15 search results - page 2 / 3 » A Convex Approach to Low Rank Matrix Approximation with Miss... |
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...
SIAMSC
2008
13 years 4 months ago
2008
In this study, nonnegative matrix factorization is recast as the problem of approximating a polytope on the probability simplex by another polytope with fewer facets. Working on th...
KDD
2012
ACM
11 years 7 months ago
2012
ACM
Trust networks, where people leave trust and distrust feedback, are becoming increasingly common. These networks may be regarded as signed graphs, where a positive edge weight cap...
ICCV
2011
IEEE
12 years 4 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...
SIAMJO
2010
13 years 2 months ago
2010
This paper introduces a novel algorithm to approximate the matrix with minimum nuclear norm among all matrices obeying a set of convex constraints. This problem may be understood a...