A parallel algorithm for Boltzmann machines
type: Item
instance of: scholarly article
title: A parallel algorithm for Boltzmann machines
zbMATH Open document ID: 0753.65055
author: Takashi Yozawa
published in: Osaka Journal of Mathematics
publication date: 1992-09-27T00:00:00Z
review text: The Boltzmann machine is a neural network model for which the author suggests a new synchronously parallel algorithm. The sequential Boltzmann machine calculates the Gibbs distribution of the energy function over the configuration space whence we can solve the optimization problem of the energy function by generally using the simulated annealing technique. But this last algorithm does not exploit the parallelism of the Boltzmann machine. The proposed algorithms are independent of the connection pattern and ensure that the equilibrium distributions are the Gibbs distributions and thus guarantee that they solve the optimization problems. The method is being tested by computer simulations. Reviewer's remark: I suggest to compare it with a new deterministic global optimization method (called Alienor) allowing to obtain good approximations of global minima.
Mathematics Subject Classification ID: 65K10
Mathematics Subject Classification ID: 65Y05
zbMATH DE Number: 59011
zbMATH Keywords: Boltzmann machine
zbMATH Keywords: neural network model
zbMATH Keywords: parallel algorithm
zbMATH Keywords: Gibbs distribution
zbMATH Keywords: energy function
zbMATH Keywords: simulated annealing technique
zbMATH Keywords: computer simulations
reviewed by: Yves Cherruault
MaRDI profile type: Publication
description: scientific article; zbMATH DE number 59011