Maximum Likelihood Bounded Tree-Width Markov Networks

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.

• Type: Conference
• Year: 2001
• Where: UAI
• Authors: Nathan Srebro
• Keywords: Combinatorial Optimization Problem, Maximum Likelihood Distribution, Maximum Weight Hypertree, UAI 2001, UAI 2008