An analysis of convex relaxations for MAP estimation
The problem of obtaining the maximum a posteriori estimate of a general discrete random field (i.e. a random field defined using a finite and discrete set of labels) is known to be NP-hard. However, due to its central importance in many applications, several approximate algorithms have been proposed...
Главные авторы: | Kumar, MP, Kolmogorov, V, Torr, PHS |
---|---|
Формат: | Conference item |
Язык: | English |
Опубликовано: |
Curran Associates
2008
|
Схожие документы
-
Analyzing convex relaxations for map estimation
по: Kumar, MP, и др.
Опубликовано: (2011) -
An analysis of convex relaxations for MAP estimation of discrete MRFs
по: Pawan Kumar, M, и др.
Опубликовано: (2009) -
Efficiently solving convex relaxations for MAP estimation
по: Kumar, MP, и др.
Опубликовано: (2008) -
Improved moves for truncated convex models
по: Kumar, MP, и др.
Опубликовано: (2009) -
Solving Markov random fields using second order cone programming relaxations
по: Kumar, MP, и др.
Опубликовано: (2006)