12 search results - page 1 / 3 » Null space conditions and thresholds for rank minimization |
MP
2011
13 years 2 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
2011
IEEE
12 years 11 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...
SIAMJO
2010
13 years 5 months ago
2010
This paper introduces a novel algorithm to approximate the matrix with minimum nuclear norm among all matrices obeying a set of convex constraints. This problem may be understood a...
IFIP
2005
Springer
14 years 29 days ago
2005
Springer
A new quasi-Newton scheme for updating a low rank positive semi-definite Hessian approximation is described, primarily for use in sequential quadratic programming methods for non...
JCT
2011
13 years 2 months ago
2011
We find sharp absolute constants C1 and C2 with the following property: every well-rounded lattice of rank 3 in a Euclidean space has a minimal basis so that the solid angle spann...