2001 Recipient: Geoffrey 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.