Riemannian CUR Decompositions for Robust Principal Component Analysis.
Keaton HammMohamed MeskiniHanQin CaiPublished in: CoRR (2022)
Keyphrases
- robust principal component analysis
- low rank
- singular value decomposition
- linear combination
- matrix factorization
- matrix completion
- convex optimization
- missing data
- manifold learning
- low rank and sparse
- rank minimization
- low rank matrix
- kernel matrix
- semi supervised
- high dimensional data
- low rank approximation
- dimensionality reduction
- singular values
- high order
- data matrix
- least squares
- small number
- machine learning
- nearest neighbor
- foreground detection
- pairwise
- data analysis
- feature selection