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Efficient exact inference in planar Ising models

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Schraudolph, Nicol
Kamenetsky, Dmitry

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MIT Press

Abstract

We give polynomial-time algorithms for the exact computation of lowest-energy states, worst margin violators, partition functions, and marginals in certain binary undirected graphical models. Our approach provides an interesting alternative to the well-known graph cut paradigm in that it does not impose any submodularity constraints; instead we require planarity to establish a correspondence with perfect matchings in an expanded dual graph. Maximum-margin parameter estimation for a boundary detection task shows our approach to be efficient and effective. A C++ implementation is available from http://nic.schraudolph.org/isinf/.

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Advances in Neural Information Processing Systems 21

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2037-12-31