Convex optimization via inertial algorithms with vanishing Tikhonov regularization: fast convergence to the minimum norm solution.
Hédy AttouchSzilárd Csaba LászlóPublished in: Math. Methods Oper. Res. (2024)
Keyphrases
- convex optimization
- tikhonov regularization
- convex optimization problems
- minimum norm
- image restoration
- regularization parameter
- least squares
- machine learning algorithms
- learning algorithm
- low rank
- convergence rate
- image classification
- total variation
- singular value decomposition
- vector valued
- natural images
- pairwise