Uncertainty in Artificial Intelligence
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On the optimality of tree-reweighted max-product message-passing
Vladimir Kolmogorov, Martin Wainwright
Tree-reweighted max-product (TRW) message passing is a modified form of the ordinary max-product algorithm for attempting to find minimal energy configurations in Markov random field with cycles. For a TRW fixed point satisfying the strong tree agreement condition, the algorithm outputs a configuration that is provably optimal. In this paper, we focus on the case of binary variables with pairwise couplings, and establish stronger properties of TRW fixed points that satisfy only the milder condition of weak tree agreement (WTA). First, we demonstrate how it is possible to identify part of the optimal solution|i.e., a provably optimal solution for a subset of nodes| without knowing a complete solution. Second, we show that for submodular functions, a WTA fixed point always yields a globally optimal solution. We establish that for binary variables, any WTA fixed point always achieves the global maximum of the linear programming relaxation underlying the TRW method.
Pages: 316-323
PS Link:
PDF Link: /papers/05/p316-kolmogorov.pdf
AUTHOR = "Vladimir Kolmogorov and Martin Wainwright",
TITLE = "On the optimality of tree-reweighted max-product message-passing",
BOOKTITLE = "Proceedings of the Twenty-First Conference Annual Conference on Uncertainty in Artificial Intelligence (UAI-05)",
ADDRESS = "Arlington, Virginia",
YEAR = "2005",
PAGES = "316--323"

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