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Learning the parameters of graphical models using the maximum likelihoodestimation is generally hard which requires an approximation. Maximum compositelikelihood estimations are statistical approximations of the maximum likelihoodestimation which are higher-order generalizations of the maximumpseudo-likelihood estimation. In this paper, we propose a composite likelihoodmethod and investigate its property. Furthermore, we apply our compositelikelihood method to restricted Boltzmann machines.

Composite Likelihood Estimation for Restricted Boltzmann machines