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Maximum likelihood bounded tree-width Markov networks
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DOI：10.1016/S0004-3702(02)00360-0.png)
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Abstract
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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. (C) 2002 Elsevier Science B.V All rights reserved.
Keywords:
Markov networks
Markov random fields
undirected graphical models
entropy decomposition
hyper-trees
tree-width
hardness
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