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