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Convergence analysis of a primal-dual optimization-by-continuation algorithm
- Source :
- Journal of computational and applied mathematics
- Publication Year :
- 2024
-
Abstract
- We present a numerical iterative optimization algorithm for the minimization of a cost function consisting of a linear combination of three convex terms, one of which is differentiable, a second one is prox-simple and the third one is the composition of a linear map and a prox-simple function. The algorithm's special feature lies in its ability to approximate, in a single iteration run, the minimizers of the cost function for many different values of the parameters determining the relative weight of the three terms in the cost function. A proof of convergence of the algorithm, based on an inexact variable metric approach, is also provided. As a special case, one recovers a generalization of the primal-dual algorithm of Chambolle and Pock, and also of the proximal-gradient algorithm. Finally, we show how it is related to a primal-dual iterative algorithm based on inexact proximal evaluations of the non-smooth terms of the cost function.<br />Submitted.<br />info:eu-repo/semantics/inPress
Details
- Database :
- OAIster
- Journal :
- Journal of computational and applied mathematics
- Notes :
- 1 full-text file(s): application/pdf, English
- Publication Type :
- Electronic Resource
- Accession number :
- edsoai.on1427400550
- Document Type :
- Electronic Resource