49 search results - page 7 / 10 » Non-iterative generalized low rank approximation of matrices |
CVPR
2009
IEEE
13 years 11 months ago
2009
IEEE
Nonnegative Matrix Factorization (NMF) approximates a given data matrix as a product of two low rank nonnegative matrices, usually by minimizing the L2 or the KL distance between ...
COMPUTING
2006
13 years 7 months ago
2006
The ULV decomposition (ULVD) is an important member of a class of rank-revealing two-sided orthogonal decompositions used to approximate the singular value decomposition (SVD). Th...
ICPR
2010
IEEE
14 years 11 days ago
2010
IEEE
Covariance matrices have recently been a popular choice for versatile tasks like recognition and tracking due to their powerful properties as local descriptor and their low comput...
TIT
2010
13 years 2 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...
ICML
2005
IEEE
14 years 8 months ago
2005
IEEE
Low-rank matrix decompositions are essential tools in the application of kernel methods to large-scale learning problems. These decompositions have generally been treated as black...