TIT
2010
12 years 11 months ago
2010
This paper is concerned with the problem of recovering an unknown matrix from a small fraction of its entries. This is known as the matrix completion problem, and comes up in a gr...
JMLR
2010
12 years 11 months ago
2010
We use convex relaxation techniques to provide a sequence of regularized low-rank solutions for large-scale matrix completion problems. Using the nuclear norm as a regularizer, we...
CVPR
2011
IEEE
12 years 12 months ago
2011
IEEE
Exact recovery from contaminated visual data plays an important role in various tasks. By assuming the observed data matrix as the addition of a low-rank matrix and a sparse matri...
SIAMJO
2010
13 years 2 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...