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...
Main Authors: | Kumar, MP, Torr, PHS |
---|---|
פורמט: | Conference item |
שפה: | English |
יצא לאור: |
Association for Computing Machinery
2008
|
פריטים דומים
-
An analysis of convex relaxations for MAP estimation
מאת: Kumar, MP, et al.
יצא לאור: (2008) -
Analyzing convex relaxations for map estimation
מאת: Kumar, MP, et al.
יצא לאור: (2011) -
An analysis of convex relaxations for MAP estimation of discrete MRFs
מאת: Pawan Kumar, M, et al.
יצא לאור: (2009) -
Solving Markov random fields using second order cone programming relaxations
מאת: Kumar, MP, et al.
יצא לאור: (2006) -
Improved moves for truncated convex models
מאת: Kumar, MP, et al.
יצא לאור: (2009)