9 search results - page 1 / 2 » Relative-Error CUR Matrix Decompositions |
CORR
2007
Springer
13 years 4 months ago
2007
Springer
Many data analysis applications deal with large matrices and involve approximating the matrix using a small number of “components.” Typically, these components are linear combi...
ESA
2006
Springer
13 years 8 months ago
2006
Springer
Much recent work in the theoretical computer science, linear algebra, and machine learning has considered matrix decompositions of the following form: given an m
SDM
2012
SIAM
11 years 7 months ago
2012
SIAM
Low-rank approximations which are computed from selected rows and columns of a given data matrix have attracted considerable attention lately. They have been proposed as an altern...
CORR
2010
Springer
13 years 2 months ago
2010
Springer
The CUR decomposition provides an approximation of a matrix X that has low reconstruction error and that is sparse in the sense that the resulting approximation lies in the span o...
KDD
2006
ACM
14 years 5 months ago
2006
ACM
Motivated by numerous applications in which the data may be modeled by a variable subscripted by three or more indices, we develop a tensor-based extension of the matrix CUR decom...