Convergence of projected subgradient method with sparse or low-rank constraints.
Hang XuSong LiJunhong LinPublished in: Adv. Comput. Math. (2024)
Keyphrases
- low rank
- low rank matrix
- rank minimization
- low rank matrices
- linear combination
- missing data
- convex optimization
- subgradient method
- matrix factorization
- matrix completion
- singular value decomposition
- high dimensional data
- high order
- regularized regression
- kernel matrix
- semi supervised
- sparse matrix
- constraint programming
- convergence rate
- constrained optimization
- convex relaxation
- sparse representation
- low dimensional
- linear programming
- higher order
- dynamic programming