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ECCV
2008
Springer
14 years 6 months ago
Efficiently Learning Random Fields for Stereo Vision with Sparse Message Passing
As richer models for stereo vision are constructed, there is a growing interest in learning model parameters. To estimate parameters in Markov Random Field (MRF) based stereo formu...
Jerod J. Weinman, Lam Tran, Christopher J. Pal
JAIR
2011
114views more  JAIR 2011»
12 years 7 months ago
Properties of Bethe Free Energies and Message Passing in Gaussian Models
We address the problem of computing approximate marginals in Gaussian probabilistic models by using mean field and fractional Bethe approximations. We define the Gaussian fracti...
Botond Cseke, Tom Heskes
CVPR
2011
IEEE
13 years 28 days ago
Learning Message-Passing Inference Machines for Structured Prediction
Nearly every structured prediction problem in computer vision requires approximate inference due to large and complex dependencies among output labels. While graphical models prov...
Stephane Ross, Daniel Munoz, J. Andrew Bagnell
JMLR
2010
164views more  JMLR 2010»
12 years 11 months ago
Solving the Uncapacitated Facility Location Problem Using Message Passing Algorithms
The Uncapacitated Facility Location Problem (UFLP) is one of the most widely studied discrete location problems, whose applications arise in a variety of settings. We tackle the U...
Nevena Lazic, Brendan J. Frey, Parham Aarabi
CORR
2010
Springer
166views Education» more  CORR 2010»
13 years 4 months ago
The dynamics of message passing on dense graphs, with applications to compressed sensing
`Approximate message passing' algorithms proved to be extremely effective in reconstructing sparse signals from a small number of incoherent linear measurements. Extensive num...
Mohsen Bayati, Andrea Montanari