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Since 1985, the methods of statistical mechanics have been successfully applied to the theory of neural networks. The current status of the statistical physics of neural networks was reviewed at the workshop upon which this book is based, and propsects for the future examined. Recent interdisciplinary development with related fields such as computational learning theory, statistics, information theory, and nonlinear dynamics are also presented. Key Contributors include S. Amari, H. Sompolinsky, Y. LeCun, I. Kanter, D. Haussler, H. S. Seung, M. Opper, M. Kearns and M. Biehl.
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