Low-Rank-Sparse Subspace Representation for Robust Regression.
Yongqiang ZhangDaming ShiJunbin GaoDansong ChengPublished in: CVPR (2017)
Keyphrases
- low rank
- rank minimization
- low rank representation
- regularized regression
- robust regression
- low rank matrix
- high dimensional data
- missing data
- singular value decomposition
- matrix factorization
- linear combination
- kernel matrix
- convex optimization
- high dimensional
- matrix completion
- high order
- semi supervised
- feature selection
- low dimensional
- data sets
- linear regression
- image representation
- dimensionality reduction
- least squares
- image segmentation
- sparse representation
- image restoration
- input data
- support vector
- decision trees
- nearest neighbor