6 search results - page 1 / 2 » Subspace Sampling and Relative-Error Matrix Approximation: C... |
APPROX
2006
Springer
13 years 8 months ago
2006
Springer
Given an m
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
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...
JMLR
2012
11 years 7 months ago
2012
In this paper, we propose a second order optimization method to learn models where both the dimensionality of the parameter space and the number of training samples is high. In ou...
ICDM
2009
IEEE
13 years 11 months ago
2009
IEEE
Given a data matrix, the problem of finding dense/uniform sub-blocks in the matrix is becoming important in several applications. The problem is inherently combinatorial since th...