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» From Margin to Sparsity
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DCC
2010
IEEE
14 years 2 months ago
Block Compressed Sensing of Images Using Directional Transforms
Block-based random image sampling is coupled with a projectiondriven compressed-sensing recovery that encourages sparsity in the domain of directional transforms simultaneously wi...
Sungkwang Mun, James E. Fowler
SIGPRO
2011
209views Hardware» more  SIGPRO 2011»
13 years 2 months ago
Surveying and comparing simultaneous sparse approximation (or group-lasso) algorithms
In this paper, we survey and compare different algorithms that, given an overcomplete dictionary of elementary functions, solve the problem of simultaneous sparse signal approxim...
A. Rakotomamonjy
ICASSP
2011
IEEE
12 years 11 months ago
A wideband doubly-sparse approach for MITO sparse filter estimation
We propose an approach for the estimation of sparse filters from a convolutive mixture of sources, exploiting the time-domain sparsity of the mixing filters and the sparsity of ...
Simon Arberet, Prasad Sudhakar, Rémi Gribon...
ICASSP
2011
IEEE
12 years 11 months ago
Fast adaptive variational sparse Bayesian learning with automatic relevance determination
In this work a new adaptive fast variational sparse Bayesian learning (V-SBL) algorithm is proposed that is a variational counterpart of the fast marginal likelihood maximization ...
Dmitriy Shutin, Thomas Buchgraber, Sanjeev R. Kulk...
CSDA
2006
142views more  CSDA 2006»
13 years 7 months ago
Automatic approximation of the marginal likelihood in non-Gaussian hierarchical models
Fitting of non-Gaussian hierarchical random effects models by approximate maximum likelihood can be made automatic to the same extent that Bayesian model fitting can be automated ...
Hans J. Skaug, David A. Fournier