On the linear convergence of a Bregman proximal point algorithm

IF 2.5 2区 数学 Q1 MATHEMATICS Journal of Nonlinear and Variational Analysis Pub Date : 2022-01-01 DOI:10.23952/jnva.6.2022.2.02
K. Guo, C. Zhu, K. Guo, C. Zhu
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引用次数: 1

Abstract

. In this paper, we study a Bregman proximal point algorithm (BPPA) for convex optimization problems. Though the convergence and sublinear convergence rate for BPPA are well-understand, the linear convergence rate for BPPA has yet been thoroughly studied in the literature. In this paper, we analyze the linear convergence rate of BPPA. Under the assumption that the objective function is strongly convex relative to a Legendre function, we establish the linear convergence for the function values sequence. Moreover, if the Legendre function is strongly convex and smooth, the linear convergence for the iterative sequence of BPPA is obtained.
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Bregman近点算法的线性收敛性
. 本文研究了求解凸优化问题的Bregman近点算法(BPPA)。虽然对BPPA的收敛性和亚线性收敛率已经有了很好的了解,但对BPPA的线性收敛率还没有深入的文献研究。本文分析了BPPA算法的线性收敛速度。在目标函数相对于Legendre函数是强凸的假设下,我们建立了函数值序列的线性收敛性。此外,当Legendre函数是强凸光滑时,得到了BPPA迭代序列的线性收敛性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
CiteScore
3.30
自引率
3.40%
发文量
10
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