Provable accelerated gradient method for nonconvex low rank optimization.
Huan LiZhouchen LinPublished in: Mach. Learn. (2020)
Keyphrases
- low rank
- gradient method
- convex optimization
- low rank matrices
- optimization methods
- robust principal component analysis
- optimization problems
- nuclear norm
- missing data
- low rank matrix
- global optimization
- convex relaxation
- matrix factorization
- linear combination
- matrix completion
- rank minimization
- negative matrix factorization
- norm minimization
- singular value decomposition
- convergence rate
- high order
- semi supervised
- high dimensional data
- low rank and sparse
- optimization algorithm
- step size
- optimization method
- objective function
- neural network
- evolutionary algorithm
- small number
- data sets
- data analysis
- support vector machine
- image segmentation
- sparse representation