Adaptive Methods for Variational Inequalities with Relatively Smooth and Reletively Strongly Monotone Operators

IF 0.7 4区 计算机科学 Q4 COMPUTER SCIENCE, SOFTWARE ENGINEERING Programming and Computer Software Pub Date : 2023-12-01 DOI:10.1134/s0361768823060026
S. S. Ablaev, F. S. Stonyakin, M. S. Alkousa, D. A. Pasechnyk
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Abstract

This paper is devoted to some adaptive methods for variational inequalities with relatively smooth and relatively strongly monotone operators. Based on the recently proposed proximal version of the extragradient method for this class of problems, we study in detail the method with adaptively selected parameter values. The rate of convergence of this method is estimated. The result is generalized to the class of variational inequalities with relatively strongly monotone δ-generalized smooth operators. For the ridge regression problem and variational inequality associated with box-simplex games, numerical experiments are carried out to demonstrate the effectiveness of the proposed technique for adaptive parameter selection during the execution of the algorithm.

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具有相对光滑和相对强单调算子的变分不等式的自适应方法
摘要本文研究了具有相对光滑和相对强单调算子的变分不等式的一些自适应方法。在最近提出的这类问题的近端提取方法的基础上,我们详细研究了自适应选择参数值的方法。估计了该方法的收敛速度。结果推广到一类具有较强单调δ-广义光滑算子的变分不等式。针对岭回归问题和盒形博弈相关的变分不等式问题,进行了数值实验,验证了算法执行过程中自适应参数选择技术的有效性。
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来源期刊
Programming and Computer Software
Programming and Computer Software 工程技术-计算机:软件工程
CiteScore
1.60
自引率
28.60%
发文量
35
审稿时长
>12 weeks
期刊介绍: Programming and Computer Software is a peer reviewed journal devoted to problems in all areas of computer science: operating systems, compiler technology, software engineering, artificial intelligence, etc.
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