par Loris, Ignace
Référence SIAM Conference on Imaging Science (23-26/05/2016: Albuquerque, New Mexico, USA)
Publication Non publié, 2016-05-23
Communication à un colloque
Résumé : Iterative algorithms for the numerical solution of non-smooth optimization problems involving an objective function that is a combination of a data misfit term and regularizing penalty are discussed. The proposed algorithms are based on variable metrics, descent directions and the Armijo line-search rule. Convergence results are given in the convex and non-convex case, and are also examined in case the proximal operator of the non-smooth part of the objective function can only be calculated approximately.Based on joint work with S. Bonettini, F. Porta, M. Prato and S. Rebegoldi.