Robust low-rank training via approximate orthonormal constraints.
Dayana SavostianovaEmanuele ZangrandoGianluca CerutiFrancesco TudiscoPublished in: CoRR (2023)
Keyphrases
- low rank
- rank minimization
- low rank matrix
- singular value decomposition
- low rank subspace
- low rank representation
- robust principal component analysis
- missing data
- linear combination
- convex optimization
- matrix completion
- matrix factorization
- sparse matrix
- matrix decomposition
- semi supervised
- basis functions
- kernel matrix
- singular values
- high order
- high dimensional data
- non rigid structure from motion
- low rank matrices
- training set
- data matrix
- norm minimization
- trace norm
- multiscale
- minimization problems
- denoising
- least squares
- high dimensional