schedule for the upcoming NIPS conference

Wed Sep 7 22:49:31 EDT 1988

A copy of the preliminary schedule for the upcoming NIPS conference
(November 28-December 1, with workshops December 1-3) appears below.  NIPS
is a single-track, purely scientific conference.  The program committee,
chaired by Scott Kirkpatrick, was very selective: only 25% of submissions
were accepted this year.  There will be 25 oral presentations and 60
posters.  The proceedings will be available around the end of April '89,
but they can be ordered now from Morgan Kaufmann Publishers, P.O. Box
50490, Palo Alto, CA 94303-9953; tel. 415-578-9911.  Prepublication price
is $33.95, plus $2.25 postage ($4.00 for overseas orders).  California
residents must add sales tax.  Specify that you want "Advances in Neural
Information Processing Systems".

		 PRELIMINARY PROGRAM, NIPS '88

	      Denver, November 29-December 1, 1988

			   Tuesday AM
			   __________

SESSION O1:  Learning and Generalization
________________________________________

Invited Talk

8:30 O1.1:  "Birdsong  Learning", Mark Konishi,  Division of
Biology, California Institute of Technology

Contributed Talks

9:10 O1.2:  "Comparing Generalization by Humans and Adaptive
Networks", M.  Pavel, M.A.  Gluck, V. Henkle,  Department of
Psychology, Stanford University

9:40 O1.3:  "An Optimality Principle for Unsupervised Learn-
ing", T. Sanger, AI Lab, MIT

10:10 Break

10:30 O1.4:   "Learning by  Example  with  Hints", Y.S.  Abu-
Mostafa, California  Institute of Technology,  Department of
Electrical Engineering

11:00 O1.5:   "Associative Learning  Via Inhibitory  Search",
D.H. Ackley, Cognitive Science Research Group, Bell Communi-
cation Research, Morristown NJ

11:30 O1.6:   "Speedy Alternatives  to Back  Propagation", J.
Moody, C. Darken, Computer  Science Department, Yale Univer-
sity

		   Tuesday PM
		   __________

12:00 Poster Preview I

SESSION P1A:  Learning and Generalization
_________________________________________

P1A.1:  "Efficient  Parallel Learning Algorithms  for Neural
Networks", A. Kramer,  Prof. A. Sangiovanni-Vincentelli, De-
partment of EECS, U.C. Berkeley

P1A.2:   "Properties of  a Hybrid  Neural Network-Classifier
System", Lawrence  Davis, Bolt Beranek and  Newman Laborato-
ries, Cambridge, MA

P1A.3:  "Self Organizing Neural Networks For The Identifica-
tion Problem",  M.R. Tenorio, Wei-Tsih Lee,  School of Elec-
trical Engineering, Purdue University

P1A.4:  "Comparison  of Multilayer Networks and  Data Analy-
sis",   P.  Gallinari,   S.   Thiria,  F.   Fogelman-Soulie,
Laboratoire  d'Intelligence Artificielle,  Ecole des  Hautes
Etudes  en  Informatique, Universite'  de  Paris  5, 75  006
Paris, France

P1A.5:  "Neural  Networks and Principal  Component Analysis:
Learning from Examples, without  Local Minima", P. Baldi, K.
Hornik, Department of Mathematics, University of California,
San Diego

P1A.6:   "Learning by  Choice of  Internal Representations",
Tal Grossman, Ronny Meir,  Eytan Domany, Department of Elec-
tronics, Weizmann Institute of Science

P1A.7:   "What size  Net  Gives  Valid Generalization?",  D.
Haussler, E.B. Baum, Department  of Computer and Information
Sciences, University of California, Santa Cruz

P1A.8:   "Mean  Field  Annealing and  Neural  Networks",  G.
Bilbro, T.K. Miller, W. Snyder, D. Van den Bout, M White, R.
Mann,  Department of  Electrical  and Computer  Engineering,
North Carolina State University

P1A.9:   "Connectionist Learning  of  Expert Preferences  by
Comparison Training", G. Tesauro,  University of Illinois at
Urbana-Champign, Champaign, IL

P1A.10:  "Dynamic Hypothesis Formation in Connectionist Net-
works", M.C.  Mozer, Department  of Psychology  and Computer
Science, University of Toronto

P1A.11:  "Digit Recognition  Using a Multi-Architecture Feed
Forward Neural  Network", W.R.  Gardner, L.  Pearlstein, De-
partment of Electrical Engineering, University of Delaware

P1A.12:  "The  Boltzmann Perceptron:  A  Multi-Layered Feed-
Forward Network, Equivalent to  the Boltzmann Machine", Eyal
Yair, Allen  Gersho, Center  For Information  Processing Re-
search, University of California

P1A.13:  "Adaptive  Neural-Net Preprocessing for  Signal De-
tection   in  Non-Gaussian   Noise",  R.P.   Lippmann,  P.E.
Beckmann, MIT Lincoln Laboratory, Lexington, MA

P1A.14:  "Training Multilayer  Perceptrons with the Extended
Kalman Algorithm",  S. Singhal,  L. Wu,  Bell Communications
Research, Morristown, NJ

P1A.15:  "GEMINI: Gradient  Estimation through Matrix Inver-
sion after  Noise Injection",  Y. LeCun, C.C.  Galland, G.E.
Hinton, Computer Science Department, University of Toronto

P1A.16:   "Analysis  of   Recurrent  Backpropagation",  P.Y.
Simard, M.B.  Ottaway, D.H. Ballard, Department  of Computer
Science, University of Rochester

P1A.17:  "Scaling  and Generalization in Neural  Networks: a
Case Study", Subutai Ahmad,  Gerald Tesauro, Center for Com-
plex  Systems Research,  University of  Illinois at  Urbana-
Champaign

P1A.18:   "Does the  Neuron "Learn"  Like the  Synapse?", R.
Tawel,  Jet Propulsion  Laboratory, California  Institute of
Technology

P1A.19:   "Experiments  on  Network Learning  by  Exhaustive
Search", D.  B. Schwartz,  J. S. Denker,  S. A.  Solla, AT&T
Bell Laboratories, Holmdel, NJ

P1A.20:  "Some  Comparisons of Constraints for  Minimal Net-
work  Construction,  with   Backpropagation",  Stephen  Jose
Hanson,  Lorien  Y.  Pratt,  Bell  Communications  Research,
Morristown, NJ

P1A.21:  "Implementing the  Principle of Maximum Information
Preservation:  Local Algorithms for Biological and Synthetic
Networks", Ralph Linsker, IBM Thomas J. Watson Research Cen-
ter, Yorktown Heights, NY

P1A.22:  "Biological Implications  of a Pulse-Coded Reformu-
lation  of  Klopf's  Differential-, Hebbian  Learning  Algo-
rithm", M.A. Gluck, D.  Parker, E. Reifsnider, Department of
Psychology, Stanford University

SESSION P1B:  Applications
__________________________

P1B.1:  "Comparison of Two LP Parametic Representations in a
Neural Network-based, Speech Recognizer", K.K. Paliwal, Tata
Institute  of   Fundamental  Research,  Homi   Bhabha  Road,
Bombay-400005, India

P1B.2:  "Nonlinear Dynamical Modeling of Speech Using Neural
Networks", N.  Tishby, AT&T Bell Laboratories,  Murray Hill,
NJ

P1B.3:   "Use of  Multi-Layered Networks  for Coding  Speech
with Phonetic  Features", Y. Bengio,  R. De Mori,  School of
Computer Science, McGill University

P1B.4:  "Speech Production Using Neural Network with Cooper-
ative Learning  Mechanism", M.  Komura, A.  Tanaka, Interna-
tional Institute  for Advanced  Study of  Social Information
Science, Fujitsu Limited, Japan

P1B.5:  "Temporal Representations  in a Connectionist Speech
System", E.J.  Smythe, Computer Science  Department, Indiana
University

P1B.6:  "TheoNet:  A Connectionist Network Implementation of
a Solar Flare Forecasting Expert System (Theo)", R. Fozzard,
L. Ceci, G. Bradshaw, Department  of Computer Science & Psy-
chology, University of Colorado at Boulder

P1B.7:   "An Information  Theoretic  Approach to  Rule-Based
Connectionist Expert Systems", R.M. Goodman, J.W. Miller, P.
Smyth, Department  of Electrical Engineering  California In-
stitute of Technology, Pasadena, CA

P1B.8:   "Neural TV  Image Compression  Using Hopfield  Type
Networks",   M.   Naillon,   J.B.   Theeten,   G.   Nocture,
Laboratoires d'Electronique et de Physique Appliquee (LEP1),
France

P1B.9:  "Neural  Net Receivers in  Spread-Spectrum Multiple-
Access Communication  Systems", B.P.  Paris, G.  Orsak, M.K.
Varanasi, B.  Aazhang, Department  of Electrical  & Computer
Engineering, Rice University

P1B.10:   "Performance of  Synthetic Neural  Network Classi-
fication of Noisy Radar Signals", I. Jouny, F.D. Garber, De-
partment   of  Electrical   Engineering,   The  Ohio   State
University

P1B.11:   "The  Neural  Analog  Diffusion-Enhancement  Layer
(NADEL)  and  Early  Visual, Processing",  A.M.  Waxman,  M.
Seibert, Laboratory for Sensory Robotics, Boston University

P1B.12:  "A Cooperative Network  for color Segmentation", A.
Hurlbert, T. Poggio, Center for Biological Information Proc-
essing, Whitaker College

P1B.13:   "Neural  Network   Star  Pattern  Recognition  for
Spacecraft Attitude Determination, and Control", P. Alvelda,
M.A.  San Martin,  C.E. Bell,  J.Barhen, The  Jet Propulsion
Laboratory, California Institute of Technology,

P1B.14:  "Neural Networks that Learn to Discriminate Similar
Kanji  Characters", Yoshihiro  Mori, Kazuhiko  Yokosawa, ATR
Auditory and Visual Perception Research Laboratories, Osaka,
Japan

P1B.15:  "Further Explorations in  the Learning of Visually-
Guided Reaching:  Making, MURPHY Smarter", B.W.  Mel, Center
for Complex Systems Research, University of Illinois

P1B.16:  "Using  Backpropagation to Learn the  Dynamics of a
Real Robot Arm", K.  Goldberg, B. Pearlmutter, Department of
Computer Science, Carnegie-Mellon University

SESSION O2:  Applications
_________________________

Invited Talk

2:20 O2.1:  "Speech  Recognition," John Bridle,  Royal Radar
Establishment, Malvern, U.K.

Contributed Talks

3:00 O2.2:  "Modularity in Neural Networks for Speech Recog-
nition," A. Waibel, Carnegie Mellon University

3:30 O2.3:  "Applications of  Error Back-propagation to Pho-
netic Classification,"  H.C. Leung, V.W. Zue,  Department of
Electrical Eng. & Computer Science, MIT

4:00 O2.4:  "Neural Network  Recognizer for Hand-Written Zip
Code  Digits: Representations,,  Algorithms, and  Hardware,"
J.S.  Denker,  H.P.  Graf,  L.D.  Jackel,  R.E.  Howard,  W.
Hubbard, D.  Henderson, W.R. Gardner, H.S.  Baird, I. Guyon,
AT&T Bell Laboratories, Holmdel, NJ

4:30 O2.5:  "ALVINN: An Autonomous  Land Vehicle in a Neural
Network,"  D.A.  Pomerleau,   Computer  Science  Department,
Carnegie Mellon University

5:00 O2.6:   "A Combined  Multiple  Neural Network  Learning
System for the Classification  of, Mortgage Insurance Appli-
cations and Prediction of  Loan Performance," S. Ghosh, E.A.
Collins, C. L. Scofield, Nestor Inc., Providence, RI

8:00 Poster Session I

		  Wednesday AM
		  ____________

SESSION O3:  Neurobiology
_________________________

Invited Talk

8:30 O3.1:  "Cricket  Wind Detection," John  Miller, Depart-
ment of Zoology, UC Berkeley

Contributed Talks

9:10 O3.2:   "A Passive,  Shared  Element Analog  Electronic
Cochlea," D.  Feld, J. Eisenberg, E.R.  Lewis, Department of
Electrical   Eng.   &   Computer  Science,   University   of
California, Berkeley

9:40 O3.3:  "Neuronal Maps for  Sensory-motor Control in the
Barn  Owl," C.D.  Spence, J.C.  Pearson, J.J.  Gelfand, R.M.
Peterson, W.E. Sullivan, David Sarnoff Research Ctr, Subsid-
iary of SRI International, Princeton, NJ

10:10 Break

10:30 O3.4:  "Simulating Cat  Visual Cortex: Circuitry Under-
lying  Orientation  Selectivity,"  U.J. Wehmeier,  D.C.  Van
Essen, C. Koch, Division of Biology, California Institute of
Technology

11:00 O3.5:  Model of Ocular Dominance Column Formation: Ana-
lytical  and  Computational,  Results,"  K.D.  Miller,  J.B.
Keller, M.P.  Stryker, Department of  Physiology, University
of California, San Francisco

11:30 O3.6:  "Modeling  a Central Pattern Generator  in Soft-
ware and Hardware:, Tritonia in Sea Moss," S. Ryckebusch, C.
Mead,  J. M.  Bower, Computational  Neural Systems  Program,
Caltech

		  Wednesday PM
		  ____________

12:00 Poster Preview II

SESSION P2A:  Structured Networks
_________________________________

P2A.1:  "Training  a 3-Node Neural Network  is NP-Complete,"
A. Blum, R.L. Rivest, MIT Lab for Computer Science

P2A.2:   "A  Massively   Parallel  Self-Tuning  Context-Free
Parser,"  E. Santos  Jr.,  Department  of Computer  Science,
Brown University,

P2A.3:  "A  Back-Propagation Algorithm  With Optimal  Use of
Hidden Units," Y. Chauvin,  Thomson CSF, Inc./ Stanford Uni-
versity

P2A.4:   "Analyzing  the  Energy Landscapes  of  Distributed
Winner-Take-All Networks," D.S.  Touretzky, Computer Science
Department, Carnegie Mellon University

P2A.5:  "Dynamic, Non-Local Role Bindings and Inferencing in
a Localist Network For Natural Language Understanding," T.E.
Lange, M.G. Dyer, Computer Science Department, University of
California, Los Angeles

P2A.6:   "Spreading  Activation Over  Distributed  Microfea-
tures," J. Hendler, Department  of Computer Science, Univer-
sity of Maryland

P2A.7:  "Short-term Memory as a Metastable State: A Model of
Neural Oscillator  For A Unified Submodule,"  A.B. Kirillov,
G.N. Borisyuk, R.M. Borisyuk, Ye.I. Kovalenko, V.I. Kryukov,
V.I. Makarenko,  V.A. Chulaevsky, Research  Computer Center,
USSR Academy of Sciences

P2A.8:  "Statistical  Prediction with Kanerva's  Sparse Dis-
tributed Memory," D. Rogers, Research Institute for Advanced
Computer Science, NASA Ames Research Ctr, Moffett Field, CA

P2A.9:  "Image  Restoration By  Mean Field  Annealing," G.L.
Bilbro, W.E. Snyder, Dept.  of Electrical and Computer Engi-
neering, North Carolina State University

P2A.10:  "Automatic  Local Annealing," J.  Leinbach, Depart-
ment of Psychology, Carnegie-Mellon University

P2A.11:  "Neural Networks for  Model Matching and Perceptual
Organization," E.  Mjolsness, G. Gindi, P.  Anandan, Depart-
ment of Computer Science, Yale University

P2A.12:  "On the k-Winners-Take-All Feedback Network and Ap-
plications,"  E. Majani,  R. Erlanson,  Y. Abu-Mostafa,  Jet
Propulsion Laboratory, California Institute of Technology,

P2A.13:  "An Adaptive Network that Learns Sequences of Tran-
sitions,"  C.L. Winter,  Science Applications  International
Corporation, Tucson, Arizona

P2A.14:   "Convergence  and   Pattern-Stabilization  in  the
Boltzmann Machine,"  M. Kam,  R. Cheng, Department  of Elec-
trical and Computer Eng., Drexel University

SESSION P2B:  Neurobiology
__________________________

P2B.1:  "Storage  of Covariance  By The  Selective Long-Term
Potentiation and  Depression of,  Synaptic Strengths  In The
Hippocampus", P.K.  Stanton, J.  Jester, S.  Chattarji, T.J.
Sejnowski, Department of Biophysics,  The Johns Hopkins Uni-
versity

P2B.2:  "A Mathematical Model of the Olfactory Bulb", Z. Li,
J.J. Hopfield, Division of  Biology, California Institute of
Technology

P2B.3:  "A  Model of Neural Control  of the Vestibulo-Ocular
Reflex", M.G. Paulin, S.Ludtke, M. Nelson, J.M. Bower, Divi-
sion of Biology, California Institute of Technology

P2B.4:  "Associative Learning in  Hermissenda:  A Lumped Pa-
rameter  Computer Model,  of Neurophysiological  Processes",
Daniel L. Alkon, Francis Quek, Thomas P. Vogl, Environmental
Research Institute of Michigan, Arlington, VA

P2B.5:  "Reconstruction of the Electric Fields of the Weakly
Electric Fish Gnathonemus, Petersii Generated During Explor-
atory  Activity", B.  Rasnow,  M.E. Nelson,  C. Assad,  J.M.
Bower, Department of Physics,  California Institute of Tech-
nology

P2B.6:  "A Model for Resolution Enhancement (Hyperacuity) in
Sensory Representation"  J. Miller, J. Zhang,  Department of
Zoology, University of California, Berkeley

P2B.7:  "Coding Schemes for  Motion Computation in Mammalian
Cortex", H.T. Wang, B.P.  Mathur, C. Koch, Rockwell Interna-
tional Science Ctr., Thousand Oaks, CA

P2B.8:  "Theory of Self-  Organization of Cortical Maps", S.
Tanaka,  NEC Corporation-  Fundamental  Res. Lab.,  Kawasaki
Kanagawa, 213 JAPAN

P2B.9:  "A Bifurcation Theory Approach to the Programming of
Periodic Attractors, in Network Models of Olfactory Cortex",

Bill   Baird,  Department   of  Biophysics,   University  of
California at Berkeley

P2B.10:  "Neuronal Cartography: population coding and resol-
ution enhancement,  through arrays of broadly  tuned cells",
Pierre Baldi,  Walter Heiligenberg, Department  of Mathemat-
ics, University of California, San Diego

P2B.11:  "Learning the Solution  to the Aperture Problem for
Pattern Motion with  a Hebb Rule", M.I.  Sereno, Division of
Biology, California Institute of Technology

P2B.12:  "A  Model for  Neural Directional  Selectivity that
Exhibits  Robust  Direction  of, Motion  Computation",  N.M.
Grzywacz,  F.R. Amthor,  Center  for Biological  Information
Processing, Whitaker College, Cambridge, MA

P2B.13:  "A  Low-Power CMOS Circuit which  Emulates Temporal
Electrical Properties of, Neurons",  J. Meador, C. Cole, De-
partment of Electrical  and Computer Engineering, Washington
State University

P2B.14:  "A General Purpose Neural Network Simulator for Im-
plementing  Realistic  Models   of  Neural  Circuits",  M.A.
Wilson, U.S. Bhalla, J.D. Uhley, J.M. Bower, Division of Bi-
ology, California Institute of Technology,

SESSION P2C:  Implementation
____________________________

P2C.1:   "MOS Charge  Storage  of  Adaptive Networks,"  R.E.
Howard, D.B. Schwartz, AT&T Bell Laboratories, Holmdel, NJ

P2C.2:  "A Self-Learning Neural Network," A. Hartstein, R.H.
Koch,  IBM-Thomas   J.  Watson  Research   Center,  Yorktown
Heights, NY

P2C.3:  "An  Analog VLSI Chip  for Cubic Spline  Surface In-
terpolation,"  J.G.  Harris,  Division  of  Computation  and
Neural Systems, California Institute of Technology

P2C.4:  "Analog Implementation of Shunting Neural Networks,"
B.  Nabet, R.B.  Darling, R.B.  Pinter, Department  of Elec-
trical Engineering University of Washington

P2C.5:  "Stability  of Analog Neural Networks  with Time De-
lay," C.M. Marcus, R.M. Westervelt, Division of Applied Sci-
ences, Harvard University

P2C.6:  "Analog subthreshold  VLSI circuit for interpolating
sparsely sampled 2-D, surfaces using resistive networks," J.
Luo, C. Koch, C. Mead, Division of Biology California Insti-
tute of Technology

P2C.7:  "A Physical Realization of the Winner-Take-All Func-
tion," J.  Lazzaro, C.A.  Mead, Computer  Science California
Institute of Technology

P2C.8:   "General   Purpose  Neural  Analog   Computer,"  P.
Mueller, J. Van der Spiegel, D. Blackman, J. Dao, C. Donham,
R. Furman, D.P. Hsieh, M. Loinaz, Department of Biochemistry
and Biophysics, University of Pennsylvania

P2C.9:  "A  Silicon Based  Photoreceptor Sensitive  to Small
Changes  in  Light  Intensity,"   C.A.  Mead,  T.  Delbruck,
California Institute of Technology Pasadena, CA

P2C.10:   "A Digital  Realisation of  Self-Organising Maps,"
M.J. Johnson,  N.M. Allinson,  K. Moon, Department  of Elec-
tronics, University of York, England

P2C.11:   "Training  of  a  Limited-Interconnect,  Synthetic
Neural IC," M.R. Walker,  L.A. Akers, Center for solid-State
Electronics Research, Arizona State University

P2C.12:   "Electronic Receptors  for Tactile  Sensing," A.G.
Andreou, Department of  Electrical and Computer Engineering,
The Johns Hopkins University

P2C.13:  "Cooperation in an Optical Associative Memory Based
on Competition,"  D.M. Liniger, P.J. Martin,  D.Z. Anderson,
Department  of   Physics  &   Joint  Inst.   for  Laboratory
Astrophysics, University of Colorado, Boulder

SESSION O4:  Computational Structures
_____________________________________

Invited Talk

2:20 O4.1:   "Symbol  Processing  in  the  Brain,"  Geoffrey
Hinton, Computer Science Department, University of Toronto

Contributed Talks

3:00 O4.2:  "Towards a Fractal Basis for Artificial Intelli-
gence,"  Jordan Pollack,  New Mexico  State University,  Las
Cruces, NM

3:30 O4.3:  "Learning Sequential  Structure In Simple Recur-
rent  Networks," D.  Servan-Schreiber,  A. Cleeremans,  J.L.
McClelland, Department  of Psychology,  Carnegie-Mellon Uni-
versity

4:00 O4.4:   "Short-Term   Memory  as  a   Metastable  State
"Neurolocator,"  A Model  of Attention",  V.I. Kryukov,  Re-
search Computer Center, USSR Academy of Sciences

4:30 O4.5:  "Heterogeneous Neural  Networks for Adaptive Be-
havior in Dynamic Environments," R.D. Beer, H.J. Chiel, L.S.
Sterling, Center  for Automation and Intelligent  Sys. Res.,
Case Western Reserve University, Cleveland, OH

5:00 O4.6:   "A Link  Between Markov  Models and  Multilayer
Perceptions," H. Bourlard,  C.J. Wellekens, Philips Research
Laboratory, Brussels, Belgium

7:00 Conference Banquet

9:00 Plenary Speaker

"Neural Architecture  and Function,"  Valentino Braitenberg,
Max Planck Institut fur Biologische Kybernetik, West Germany

		  Thursday AM
		  ___________

SESSION O5:  Applications
_________________________

Invited Talk

8:30 O5.1:   "Robotics,  Modularity, and  Learning,"  Rodney
Brooks, AI Lab, MIT

Contributed Talks

9:10 O5.2:   "The Local  Nonlinear  Inhibition Circuit,"  S.
Ryckebusch, J. Lazzaro, M. Mahowald, California Institute of
Technology, Pasadena, CA

9:40 O5.3:  "An Analog Self-Organizing Neural Network Chip,"
J. Mann, S. Gilbert, Lincoln Laboratory, MIT, Lexington, MA

10:10 Break

10:30 O5.4:   "Performance of  a  Stochastic Learning  Micro-
chip,"  J.  Alspector,  B.   Gupta,  R.B.  Allen,  Bellcore,
Morristown, NJ

11:00 O5.5:  "A Fast, New  Synaptic Matrix For Optically Pro-
grammed  Neural Networks,"  C.D. Kornfeld,  R.C. Frye,  C.C.
Wong, E.A. Rietman, AT&T Bell Laboratories, Murray Hill, NJ

11:30 O5.6:   "Programmable Analog  Pulse-Firing Neural  Net-
works," Alan F. Murray, Lionel Tarassenko, Alister Hamilton,
Department   of   Electrical  Engineering,   University   of
Edinburgh Scotland, UK

12:00 Poster Session II