mathematical Sciences, Clemson
University, Clemson, SC

"Robust Control Under Extreme Uncertainty."
Vijaykumar Gullapalli, CS Department, LGRC, University of Massachusetts,
Amherst, MA

"Trajectory Relaxation Learning for Approximation of Robot Inverse Dynamics."
T. Sanger, MIT, Cambridge, MA

"Learning Spatio-Temporal Planning from a Dynamic Programming Teacher: 
A Feed Forward Net for the Moving Obstacle Avoidance Problem."
G. Fahner and R. Eckmiller, Department of Biophysics, Division of
Biocybernetics, Heinrich-Heine-University of Dusseldorf, Dusseldorf,
Germany

"Learning Fuzzy Rule-Based Neural Networks for Control."
Rodney M. Goodman and Charles M. Higgins, Department of Electrical
Engineering, Cal. Tech., Pasadena, CA


VISUAL PROCESSING

"Computation of Stereo Disparity for Transparent and for Opaque Surfaces."
Suthep Madarasmi*, Daniel Kersten%, Ting-Cheun Pong*
*Computer Science Department,
%Department of Psychology,
*Computer Science Department, University of Minnesota, Minneapolis, MN

"Some Solutions to the Missing Feature Problem in Vision."
Sabutai Ahmad and Volker Tresp, Seimens Research, Munich, Germany

"Improving Convergence in Hierarchial Matching Networks for Object
Recognition."
Joachim Utans and Gene Gindi, Yale University

"An LGN Model Which Mediates Communication Between Different Spatial
Frequency Channels Through Feedback From Cortex."
Carlos D. Brody, Computation and Neural Systems Program, Cal. Tech.,
Pasadena, CA

"Unsmearing Visual Motion:  Development of Long-Range Horizontal
Intrinsic Connections."
Kevin E. Martin and Jonathan A. Marshall, Department of Computer
Science, University of North Carolina, Chapel Hill, NC

"LandSat Image Analysis via a Texture Classification Neural Network."
Hayit K. Greenspan and Rodney M. Goodman, Department of Electrical
Engineering, Cal. Tech., Pasadena, CA

"Computation of Ego-Motion from Optic Flow in Visual Cortex."
Markus Lappe and Josef P. Rauschecker, National Institutes of Health
Animal Center, NIMH, Poolesville, MD, and Max Planck Institute for
Biological Cybernetics, Tubingen, Germany

"Learning to See Where and What:  A Backprop Net Trained to Make
Saccades and Recognize Characters."
Gale L. Martin, Mosfeq Rashid, David Chapman & James Pittman, MCC, Austin, TX

STOCHASTIC LEARNING AND ANALYSIS

"Bayesian Learning via Stochastic Dynamics.'
Radford M. Neal, Department of Computer Science, University of Toronto,
Toronto, Canada

"Accelerating Learning Using Query by Committee."
Yoav Freund*, H. Sebastian Seung%, and Naftali Tishby+
*Computer and Info. Sciences, UC Santa Cruz
%Racah Inst. of Physics and Ctr. for Neural Computation, Hebrew
University, Jerusalem
+Department of Computer Science and Ctr. for Neural Computation, Hebrew
University, Jerusalem

"Synaptic Weight Noise During MLP Learning Enhances Fault-Tolerance."
Alan F. Murray and Peter J. Edwards, Dept. of Electrical Engineering,
University of Edinburgh, Scotland

"Self-Stabilizing Hebbian Learning:  Beyond Principal Components."
Nicol N. Schraudolph* and Terrence J. Sejnowski%
*Computer Science & Engr. Department, UC San Diego
%Computational Neurobiology Laboratory, The Salk Institute, La Jolla, CA

"Probability Densities and Basin-Hopping in Stochastic Learning."
Todd K. Leen and Genevieve B. Orr, Department of Computer Science and
Engineering, Oregon Graduate Institute of Science and Technology,
Beaverton, OR

"Information Theoretic Analysis of Connection Structure from Spike Trains."
S. Shiono, S. Yamada,  M. Nakashima, and Kenji Matsumoto, Central
Research Laboratory, Mitsubishi Electric Corp., Hyogo, Japan

"Statistical Mechanics of Learning in a Large Committee Machine."
H. Schwarze and J. Hertz, The Niels Bohr Institute and Nordita,
Copenhagen, Denmark

"Probability Estimation from a Database Using a Gibbs Energy Model."
John W. Miller and Rodney M. Goodman, Department of Electrical Engr.,
Cal. Tech., Pasadena, CA

"On the Use of Evidence in Bayesian Reasoning."
David H. Wolpert, The Santa Fe Institute, Santa Fe, NM



NETWORK DYNAMICS & CHAOS

"Destabilization and Route to Chaos in Neural Networks with Random
Connectivity."
B. Doyon*, B. Cessac%+, M. Quoy%$, M. Samuelides%$
*Unite INSERM 230, Service de Neurologie, CHU Purpan, ToulouseCedex, France
%Centre d'Etudes et de Recherches de Toulouse, Toulouse Cedex, France
+Laboratoire de Physique Quantique, Universite Paul Sabatier, Toulouse
Cedex, France
$Ecole Nationale Superieure de l'Aeronautique et de l'Espace, Toulouse
Cedex, France

"Predicting Complex Behavior in Space Asymmetric Networks.'
Ali A. Minai and William B. Levy, Department of Neurosurgery, University
of Virginia, Charlottesville, VA

"Single-iteration Threshold Hamming Networks."
I. Meilijosn, E. Ruppin, M. Sipper, School of Mathematical Sciences, Tel
Aviv University, Tel Aviv, Israel

"History-Dependent Dynamics in Attractor Neural Networks:  A Bayesian
Approach."

Isaac Meilijosn and Eytan Ruppin, School of Mathematical Sciences, Tel
Aviv University, Tel Aviv, Israel

"Bifurcation Analysis of a Coupled Neural Oscillator System With
Application to Visual Cortex Modeling."

Galina N. Borisyuk, Roman M. Borisyuk, Alexander I. Khibnki, Institute
of Mathematical Problems of Biology, Russia Academy of Sciences,
Pushchino, Russia

"Non-Linear Dimensionality Reduction."
David DeMers and Garrison Cottrell, Department of Computer Science, UC
San Diego, La Jolla, CA


THEORY AND ANALYSIS

"On Learning m-Perceptron Networks with Binary Weights."
Mostefa Golea*, Mario Marchand* and Thomas R. Hancock%
*Ottawa-Carleton Institute for Physics, University of Ottawa, Ottawa, Canada
%Aiken Computation Laboratory, Harvard University, Cambridge, MA

"Neural Network Model Selection Using Asymptotic Jackknife Estimator and
Cross-Validation Method."
Yong Liu, Department of Physics and Center for Neural Science, Brown
University, Providence, RI

"Learning Curves, Model Selection and Complexity of Neural Networks."
Noboru Murata, Shuji Yoshizawa, and Shun-ichi Amari, Department of
Mathematical Engineering and Information Physics, University of Tokyo,
Japan

"The Power of Approximating:  A Comparison of Activation Functions."
Dhaskar DasGupta and Georg Schnitger, Department of Computer Science,
The Pensylvania State University, Unviersity Park, PA

"Rational Parameterizations of Neural Networks."
Uwe Helmke* and Robert C. Williamson%
*Department of Mathematics, University of Regensburg, Regensburg, Germany
%Department of Systems Engineering, Australian National University,
Canberra Australia

"Learning Cellular Automaton Dynamics with Neural Networks."
N. H. Wulff and J. A. Hertz, CONNECT, The Niels Bohr Institute and
Nordita, Copenhagen, Denmark

"Some Estimations of Necessary Number of Connections and Hidden Units
for Feed Forward Networks."
Adam Kowalczyk, Telcom Australia, Research Laboratories, Victoria, Australia


WEDNESDAY EVENING:  SESSION 2

COMPLEXITY, LEARNING AND GENERALIZAITON 2

"Automatic Capacity Tuning of Very Large VC-Dimension Classifiers."
I. Gunyon, B. Boser*, V. Vapnik, AT& T Bell Laboratories, Holmdel, NJ
*currently in EECS Department, UC Berkeley, CA

"Local Computation of the Second Derivative Information in a Multi-Layer
Network."
Patrice Y. Simard, Yann Le Cun and Barak Pearlmutter*
AT&T Bell Laboratories, Holmdel, NJ
*Yale University, New Haven, CT

"Improving Performance in Neural Networks Using a Boosting Algorithm."
H. Drucker, R. Schapire & P. Simard, AT&T Bell Labs, Holmdel, NJ

"Learning Classification With Few Labelled Examples."
Joel Ratsaby and Santosh S. Venkatesh, Department of Electrical
Engineering, University of Pennsylvania, Philadelphia, PA

"Second Order Derivatives for Network Pruning:  Optimal Brain Surgeon."
Babak Hassibi and David G. Stork, Ricoh California Research Center,
Menlo Park, CA, and Department of Electrical Engineering, Stanford
University, Stanford, CA

"Directional-Unit Boltzmann Machines."
Richard S. Zemel, Christopher K. I. Williams and Michael C. Mozer*
Computer Science Department, University of Toronto, Toronto, Canada
*Computer Science Department, University of Colorado, Boulder, CO

"Applying Classical Optimization Techniques to Neural Network Testing."
Dr. Scott A. Markel and Dr. Roger L. Crane, David Sarnoff Research
Center, Princeton, NJ

"Time Warping Invariant Neural Networks."
G. Z. Sun, H. H. Chen, Y. C. Lee and Y. D. Liu, Institute for Advanced
Computer Studies / Laboratory for Plasma Research, University of
Maryland, College Park, MD

"Generalization Abilities of Cascade Network Architectures."
E. Littmann and H. Ritter, Department of Computer Science, Bielefeld
University, Bielefeld, Germany

"Assessing and Improving Neural Network Predictions by the Bootstrap
Algorithm."
Gerhard Paa', German National Research Center for Computer Science,
Augustin, Germany

"Discriminability-Based Transfer between Neural Networks."
L. Y. Pratt, Department of Matheamatics and Computer Science, Colorado
School of mines, Golden, CO

"Summed Weight Neuron Perturbation:  An O(N) Improvement over Weight
Perturbation."
Barry Flower and Marwan Jabri, SEDAL, Department of Electrical
Engineering, University of Sydney, Australia

"Supervised Clustering."
Virginia de Sa and Dana Ballard, Computer Science Department, University
of Rochester, Rochester, NY

"Extended Regularization Methods for Nonconvergent Model Selection."
W. Finnoff, F. Hergert and H. G. Zimmerman, Siemans AG, Corporate
Research and Development, Munich, Germany

"Synchronization and Gramatical Inference in an Oscillating Elman Net."
Bill Baird* and Frank Eeckman%
*Department of Mathematics, UC Berkeley, CA
%O-Division, Lawrence Livermore National Laboratory, Livermore, CA

"Training Hidden Units in Reinforcement Learning Networks."
Charles W. Anderson, Department of Computer Science, Colorado State
University, Fort Collins, CO

"Nets with Unreliable Hidden Nodes Learn Error-Correcting Codes."
Stephen Judd and Paul Munro, Seimens Corporate Research, Princeton, NJ,
and Department of Information Science, University of Pittsburgh, PA

"A Fast Stochastic Error-Descent Algorithm for Supervised Learning and
Optimization."
Gert Cauwenberghs, Cal. Tech., Pasadena, CA


SPEECH AND SIGNAL PROCESSING

"Modeling Consistency in a Speaker Independent Continuous Speech
Recognition System."
Yochai Konig*, Nelson Morgan*, Chuck Wooters*, Victor Abrash%, Michael
Cohen%, and Horacio Franco%
*International Computer Science Institute, Berkeley, CA
%SRI International, Menlo Park, CA

"A Hybrid Linear/Nonlinear Approach to Channel Equalization Problems."
Wei-Tsih Lee*, John C. Pearson*, and Manoel F. Tenorio%
*David Sarnoff Research Center, Princeton, NJ
%Purdue University, School of Electrical Engineering, West Lafayette, IN
"Transient Detection Using Neural Networks:  The Search for the Desired
Signal."
Abir Zahalka and Jose C. Principe, Computational NeuroEngineering
Laboratory, University of Florida, Gainesville, FL

"Performance Through Consistency:  MS-TDNN's for Large Vocabulary
Continuous Speech Recognition."
Joe Tebelskis and Alex Waibel, School of Computer Science, Carnegie
Mellon University, Pittsburgh, PA

"Speech Recognition Using Segmental Neural Nets with the N-Best Paradigm."
G. Zavaliagkos, S. Austin, J. Makhous and R. Schwartz, BBN Systems and
Technologies, Cambridge, MA

"Connected Letter Recognition with a Multi-State Time Delay Neural Network."
Hermann Hild and Alex Waibel, School of Computer Science, Carnegie
Mellon University, Pittsburgh, PA

"Classification of Electroencephalogram Using Artificial Neural Networks."
A. C. Tsoi, D. S. C. So, and A. Sergejew, Department of Electrical
Engineering, University of Queensland, Queensland, Australia

"Classification of Satellite Multi-Spectral Image Data by the Binary
Diamond Neural Network."
Yehuda Salu, The Physics Department and CSTEA, Howard University,
Washington, DC

"Silicon Auditory Processors as Computer Peripherals."
John Lazzaro*, John Wawrzynek*, M. Mahowald%, Massimo Sivilotti+, and
Dave Gillespie+
*Computer Science Division, UC Berkeley, CA
%Computation and Neural Sciences, Cal. Tech, Pasadena, CA
+Computer Science, Cal. Tech., Pasadena, CA

"Object-Based Analog VLSI Vision Circuits."
Christof Koch*, Bimal Mathur%, Shih-Chii Liu+, John G. Harris$, Jin Luo
and Missimo Sivilotti$
*Computation and Neural Systems, Cal. Tech., Pasadena, CA
%Rockwell International Science Center, Thousand Oaks, CA
+Artificial Intelligence Laboratory, MIT, Cambridge, MA
$Tanner Research, Pasadena, CA

"A Parallel Gradient Descent Method for Learning in Analog VLSI Neural
Networks."
Joshua Alspector, Ronny Meir, Ben Yuhas, Anthony Jayakumar, Bellcore,
Morristown, NJ



APPLICATIONS

"Dynamic Planar Warping and Planar Hidden Markov Modeling:  From Speech
to Optical Character Recognition."
Esther Levin and Roberto Pieraccini, AT&T Bell Laboratories, Murray Hill, NJ

"Forecasting Demand for Electric Power."
Terrence L. Fine and Jen-Lun Yuan, School of Electrical Engineering,
Cornell University, Ithaca, NY

"Adaptive Algorithms for Multiple Sequence Alignments."
Pierre Baldi*, Tim Hunkapiller*, Yves Chauvin%, and Marcella McClure+
*Cal. Tech, Pasadena, CA
%Net-ID, Inc.
+UC, Irvine

"A Neural Network that Learns to Interpret Myocardial Planar Thallium
Scintigrams."
Charles Rosenberg*, Jacob Erel%, and Henri Atlan%
*Department of Computer Science, Hebrew University, Jerusalem, Israel
%Department of Biophysics and Nuclear Medicine, Hadassah Medical Center,
Jeruslaem, Israel


IMPLEMENTATIONS

"An Analog VLSI Chip for Local Velocity Estimation Based on Reichardt's
Motion Algorithm."
Rahul Sarpeshkar, Wyeth Bair and Christof Koch, Department of
Computation and Neural Systems, Cal. Tech., Pasadena, CA

"Analog VLSI Implementation of Gradient Descent."
David Kirk, Douglas Kerns, Kurt Fleischer, Alan Barr
Cal. Tech., Pasadena, CA

"An Object-oriented Framework and its Implementation for the Simulation
of Neural Nets."
Alexander Linden and Christoph Tietz, AI Research Division, German
National Research Center For Computer Science, Augustin, Germany

"Attractor Neural Networks with Local Inhibition."
L. D'Alessandro*, E. Pasero*, and R. Zecchina%
*Dipart. Elettronica, Politenico di Torino
%Dipart. Fisica Teorica, Universita di Torino

"Biological Neurons and Model Neurons:  Construction and Study of Hybrid
Networks."
G. Le Masson, S. Renaud-Le Masson, E. Marder, and L. F. Abbot
Department of Biology and Physics and Center for Complex Systems,
Brandeis University, Waltham, MA


COGNITIVE SCIENCE

"A Connectionist Chunker that Induces the Structure of Context-Free Languages."
Michael C. Mozer and Sreerupa Das, Department of Computer Science and
Institute of Cognitive Science, University of Colorado, Boulder, CO

"Network Structuring and Training Using Rule-Based Knowledge."
Volker Tresp*, Jurgen Hollatz%, and Subutai Ahmad*
*Siemens AG, Central Research and Development, Munich, Germany
%Institut fur Informatik, Munich Germany

"A Dynamic Model of Priming and Repetition Blindness.'
Daphne Bavelier and Michael I. Jordan, Department of Brain and
CCognitive Sciences, MIT, Cambridge, MA

"A Knowledge-Based Model of Geometry Learning."
Geoffrey Towell* and Richard Lehrer%
*Siemens Corporate Research, Princeton, NJ
%Educational Psychology, University of Wisconsin, Madison, WI

"Representing Meaning With Activation Gestalts."
Hinrich Schutze, CSLI, Stanford, CA

"Perceiving Complex Visual Scenes:  An Oscillator Neural Network Model
that Integrates Location-Based Attention, Perceptual Organization, and
Object-Based Selection."
Rainer Goebel, Department of Psychology, University of Braunschweig,
Braunschweig, Germany


COMPUTATIONAL AND THEORETICAL NEUROBIOLOGY

"Statistical Modeling of Cell-Assembly Activities in Prefrontal Cortex
of Behaving Monkeys."
Itay Gutterman and Naftali, Department of Computer Science and Center
for Neural Comuptation, Hebrew University, Jerusalem, Israel

 "Towards Unambiguous Derivation of Receptive Fields Using a New
Optimal-Encoding Criterion."
Ralph Linsker, IBM, T. J. Watson Research Center, Yorktown Heights, NY

"Biologically Plausible Learning Rules for the Vestibulo-Ocular Reflex (VOR)."
Oliver Coenen*, Terrence J. Sejnowski*, and Stephen G. Lisberger%
*Computational Neurobilogy Laboratory, The Salk Institute, La Jolla, CA
%Department of Physiology, W. M. Keck Foundation Center for Integrative
Neuroscience; and Neuroscience Graduata Program, UC San Francisco, CA

"A Non-Hebbian LTP Learning Rule in Hippocampus Enables High-Capacity
Temporal Sequence Encoding."
Richard Granger, James W. Whitson, Jr., and Gary Lynch, Center for the
Neurobiology of Learning and Memory, UC Irvine, CA

"Using Aperiodic Reinforcement for Directed Self Organization."
P. Read Montague, Steven J. Nowlan, Peter Dayan and Terrance J.
Sejnowski, Computational Neurobiology Laboratory, The Salk Institute,
San Diego, CA

"Information Processing in Neocortical Pyramidal Cells."
Bartlett W. Mel, Computation and Neural Systems Program, Cal. Tech.,
Pasadena, CA

"How Oscillatory Neuronal Responses Reflect Bistability and Switching of
the Hidden Assembly Dynamics."
K. Pawelzik, H.-U. Bauer, J. Deppisch, and T. Geisel, Institute fur
Theoretische Physik and SFP, Frankfurt, Germany

"Topography and Ocular Dominance: A New Model that Explores Positive
Between-Eye Correlations."
Geoffrey Goodhill, University of Edinburgh, Centre for Cognitive
Science, Edinburgh, Scotland

"Statistical and Dynamical Interpretation of ISIH Data from Periodically
Stimulated Sensory Neurons."
Frank Moss* and Andre Longtin%
*Department of Physics and Department of Biology, University of
Missouri, St. Louis, MO
%Department of Physics, University of Ottawa, Canada

"Modelling Movement Disorders with Cascaded Jordan Networks."
Alexander Britain*, Gordon D. A. Brown*, Michael Malloch* and Ian J. Mitchell%
*Cognitive Neurocomputation Unit, Dept. of Psychology, University of
Wales, Bangor, United Kingdom
%Department of Cell and Structural Biology, Manchester, United Kingdom

"Spiral Waves in Integrate-And-Fire Neural Networks."
John G. Milton*, Po Hsiang Chu% and Jack D. Cowan+
*Department of Neurology, University of Chicago, Chicago, IL
%Department of Computer Science, De Paul University, Chicago, IL
+Department of Mathematics, University of Chicago, Chicago, IL

"Parameterising Feature Sensitive Cell Formation in Linsker Networks."
L. C. Walton and D. L. Bisset, Electronic Engineering Laboratories,
University of Kent, United Kingdom

"A Recurrent Neural Network for Generation of Ocular Saccades."
Lina L. E. Massone, Departments of Physiology and Electrical Engineering
and Computer Science, Northwestern University, Chicago, IL

"A Formal Model of the Insect Olfactory Macroglomerulus."
C. Linster*, C. Masson%, M. Kerszberg+, L. Personnaz*, and G. Dreyfus*
*Ecole Superieure de Physique et de Chimie Industrielles de la Villa De
Paris, Laboratoire d'Electronique, Paris, France
%Laboratoire de Neurobiologie Comparees des Invertebres, INRA?CNRS,
Bures Sur Yvette, France
+Institut Pasteur, Paris, France

"An Information-Theoretic Approach to Deciphering the Hippocampal Code."
William E. Skaggs, Bruce L. McNaughton, Katalin M. Gothard, Etan J.
Marksu, ARL Division of Neural Systems, Memory and Aging, University of
Arizona, Tuscan, AZ