116 search results - page 2 / 24 » A Quadratically Convergent Algorithm for Structured Low-Rank... |
SIAMSC
2011
13 years 5 months ago
2011
We consider the problem of estimating the uncertainty in large-scale linear statistical inverse problems with high-dimensional parameter spaces within the framework of Bayesian inf...
SDM
2011
SIAM
13 years 1 months ago
2011
SIAM
In this paper we present a fast and accurate procedure called clustered low rank matrix approximation for massive graphs. The procedure involves a fast clustering of the graph and...
ICML
2004
IEEE
14 years 11 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...
TKDE
2012
12 years 1 months ago
2012
—Traditional clustering techniques are inapplicable to problems where the relationships between data points evolve over time. Not only is it important for the clustering algorith...
ICCV
2011
IEEE
12 years 11 months ago
2011
IEEE
Low-Rank Representation (LRR) [16, 17] is an effective method for exploring the multiple subspace structures of data. Usually, the observed data matrix itself is chosen as the dic...