14 search results - page 2 / 3 » Online performance guarantees for sparse recovery |
ICCV
2009
IEEE
13 years 2 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
13 years 4 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
13 years 4 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
13 years 4 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...
COLT
2010
Springer
13 years 2 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...