Convergence results of two-step inertial proximal point algorithm

被引:29
作者
Iyiola, Olaniyi S. [1 ]
Shehu, Yekini [2 ]
机构
[1] Clarkson Univ, Dept Math, Potsdam, NY USA
[2] Zhejiang Normal Univ, Coll Math & Comp Sci, Jinhua 321004, Peoples R China
关键词
Proximal point algorithm; Two-point inertia; Maximal monotone operators; Weak and non-asymptotic convergence; Hilbert spaces; FORWARD-BACKWARD ALGORITHM; MAXIMAL MONOTONE-OPERATORS; PRIMAL-DUAL ALGORITHMS; RACHFORD; OPTIMIZATION; RATES;
D O I
10.1016/j.apnum.2022.07.013
中图分类号
O29 [应用数学];
学科分类号
070104 ;
摘要
This paper proposes a two-point inertial proximal point algorithm to find zero of maximal monotone operators in Hilbert spaces. We obtain weak convergence results and non-asymptotic O(1/n) convergence rate of our proposed algorithm in non-ergodic sense. Applications of our results to various well-known convex optimization methods, such as the proximal method of multipliers and the alternating direction method of multipliers are given. Numerical results are given to demonstrate the accelerating behaviors of our method over other related methods in the literature. (C) 2022 IMACS. Published by Elsevier B.V. All rights reserved.
引用
收藏
页码:57 / 75
页数:19
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