Robust principal component analysis based on low-rank and block-sparse matrix decomposition.
Gongguo TangArye NehoraiPublished in: CISS (2011)
Keyphrases
- low rank
- robust principal component analysis
- matrix decomposition
- low rank matrix
- convex optimization
- linear combination
- missing data
- matrix factorization
- rank minimization
- singular value decomposition
- semi supervised
- nuclear norm
- matrix completion
- kernel matrix
- low rank and sparse
- high dimensional data
- high order
- low rank approximation
- data matrix
- pattern recognition
- image processing
- sparse coding
- affinity matrix
- eigendecomposition
- data analysis
- nonnegative matrix factorization
- machine learning
- higher order
- image restoration