49 search results - page 2 / 10 » Non-iterative generalized low rank approximation of matrices |
IDEAL
2010
Springer
13 years 4 months ago
2010
Springer
: Covariance matrices capture correlations that are invaluable in modeling real-life datasets. Using all d2 elements of the covariance (in d dimensions) is costly and could result ...
JSCIC
2010
13 years 2 months ago
2010
We discuss the approximation of the meanfield terms appearing in computations of the multi-configuration time-dependent Hartree
SIAMJO
2011
13 years 2 months ago
2011
Many applications arising in a variety of fields can be well illustrated by the task of recovering the low-rank and sparse components of a given matrix. Recently, it is discovered...
NIPS
2004
13 years 8 months ago
2004
We prove generalization error bounds for predicting entries in a partially observed matrix by fitting the observed entries with a low-rank matrix. In justifying the analysis appro...
CORR
2011
Springer
13 years 2 months ago
2011
Springer
We analyze a class of estimators based on a convex relaxation for solving highdimensional matrix decomposition problems. The observations are the noisy realizations of the sum of ...