A Graphical Transformation for Belief Propagation: Maximum Weight Matchings and Odd-Sized Cycles

NeurIPS 2013 Jinwoo ShinAndrew E. GelfandMisha Chertkov

Max-product ‘belief propagation’ (BP) is a popular distributed heuristic for finding the Maximum A Posteriori (MAP) assignment in a joint probability distribution represented by a Graphical Model (GM). It was recently shown that BP converges to the correct MAP assignment for a class of loopy GMs with the following common feature: the Linear Programming (LP) relaxation to the MAP problem is tight (has no integrality gap)... (read more)

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