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A Block Lanczos with Warm Start Technique for Accelerating Nuclear Norm Minimization Algorithms
Lanczos Method Singular Value Decomposition Eigenvalue
2011/3/1
Recent years have witnessed the popularity of using rank minimization as a regularizer for various signal processing and machine learning problems.
Closed-Form Solutions to A Category of Nuclear Norm Minimization Problems
Closed-Form Solutions Nuclear Norm Minimization Problems
2010/11/24
It is an efficient and effective strategy to utilize the nuclear norm approximation to learn low-rank matrices, which arise frequently in machine learning and computer vision. So the exploration of n...
Guaranteed Minimum-Rank Solutions of Linear Matrix Equations via Nuclear Norm Minimization
rank convex optimization matrix norms random matrices compressed sensing semidefinite program-ming
2010/4/29
The ane rank minimization problem consists of finding a matrix of minimum rank that
satisfies a given system of linear equality constraints. Such problems have appeared in the literature
of a divers...