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» Generalized Belief Propagation
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UAI
2003
13 years 10 months ago
Approximate Inference and Constrained Optimization
Loopy and generalized belief propagation are popular algorithms for approximate inference in Markov random fields and Bayesian networks. Fixed points of these algorithms correspo...
Tom Heskes, Kees Albers, Bert Kappen
JAIR
2006
143views more  JAIR 2006»
13 years 8 months ago
Convexity Arguments for Efficient Minimization of the Bethe and Kikuchi Free Energies
Loopy and generalized belief propagation are popular algorithms for approximate inference in Markov random fields and Bayesian networks. Fixed points of these algorithms have been...
Tom Heskes
CVPR
2008
IEEE
14 years 10 months ago
Efficient mean shift belief propagation for vision tracking
A mechanism for efficient mean-shift belief propagation (MSBP) is introduced. The novelty of our work is to use mean-shift to perform nonparametric mode-seeking on belief surfaces...
Minwoo Park, Yanxi Liu, Robert T. Collins
NIPS
2001
13 years 10 months ago
Information Geometrical Framework for Analyzing Belief Propagation Decoder
The mystery of belief propagation (BP) decoder, especially of the turbo decoding, is studied from information geometrical viewpoint. The loopy belief network (BN) of turbo codes m...
Shiro Ikeda, Toshiyuki Tanaka, Shun-ichi Amari
UAI
2008
13 years 10 months ago
Convergent Message-Passing Algorithms for Inference over General Graphs with Convex Free Energies
Inference problems in graphical models can be represented as a constrained optimization of a free energy function. It is known that when the Bethe free energy is used, the fixedpo...
Tamir Hazan, Amnon Shashua