Local convergence of alternating low-rank optimization methods with overrelaxation.
Ivan V. OseledetsMaxim V. RakhubaAndré UschmajewPublished in: Numer. Linear Algebra Appl. (2023)
Keyphrases
- optimization methods
- low rank
- global convergence
- quasi newton
- optimization method
- convex optimization
- matrix factorization
- missing data
- linear combination
- singular value decomposition
- low rank matrix
- optimization problems
- matrix completion
- rank minimization
- simulated annealing
- semi supervised
- kernel matrix
- high order
- high dimensional data
- trace norm
- singular values
- minimization problems
- convergence speed
- line search
- efficient optimization
- convergence rate
- convex relaxation
- genetic algorithm
- linear program
- optimization algorithm
- multi objective
- evolutionary algorithm
- search space
- pattern recognition
- bayesian networks
- learning algorithm