Accelerated Proximal Gradient Method with Backtracking for Multiobjective Optimization

Autor:	Huang, Chengzhi, Chen, Jian, Tang, Liping
Rok vydání:	2024
Předmět:	Mathematics - Optimization and Control
Druh dokumentu:	Working Paper
Popis:	This paper proposes a new backtracking strategy based on the FISTA accelerated algorithm for multiobjective optimization problems. The strategy focuses on solving the problem of Lipschitz constant being unknown. It allows estimate parameter updates non-increasingly. Furthermore, the proposed strategy effectively avoids the limitation in convergence proofs arising from the non-negativity of the auxiliary sequence, thus providing a theoretical guarantee for its performance. We demonstrate that, under relatively mild assumptions, the algorithm achieves the convergence rate of $O(1/k2)$. Comment: arXiv admin note: text overlap with arXiv:2312.01609
Databáze:	arXiv
Externí odkaz:	http://arxiv.org/abs/2412.14007 Zobrazit plný text záznamu View this record from Arxiv