Logistic regression and the Boltzmann machine

A derivation of the learning algorithm for the Boltzmann machine is presented. It uses a statistical tool called logistic regression, in which the connection strengths in the Boltzmann machine correspond to the parameters of the logistic model. The use of maximum-likelihood estimates for the parameters leads to the standard learning algorithm for the Boltzmann machine and may be easily extended to N-way connections. This formulation makes explicit the contribution of higher-order connections and has sparked research into analysis of the tradeoff between their increased learning power and the increased number of connections they require