Efficiently solving convex relaxations for MAP estimation
<p>The problem of obtaining the maximum <em>a posteriori</em> (MAP) estimate of a discrete random field is of fundamental importance in many areas of Computer Science. In this work, we build on the tree reweighted message passing (TRW) framework of (Kolmogorov, 20...
Prif Awduron: | Kumar, MP, Torr, PHS |
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Fformat: | Conference item |
Iaith: | English |
Cyhoeddwyd: |
Association for Computing Machinery
2008
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Eitemau Tebyg
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An analysis of convex relaxations for MAP estimation
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Analyzing convex relaxations for map estimation
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An analysis of convex relaxations for MAP estimation of discrete MRFs
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Solving Markov random fields using second order cone programming relaxations
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Improved moves for truncated convex models
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