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...
Κύριοι συγγραφείς: | Kumar, MP, Torr, PHS |
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Μορφή: | Conference item |
Γλώσσα: | English |
Έκδοση: |
Association for Computing Machinery
2008
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Παρόμοια τεκμήρια
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An analysis of convex relaxations for MAP estimation
ανά: Kumar, MP, κ.ά.
Έκδοση: (2008) -
Analyzing convex relaxations for map estimation
ανά: Kumar, MP, κ.ά.
Έκδοση: (2011) -
An analysis of convex relaxations for MAP estimation of discrete MRFs
ανά: Pawan Kumar, M, κ.ά.
Έκδοση: (2009) -
Solving Markov random fields using second order cone programming relaxations
ανά: Kumar, MP, κ.ά.
Έκδοση: (2006) -
Improved moves for truncated convex models
ανά: Kumar, MP, κ.ά.
Έκδοση: (2009)