14 search results - page 2 / 3 » Online performance guarantees for sparse recovery |
112
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ICCV
2009
IEEE
14 years 9 months ago
2009
IEEE
This paper investigates a new learning formulation called dynamic group sparsity. It is a natural extension of the standard sparsity concept in compressive sensing, and is motivat...
CORR
2010
Springer
14 years 11 months ago
2010
Springer
Sparse modeling is a powerful framework for data analysis and processing. Traditionally, encoding in this framework is performed by solving an 1-regularized linear regression prob...
CORR
2010
Springer
14 years 11 months ago
2010
Springer
Compressed sensing allows perfect recovery of sparse signals (or signals sparse in some basis) using only a small number of random measurements. Existing results in compressed sens...
CORR
2010
Springer
14 years 11 months ago
2010
Springer
The MUSIC algorithm, and its extension for imaging sparse extended objects, with noisy data is analyzed by compressed sensing (CS) techniques. A thresholding rule is developed to a...
166
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COLT
2010
Springer
14 years 9 months ago
2010
Springer
We present a new family of subgradient methods that dynamically incorporate knowledge of the geometry of the data observed in earlier iterations to perform more informative gradie...