Sciweavers

Share
13 search results - page 1 / 3
» Analysis and Improvement of Low Rank Representation for Subs...
Sort
View
CORR
2011
Springer
209views Education» more  CORR 2011»
7 years 10 months ago
Analysis and Improvement of Low Rank Representation for Subspace segmentation
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...
Siming Wei, Zhouchen Lin
ICML
2010
IEEE
8 years 7 months ago
Robust Subspace Segmentation by Low-Rank Representation
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...
Guangcan Liu, Zhouchen Lin, Yong Yu
ICCV
2011
IEEE
7 years 6 months ago
Latent Low-Rank Representation for Subspace Segmentation and Feature Extraction
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...
Guangcan Liu, Shuicheng Yan
CVPR
2007
IEEE
9 years 8 months ago
Modeling Appearances with Low-Rank SVM
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...
Lior Wolf, Hueihan Jhuang, Tamir Hazan
NN
2008
Springer
201views Neural Networks» more  NN 2008»
8 years 6 months ago
Learning representations for object classification using multi-stage optimal component analysis
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...
Yiming Wu, Xiuwen Liu, Washington Mio
books