Accelerated proximal point method for maximally monotone operators

被引:1
|
作者
Donghwan Kim
机构
[1] KAIST,Department of Mathematical Sciences
来源
Mathematical Programming | 2021年 / 190卷
关键词
Proximal point method; Acceleration; Maximally monotone operators; Worst-case performance analysis; 90C25; 90C30; 90C60; 68Q25; 49M25; 90C22;
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学科分类号
摘要
This paper proposes an accelerated proximal point method for maximally monotone operators. The proof is computer-assisted via the performance estimation problem approach. The proximal point method includes various well-known convex optimization methods, such as the proximal method of multipliers and the alternating direction method of multipliers, and thus the proposed acceleration has wide applications. Numerical experiments are presented to demonstrate the accelerating behaviors.
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页码:57 / 87
页数:30
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