14 search results - page 3 / 3 » Learning Low Rank Matrices from O(n) Entries |
TIT
2010
12 years 12 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...
SIAMJO
2010
13 years 3 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...
TNN
2010
12 years 12 months ago
2010
Compared to Singular Value Decomposition (SVD), Generalized Low Rank Approximations of Matrices (GLRAM) can consume less computation time, obtain higher compression ratio, and yiel...
CORR
2011
Springer
13 years 7 days ago
2011
Springer
This paper introduces a novel algorithm for the nonnegative matrix factorization and completion problem, which aims to find nonnegative matrices X and Y from a subset of entries o...