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...
Asıl Yazarlar: | Kumar, MP, Torr, PHS |
---|---|
Materyal Türü: | Conference item |
Dil: | English |
Baskı/Yayın Bilgisi: |
Association for Computing Machinery
2008
|
Benzer Materyaller
-
An analysis of convex relaxations for MAP estimation
Yazar:: Kumar, MP, ve diğerleri
Baskı/Yayın Bilgisi: (2008) -
Analyzing convex relaxations for map estimation
Yazar:: Kumar, MP, ve diğerleri
Baskı/Yayın Bilgisi: (2011) -
An analysis of convex relaxations for MAP estimation of discrete MRFs
Yazar:: Pawan Kumar, M, ve diğerleri
Baskı/Yayın Bilgisi: (2009) -
Solving Markov random fields using second order cone programming relaxations
Yazar:: Kumar, MP, ve diğerleri
Baskı/Yayın Bilgisi: (2006) -
Improved moves for truncated convex models
Yazar:: Kumar, MP, ve diğerleri
Baskı/Yayın Bilgisi: (2009)