87 search results - page 2 / 18 » The regularized least squares algorithm and the problem of l... |
ISNN
2007
Springer
13 years 11 months ago
2007
Springer
Nonnegative Matrix and Tensor Factorization (NMF/NTF) and Sparse Component Analysis (SCA) have already found many potential applications, especially in multi-way Blind Source Separ...
PRL
2011
12 years 11 months ago
2011
Machine Learning based on the Regularized Least Square (RLS) model requires one to solve a system of linear equations. Direct-solution methods exhibit predictable complexity and s...
NECO
2011
12 years 11 months ago
2011
Accurately evaluating statistical independence among random variables is a key element of Independent Component Analysis (ICA). In this paper, we employ a squared-loss variant of ...
ICDM
2009
IEEE
13 years 11 months ago
2009
IEEE
—We describe parallel methods for solving large-scale, high-dimensional, sparse least-squares problems that arise in machine learning applications such as document classificatio...
BMCBI
2005
13 years 4 months ago
2005
Background: The advent of the technology of DNA microarrays constitutes an epochal change in the classification and discovery of different types of cancer because the information ...