Parallel Boltzmann machines : a mathematical model

P.J. Zwietering; E.H.L. Aarts

doi:10.1016/0743-7315(91)90110-U

Parallel Boltzmann machines : a mathematical model

P.J. Zwietering, E.H.L. Aarts

Research output: Contribution to journal › Article › Scientific › peer-review

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Abstract

A mathematical model is presented for the description of parallel Boltzmann machines. The framework is based on the theory of Markov chains and combines a number of previously known results into one generic model. It is argued that parallel Boltzmann machines maximize a function consisting of a weighted sum of the well-known consensus function and a pseudoconsensus function. The weighting is determined by the amount of parallelism used in the Boltzmann machine and turns out to be problem dependent.

Original language	English
Pages (from-to)	65-75
Number of pages	11
Journal	Journal of Parallel and Distributed Computing
Volume	13
Issue number	1
DOIs	https://doi.org/10.1016/0743-7315(91)90110-U
Publication status	Published - 1991
Externally published	Yes

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10.1016/0743-7315(91)90110-U

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title = "Parallel Boltzmann machines : a mathematical model",

abstract = "A mathematical model is presented for the description of parallel Boltzmann machines. The framework is based on the theory of Markov chains and combines a number of previously known results into one generic model. It is argued that parallel Boltzmann machines maximize a function consisting of a weighted sum of the well-known consensus function and a pseudoconsensus function. The weighting is determined by the amount of parallelism used in the Boltzmann machine and turns out to be problem dependent.",

author = "P.J. Zwietering and E.H.L. Aarts",

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AU - Aarts, E.H.L.

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AB - A mathematical model is presented for the description of parallel Boltzmann machines. The framework is based on the theory of Markov chains and combines a number of previously known results into one generic model. It is argued that parallel Boltzmann machines maximize a function consisting of a weighted sum of the well-known consensus function and a pseudoconsensus function. The weighting is determined by the amount of parallelism used in the Boltzmann machine and turns out to be problem dependent.

U2 - 10.1016/0743-7315(91)90110-U

DO - 10.1016/0743-7315(91)90110-U

M3 - Article

SN - 0743-7315

VL - 13

SP - 65

EP - 75

JO - Journal of Parallel and Distributed Computing

JF - Journal of Parallel and Distributed Computing

IS - 1

ER -

Parallel Boltzmann machines : a mathematical model

Abstract

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