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...
| 主要な著者: | , |
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| フォーマット: | Conference item |
| 言語: | English |
| 出版事項: |
Association for Computing Machinery
2008
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