specification of a probability distribution function. The model can then be trained by maximiz-ing the log likelihood. In this family of model, perhaps the most succesful is the deep Boltzmann machine [25]. Such models generally have intractable likelihood functions and therefore require numerous approximations to the likelihood gradient.
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