THE STATISTICAL-MECHANICS OF LEARNING A RULE

TLH WATKIN*, A RAU, M BIEHL

*Corresponding author for this work

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Abstract

A summary is presented of the statistical mechanical theory of learning a rule with a neural network, a rapidly advancing area which is closely related to other inverse problems frequently encountered by physicists. By emphasizing the relationship between neural networks and strongly interacting physical systems, such as spin glasses, the authors show how learning theory has provided a workshop in which to develop new, exact analytical techniques.

Original languageEnglish
Pages (from-to)499-556
Number of pages58
JournalReviews of Modern Physics
Volume65
Issue number2
DOIs
Publication statusPublished - Apr-1993

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