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» On the Low Rank Solutions for Linear Matrix Inequalities
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ICASSP
2010
IEEE
13 years 7 months ago
A nullspace analysis of the nuclear norm heuristic for rank minimization
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...
Krishnamurthy Dvijotham, Maryam Fazel
ICASSP
2011
IEEE
12 years 11 months ago
Cooperative spectrum sensing based on matrix rank minimization
In cognitive radio (CR) networks, multi-CR cooperation typically takes place during spectrum sensing, to cope with wireless fading effects and the hidden terminal problem. The use...
Yue Wang, Zhi Tian, Chunyan Feng
CORR
2010
Springer
115views Education» more  CORR 2010»
13 years 5 months ago
Tight oracle bounds for low-rank matrix recovery from a minimal number of random measurements
This paper presents several novel theoretical results regarding the recovery of a low-rank matrix from just a few measurements consisting of linear combinations of the matrix entr...
Emmanuel J. Candès, Yaniv Plan
SIAMSC
2008
142views more  SIAMSC 2008»
13 years 7 months ago
A Fast Direct Solver for the Biharmonic Problem in a Rectangular Grid
We present a fast direct solver methodology for the Dirichlet biharmonic problem in a rectangle. The solver is applicable in the case of the second order Stephenson scheme [34] as ...
Matania Ben-Artzi, Jean-Pierre Croisille, Dalia Fi...
PRL
2006
117views more  PRL 2006»
13 years 7 months ago
Non-iterative generalized low rank approximation of matrices
: As an extension to 2DPCA, Generalized Low Rank Approximation of Matrices (GLRAM) applies two-sided (i.e., the left and right) rather than single-sided (i.e., the left or the righ...
Jun Liu, Songcan Chen