An efficient algorithm for updating the penalty parameter of the alternating direction method for l1 problem

Jie Ma; Lijun Xu; Yijia Zhou

doi:10.1117/12.3035235

21 July 2024 An efficient algorithm for updating the penalty parameter of the alternating direction method for l1 problem

Jie Ma, Lijun Xu, Yijia Zhou

Author Affiliations +

Proceedings Volume 13219, Fourth International Conference on Applied Mathematics, Modelling, and Intelligent Computing (CAMMIC 2024); 132192O (2024) https://doi.org/10.1117/12.3035235
Event: 4th International Conference on Applied Mathematics, Modelling and Intelligent Computing (CAMMIC 2024), 2024, Kaifeng, China

Abstract

This work investigates an adaptively updating rule of the penalty in alternating direction method (ADM) for 𝑙1 problem. The adjusting criterion is motivated by the iterative behaviors of the objective and residue of constraint. The main algorithm is focused on the ADM framework of the dual problem. By studying the iterative behaviors, the dynamically updating scheme is developed with default values of startup, frequency and scaling. Numerical experiments show that the novel algorithm can not only speed up the classic ADM, but also make the choice of initial penalty parameter more flexible.

(2024) Published by SPIE. Downloading of the abstract is permitted for personal use only.

Citation Download Citation

Jie Ma, Lijun Xu, and Yijia Zhou "An efficient algorithm for updating the penalty parameter of the alternating direction method for l1 problem", Proc. SPIE 13219, Fourth International Conference on Applied Mathematics, Modelling, and Intelligent Computing (CAMMIC 2024), 132192O (21 July 2024); https://doi.org/10.1117/12.3035235

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