216 search results - page 33 / 44 » Learning in Gaussian Markov random fields |
125
Voted
JMLR
2010
14 years 10 months ago
2010
Contrastive Divergence (CD) is a popular method for estimating the parameters of Markov Random Fields (MRFs) by rapidly approximating an intractable term in the gradient of the lo...
142
Voted
ECCV
2006
Springer
16 years 5 months ago
2006
Springer
Abstract. Bayesian inference provides a powerful framework to optimally integrate statistically learned prior knowledge into numerous computer vision algorithms. While the Bayesian...
123
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ICCV
2003
IEEE
16 years 5 months ago
2003
IEEE
This paper presents a multi-scale generative model for representing animate shapes and extracting meaningful parts of objects. The model assumes that animate shapes (2D simple clo...
118
Voted
CVPR
2008
IEEE
16 years 5 months ago
2008
IEEE
Prior distributions are useful for robust low-level vision, and undirected models (e.g. Markov Random Fields) have become a central tool for this purpose. Though sometimes these p...
166
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KDD
2007
ACM
16 years 3 months ago
2007
ACM
A wide variety of machine learning problems can be described as minimizing a regularized risk functional, with different algorithms using different notions of risk and different r...