139 search results - page 1 / 28 » Structured low-rank approximation and its applications |
SDM
2011
SIAM
12 years 7 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...
SCIA
2009
Springer
13 years 11 months ago
2009
Springer
Many computer vision problems can be formulated as low rank bilinear minimization problems. One reason for the success of these problems is that they can be efficiently solved usin...
CORR
2011
Springer
12 years 8 months ago
2011
Springer
We address the problem of minimizing a convex function over the space of large matrices with low rank. While this optimization problem is hard in general, we propose an efficient...
TKDE
2012
11 years 7 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...
SIAMMAX
2010
12 years 11 months ago
2010
The problem of completing a low-rank matrix from a subset of its entries is often encountered in the analysis of incomplete data sets exhibiting an underlying factor model with app...