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---------- Forwarded message ----------
Date: Fri, 04 May 2001 13:27:21 -0400
From: David E. Rumelhart Prize <derprize@cnbc.cmu.edu>
To: derprize@cnbc.cmu.edu
Subject: First Recipient of the David E. Rumelhart Prize Announced

             Geoffrey E. Hinton Chosen as First Recipient
                  of the David E. Rumelhart Prize
   for Contributions to the Formal Analysis of Human Cognition

The Glushko-Samuelson Foundation and the Cognitive Science Society are
pleased to announce that Geoffrey E. Hinton has been chosen as the
first recipient of the David E. Rumelhart Prize for contributions to
the formal analysis of human cognition.  Hinton was chosen for his
many important contributions to the analysis of neural networks,
elucidating the nature of representation, processing, and learning in
the brain.  In a landmark early book with James Anderson (1), he
pioneered the use of distributed representations and described how
they can be used for semantic knowledge representation (2).  With
Terrence J. Sejnowski (3), he introduced the Boltzmann Machine, an
important neural network architecture for finding globally optimal
solutions to difficult constraint satisfaction problems, and with
Sejnowski and Ackley (4) he proposed a learning algorithm for use in
such networks.  With David Rumelhart and Ronald Williams (5), he
introduced the back-propagation learning algorithm and made clear how
it could be used to discover useful representations capturing the
underlying structure of a body of structured propositional
information.  He has gone on from this important early work to make
many further contributions to the field of neural networks, including
studies of mixtures of experts (6) and Helmholtz machines (7).  His
publication list includes more than 100 articles on these and a wide
range of other topics.  Beyond these contributions, Hinton is an
outstanding mentor and advisor: 18 graduate students have earned the
Ph. D. degree under his supervision.

Hinton to Deliver Prize Lecture at the Edinburgh Meeting of the
Cognitive Science Society in August, 2001

Geoffey Hinton will receive the First David E. Rumelhart Prize and
deliver the first Rumelhart Prize Lecture in Edinburgh, Scotland at
the Annual Meeting of the Cognitive Science Society, to be held August
1-4 in Edinburgh, Scotland.  The Prize itself will consist of a
certificate, a citation of the awardee's contribution, and a monetary
award of $100,000.  Information on this year's meeting is available
at http://www.hcrc.ed.ac.uk/cogsci2001/.

The David E. Rumelhart Prize to be Awarded Annually

When established in August of 2000, the David E. Rumelhart Prize was
to be awarded bienially for outstanding contributions to the formal
analysis of human cognition.  Upon reviewing the pool of individuals
nominated to receive the prize, the Glushko-Samuelson Foundation, in
consultation with the Governing Board of the Cognitive Science
Society, came to the conclusion that an annual prize is warranted.
With the aid of the Prize Selection Committee (listed below), the
foundation determined that there exists a large pool of outstanding
candidates representing each of the approaches to the formal analysis
of human cognition identified in the prize announcement: mathematical
modeling of human cognitive processes, formal analysis of language and
other products of human cognitive activity, and computational analyses
of human cognition using symbolic and non-symbolic frameworks.
Awarding the prize annually should facilitate the timely recognition
of major contributions arising within each of these approaches.

The recipient of the second David E. Rumelhart Prize will be announced
at the Cognitive Science Society Meeting in Edinburgh, with the
second prize lecture to be given at the following meeting of the
society at George Mason University in July, 2002.

Prize Selection Committee

The membership of the prize selection committee was selected in
consultation with the Distinguished Advisory Board (William Estes,
Barbara Partee, and Herbert Simon).  The members of the prize
selection committee are Allan Collins, Bolt, Beranek and Newman and
Northwestern University; Robert J. Glushko, Glushko-Samuelson
Foundation; Mark Liberman, University of Pennsylvania; Anthony
J. Marley, McGill University; and James L. McClelland (Chair),
Carnegie Mellon.

Brief Biography of Geoffrey E. Hinton

Geoffrey Hinton received his BA in experimental psychology from
Cambridge in 1970 and his PhD in Artificial Intelligence from
Edinburgh in 1978.  He did postdoctoral work at Sussex University and
the University of California, San Diego and spent five years as a
faculty member in the Computer Science department at Carnegie-Mellon
University.  He then moved to Toronto where he was a fellow of the
Canadian Institute for Advanced Research and a Professor in the
Computer Science and Psychology departments.  He is a former president
of the Cognitive Science Society, and he is a fellow of the Royal
Society (UK), the Royal Society of Canada, and the American
Association for Artificial Intelligence.  In 1992 he won the
ITAC/NSERC award for contributions to information technology.

Hinton is currently Director of the Gatsby Computational Neuroscience
Unit at University College London, where he leads an outstanding group
of faculty, post-doctoral research fellows, and graduate students
investigating the computational neural mechanisms of perception and
action with an emphasis on learning.  His current main interest is in
unsupervised learning procedures for neural networks with rich sensory
input.

Cited Publications by Geoffrey E. Hinton

(1) Hinton, G. E. and Anderson, J. A. (1981) Parallel Models of
Associative Memory, Erlbaum, Hillsdale, NJ.

(2) Hinton, G. E. (1981) Implementing semantic networks in parallel
hardware. In Hinton, G. E. and Anderson, J. A. (Eds.), Parallel Models
of Associative Memory, Erlbaum, Hillsdale, NJ.

(3) Hinton, G. E. and Sejnowski, T. J. (1983) Optimal perceptual
inference.  Proceedings of the IEEE conference on Computer Vision and
Pattern Recognition, Washington DC.

(4) Ackley, D. H., Hinton, G. E., and Sejnowski, T. J. (1985) A
learning algorithm for Boltzmann machines.  Cognitive Science, 9,
147--169.

(5) Rumelhart, D. E., Hinton, G. E., and Williams, R. J. (1986)
Learning representations by back-propagating errors.  Nature, 323,
533--536.

(6) Jacobs, R., Jordan, M. I., Nowlan. S. J. and Hinton, G. E. (1991)
Adaptive mixtures of local experts.  Neural Computation, 3, 79-87

(7) Hinton, G. E., Dayan, P., Frey, B. J. and Neal, R. (1995) The
wake-sleep algorithm for unsupervised Neural Networks.  Science, 268,
pp 1158-1161.

Visit the David E. Rumelhart Prize Website at:
     http://www.cnbc.cmu.edu/derprize










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