273 search results - page 14 / 55 » Learning the Structure of Deep Sparse Graphical Models |
125
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CVPR
2003
IEEE
16 years 3 months ago
2003
IEEE
Probabilistic models have been adopted for many computer vision applications, however inference in highdimensional spaces remains problematic. As the statespace of a model grows, ...
140
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CVPR
2011
IEEE
14 years 10 months ago
2011
IEEE
Nearly every structured prediction problem in computer vision requires approximate inference due to large and complex dependencies among output labels. While graphical models prov...
106
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TSP
2010
14 years 8 months ago
2010
The problem of learning tree-structured Gaussian graphical models from independent and identically distributed (i.i.d.) samples is considered. The influence of the tree structure a...
123
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CVPR
2004
IEEE
16 years 3 months ago
2004
IEEE
This paper proposes a new framework for image segmentation based on the integration of MRFs and deformable models using graphical models. We first construct a graphical model to r...
139
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JMLR
2012
13 years 4 months ago
2012
Constructing tractable dependent probability distributions over structured continuous random vectors is a central problem in statistics and machine learning. It has proven diffic...