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MAP estimation in Binary MRFs via Bipartite Multi-cuts

MAP estimation in Binary MRFs via Bipartite Multi-cuts

This video was recorded at 24th Annual Conference on Neural Information Processing Systems (NIPS), Vancouver 2010. We propose a new LP relaxation for obtaining the MAP assignment of a binary MRF with pairwise potentials. Our relaxation is derived from reducing the MAP assignment problem to an instance of a recently proposed Bipartite Multi-cut problem where the LP relaxation is guaranteed to provide an log k approximation where k is the number of vertices adjacent to non-submodular edges in the MRF. We then propose a combinatorial algorithm to efficiently solve the LP and also provide a lower bound by concurrently solving its dual to within an epsilon approximation. The algorithm is up to an order of magnitude faster and provides better MAP scores and bounds than the state of the art message passing algorithm that tightens the local marginal polytope with third-order marginal constraints.


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