A globally convergent fast iterative shrinkage-thresholding algorithm with a new momentum factor for single and multi-objective convex optimization.
Hiroki TanabeEllen H. FukudaNobuo YamashitaPublished in: CoRR (2022)
Keyphrases
- convex optimization
- globally convergent
- augmented lagrangian
- multi objective
- thresholding algorithm
- total variation
- image denoising
- interior point methods
- variational inequalities
- evolutionary algorithm
- autocalibration
- denoising
- primal dual
- low rank
- constrained optimization
- constrained optimization problems
- objective function
- optimization algorithm
- particle swarm optimization
- multiple objectives
- image processing
- convex sets
- genetic algorithm
- line search
- operator splitting
- douglas rachford splitting
- linear programming problems
- natural images
- optical flow
- computer vision