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...

Полное описание

Библиографические подробности
Главные авторы:	Kumar, MP, Torr, PHS
Формат:	Conference item
Язык:	English
Опубликовано:	Association for Computing Machinery 2008

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