DocumentCode
1144021
Title
Beyond the binary Boltzmann machine
Author
Anderson, N.H. ; Titterington, D.M.
Author_Institution
Dept. of Stat., Glasgow Univ., UK
Volume
6
Issue
5
fYear
1995
fDate
9/1/1995 12:00:00 AM
Firstpage
1229
Lastpage
1236
Abstract
The definition of the usual Boltzmann machine is extended to allow for neurons with polytomous (multicategory) rather than simply binary responses. Updating rules are defined along with the associated stationary distributions, and an alternating minimization method is described for the purposes of training. Emphasis is placed on the relevance of statistical ideas, including polytomous logistic regression, the iterative proportional fitting procedure and the EM algorithm
Keywords
Boltzmann machines; iterative methods; minimisation; recurrent neural nets; statistical analysis; EM algorithm; alternating minimization method; binary Boltzmann machine; iterative proportional fitting procedure; polytomous logistic regression; polytomous responses; Information geometry; Iterative algorithms; Logistics; Minimization methods; Neurons; Probability distribution; State-space methods; Statistics; Stochastic processes; Terminology;
fLanguage
English
Journal_Title
Neural Networks, IEEE Transactions on
Publisher
ieee
ISSN
1045-9227
Type
jour
DOI
10.1109/72.410364
Filename
410364
Link To Document