• DocumentCode
    1265709
  • Title

    Clamping in Boltzmann machines

  • Author

    Livesey, Mike

  • Author_Institution
    Dept. of Comput. Sci., St. Andrews Univ., UK
  • Volume
    2
  • Issue
    1
  • fYear
    1991
  • fDate
    1/1/1991 12:00:00 AM
  • Firstpage
    143
  • Lastpage
    148
  • Abstract
    A certain assumption that appears in the proof of correctness of the standard Boltzmann machine learning procedure is investigated. The assumption, called the clamping assumption, concerns the behavior of a Boltzmann machine when some of its units are clamped to a fixed state. It is argued that the clamping assumption is essentially an assertion of the time reversibility of a certain Markov chain underlying the behavior of the Boltzmann machine. As such, the clamping assumption is generally false, though it is certainly true of the Boltzmann machines themselves. The author also considers how the concept of the Boltzmann machine may be generalized while retaining the validity of the clamping assumption
  • Keywords
    Markov processes; learning systems; neural nets; Boltzmann machines; Markov chain; clamping assumption; learning; time reversibility; Clamps; Computer science; Machine learning; Probability distribution; Simulated annealing; State-space methods; Stochastic processes; Stochastic systems;
  • fLanguage
    English
  • Journal_Title
    Neural Networks, IEEE Transactions on
  • Publisher
    ieee
  • ISSN
    1045-9227
  • Type

    jour

  • DOI
    10.1109/72.80301
  • Filename
    80301