49 search results - page 1 / 10 » Non-iterative generalized low rank approximation of matrices |
CVPR
2006
IEEE
14 years 9 months ago
2006
IEEE
Recently four non-iterative algorithms for simultaneous low rank approximations of matrices (SLRAM) have been presented by several researchers. In this paper, we show that those a...
ICML
2004
IEEE
14 years 8 months ago
2004
IEEE
The problem of computing low rank approximations of matrices is considered. The novel aspect of our approach is that the low rank approximations are on a collection of matrices. W...
PRL
2006
13 years 7 months ago
2006
: 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...
CORR
2011
Springer
12 years 11 months ago
2011
Springer
We address the problem of minimizing a convex function over the space of large matrices with low rank. While this optimization problem is hard in general, we propose an efficient...
TNN
2010
13 years 2 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...