Factorization of Discrete Probability Distributions

Published 12 Dec 2012 in cs.AI | (1301.0568v1)

Abstract: We formulate necessary and sufficient conditions for an arbitrary discrete probability distribution to factor according to an undirected graphical model, or a log-linear model, or other more general exponential models. This result generalizes the well known Hammersley-Clifford Theorem.

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