5 search results - page 1 / 1 » Necessary and sufficient conditions for success of the nucle... |
CDC
2008
IEEE
13 years 4 months ago
2008
IEEE
Minimizing the rank of a matrix subject to constraints is a challenging problem that arises in many applications in control theory, machine learning, and discrete geometry. This c...
MP
2011
12 years 11 months ago
2011
Minimizing the rank of a matrix subject to constraints is a challenging problem that arises in many applications in machine learning, control theory, and discrete geometry. This c...
ICASSP
2010
IEEE
13 years 4 months ago
2010
IEEE
The problem of minimizing the rank of a matrix subject to linear equality constraints arises in applications in machine learning, dimensionality reduction, and control theory, and...
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...
CORR
2010
Springer
13 years 4 months ago
2010
Springer
In this paper we revisit the sparse multiple measurement vector (MMV) problem, where the aim is to recover a set of jointly sparse multichannel vectors from incomplete measurement...