An LP View of the M-best MAP problem

Neural Information Processing Systems 

We consider the problem of finding the M assignments with maximum probability in a probabilistic graphical model. We show how this problem can be formulated as a linear program (LP) on a particular polytope. We prove that, for tree graphs (and junction trees in general), this polytope has a particularly simple form and differs from the marginal polytope in a single inequality constraint. We use this characterization to provide an approximation scheme for non-tree graphs, by using the set of spanning trees over such graphs. The method we present puts the M -best inference problem in the context of LP relaxations, which have recently received considerable attention and have proven useful in solving difficult inference problems.