23 search results - page 3 / 5 » Rank Aggregation via Nuclear Norm Minimization |
CVPR
2011
IEEE
13 years 1 months ago
2011
IEEE
Exact recovery from contaminated visual data plays an important role in various tasks. By assuming the observed data matrix as the addition of a low-rank matrix and a sparse matri...
SIGKDD
2010
13 years 21 days ago
2010
In recent years, compressive sensing attracts intensive attentions in the field of statistics, automatic control, data mining and machine learning. It assumes the sparsity of the ...
MP
2011
13 years 28 days ago
2011
Minimizing the rank of a matrix subject to constraints is a challenging problem that arises in many applications in machine learning, control theory, and discrete geometry. This c...
SIAMJO
2011
12 years 8 months ago
2011
Suppose we are given a matrix that is formed by adding an unknown sparse matrix to an unknown low-rank matrix. Our goal is to decompose the given matrix into its sparse and low-ran...
CVPR
2012
IEEE
11 years 8 months ago
2012
IEEE
In this paper, we propose a rank minimization method to fuse the predicted confidence scores of multiple models, each of which is obtained based on a certain kind of feature. Spe...