216 search results - page 17 / 44 » Learning in Gaussian Markov random fields |
132
Voted
ICML
2004
IEEE
16 years 4 months ago
2004
IEEE
In many application domains there is a large amount of unlabeled data but only a very limited amount of labeled training data. One general approach that has been explored for util...
205
Voted
SIAMIS
2010
14 years 10 months ago
2010
Markov random field (MRF) models, including conditional random field models, are popular in computer vision. However, in order to be computationally tractable, they are limited to ...
137
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CVPR
2007
IEEE
16 years 5 months ago
2007
IEEE
Considerable advances have been made in learning to recognize and localize visual object classes. Simple bag-offeature approaches label each pixel or patch independently. More adv...
140
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CIKM
2009
Springer
15 years 10 months ago
2009
Springer
This paper addresses the issue of social recommendation based on collaborative filtering (CF) algorithms. Social recommendation emphasizes utilizing various attributes informatio...
101
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UAI
2004
15 years 4 months ago
2004
Ancestral graph models, introduced by Richardson and Spirtes (2002), generalize both Markov random fields and Bayesian networks to a class of graphs with a global Markov property ...