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...
Principais autores: | Kumar, MP, Torr, PHS |
---|---|
Formato: | Conference item |
Idioma: | English |
Publicado em: |
Association for Computing Machinery
2008
|
Registros relacionados
-
An analysis of convex relaxations for MAP estimation
por: Kumar, MP, et al.
Publicado em: (2008) -
Analyzing convex relaxations for map estimation
por: Kumar, MP, et al.
Publicado em: (2011) -
An analysis of convex relaxations for MAP estimation of discrete MRFs
por: Pawan Kumar, M, et al.
Publicado em: (2009) -
Solving Markov random fields using second order cone programming relaxations
por: Kumar, MP, et al.
Publicado em: (2006) -
Improved moves for truncated convex models
por: Kumar, MP, et al.
Publicado em: (2009)