Boltzmann Machines : High-Order Interactions and Synchronous Learning

  • Robert Azencott
Part of the Lecture Notes in Statistics book series (LNS, volume 74)


A now classical innovative paper [H.S.A.] by Hinton-Sejnowski-Ackley intro­duced a class of formal neural networks, the Boltzmann machines, governed by asynchronous stochastic dynamics, quadratic energy functions, and pairwise interac­tions defined by synaptic weights. One of the exciting aspects of [H.S.A.] was the derivation of a locally implementable learning rule linked to a scheme of decreasing (artificial) temperatures, in the spirit of simulated annealing.


Learning Rule Gibbs Distribution Stochastic Network Boltzmann Machine Random Configuration 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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Copyright information

© Springer-Verlag Berlin Heidelberg 1992

Authors and Affiliations

  • Robert Azencott
    • 1
    • 2
  1. 1.École Normale Supérieure (DIAM) and Université Paris-SudFrance
  2. 2.CNRS labs: [LMENS] and [Stat. App. Univ. Paris-Sud]Paris Cedex 05France

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