10 search results - page 2 / 2 » Nonuniform Sparse Recovery with Gaussian Matrices |
CORR
2008
Springer
13 years 5 months ago
2008
Springer
In this note, we address the theoretical properties of p, a class of compressed sensing decoders that rely on p minimization with p (0, 1) to recover estimates of sparse and compr...
CORR
2010
Springer
13 years 5 months ago
2010
Springer
A major enterprise in compressed sensing and sparse approximation is the design and analysis of computationally tractable algorithms for recovering sparse, exact or approximate, s...
ICASSP
2011
IEEE
12 years 8 months ago
2011
IEEE
—Nuclear norm minimization (NNM) has recently gained attention for its use in rank minimization problems. In this paper, we define weak, sectional and strong recovery for NNM to...
JMLR
2010
12 years 11 months ago
2010
Methods based on 1-relaxation, such as basis pursuit and the Lasso, are very popular for sparse regression in high dimensions. The conditions for success of these methods are now ...
CORR
2010
Springer
13 years 5 months ago
2010
Springer
This paper introduces a simple and very general theory of compressive sensing. In this theory, the sensing mechanism simply selects sensing vectors independently at random from a ...