Efficiently solving convex relaxations for MAP estimation

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...

書誌詳細
主要な著者:	Kumar, MP, Torr, PHS
フォーマット:	Conference item
言語:	English
出版事項:	Association for Computing Machinery 2008

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