11 search results - page 1 / 3 » Analysis and Improvement of Low Rank Representation for Subs... |
CORR
2011
Springer
12 years 8 months ago
2011
Springer
We analyze and improve low rank representation (LRR), the state-of-the-art algorithm for subspace segmentation of data. We prove that for the noiseless case, the optimization mode...
ICML
2010
IEEE
13 years 5 months ago
2010
IEEE
We propose low-rank representation (LRR) to segment data drawn from a union of multiple linear (or affine) subspaces. Given a set of data vectors, LRR seeks the lowestrank represe...
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...
CVPR
2007
IEEE
14 years 6 months ago
2007
IEEE
Several authors have noticed that the common representation of images as vectors is sub-optimal. The process of vectorization eliminates spatial relations between some of the near...
NN
2008
Springer
13 years 4 months ago
2008
Springer
Learning data representations is a fundamental challenge in modeling neural processes and plays an important role in applications such as object recognition. In multi-stage Optima...