Abstract :
We study the problem of projecting a distribution onto (or finding a maximum likelihood distribution among) Markov networks of bounded tree-width. By casting it as the combinatorial optimization problem of finding a maximum weight hypertree, we prove that it is NP-hard to solve exactly and provide an approximation algorithm with a provable performance guarantee.
Keywords :
Entropy decomposition , Hyper-trees , Tree-width , Hardness , Undirected graphical models , Markov Networks , Markov random fields