Nonconvex Factorization and Manifold Formulations are Almost Equivalent in Low-rank Matrix Optimization.
Yuetian LuoXudong LiAnru R. ZhangPublished in: CoRR (2021)
Keyphrases
- low rank matrix
- low rank
- convex optimization
- low rank matrices
- nuclear norm
- missing entries
- matrix factorization
- singular value decomposition
- optimization problems
- optimization methods
- norm minimization
- convex relaxation
- matrix completion
- missing data
- low rank and sparse
- semi supervised
- kernel matrix
- data matrix
- sparse matrix
- linear combination
- low dimensional
- high order
- high dimensional data
- least squares
- state space
- high dimensional
- reinforcement learning