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» Bayesian Inference for Sparse Generalized Linear Models
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ICASSP
2011
IEEE
14 years 5 months ago
USPACOR: Universal sparsity-controlling outlier rejection
The recent upsurge of research toward compressive sampling and parsimonious signal representations hinges on signals being sparse, either naturally, or, after projecting them on a...
Georgios B. Giannakis, Gonzalo Mateos, Shahrokh Fa...
ECCV
2008
Springer
16 years 3 months ago
Constrained Maximum Likelihood Learning of Bayesian Networks for Facial Action Recognition
Probabilistic graphical models such as Bayesian Networks have been increasingly applied to many computer vision problems. Accuracy of inferences in such models depends on the quali...
Cassio Polpo de Campos, Yan Tong, Qiang Ji
BMCBI
2008
159views more  BMCBI 2008»
15 years 2 months ago
Multivariate hierarchical Bayesian model for differential gene expression analysis in microarray experiments
Background: Identification of differentially expressed genes is a typical objective when analyzing gene expression data. Recently, Bayesian hierarchical models have become increas...
Hongya Zhao, Kwok-Leung Chan, Lee-Ming Cheng, Hong...
CVPR
2004
IEEE
16 years 3 months ago
Representation and Matching of Articulated Shapes
We consider the problem of localizing the articulated and deformable shape of a walking person in a single view. We represent the non-rigid 2D body contour by a Bayesian graphical...
Jiayong Zhang, Robert T. Collins, Yanxi Liu
NIPS
2008
15 years 3 months ago
Learning Bounded Treewidth Bayesian Networks
With the increased availability of data for complex domains, it is desirable to learn Bayesian network structures that are sufficiently expressive for generalization while at the ...
Gal Elidan, Stephen Gould