Linear convergence rates for extrapolated fixed point algorithms

被引：9

作者：

Bargetz, Christian ^{[1
]}

Kolobov, Victor I. ^{[2
]}

Reich, Simeon ^{[3
]}

Zalas, Rafal ^{[3
]}

机构：

[1] Univ Innsbruck, Dept Math, Innsbruck, Austria

[2] Technion Israel Inst Technol, Dept Comp Sci, Haifa, Israel

[3] Technion Israel Inst Technol, Dept Math, IL-32000 Haifa, Israel

来源：

OPTIMIZATION | 2019年 / 68卷 / 01期

基金：

以色列科学基金会;

关键词：

Extrapolation; linear rate; string averaging; QUASI-NONEXPANSIVE OPERATORS; CONVEX FEASIBILITY PROBLEMS; PROJECTION METHODS; SUCCESSIVE-APPROXIMATIONS; INFINITE PRODUCTS; WEAK-CONVERGENCE; HILBERT; REGULARITY; ITERATION; MAPPINGS;

D O I：

10.1080/02331934.2018.1512109

中图分类号：

C93 [管理学]; O22 [运筹学];

学科分类号：

070105 ; 12 ; 1201 ; 1202 ; 120202 ;

摘要：

We establish linear convergence rates for a certain class of extrapolated fixed point algorithms which are based on dynamic string-averaging methods in a real Hilbert space. This applies, in particular, to the extrapolated simultaneous and cyclic cutter methods. Our analysis covers the cases of both metric and subgradient projections.

引用

页码：163 / 195

页数：33

共 49 条

[1] Block-iterative algorithms for solving convex feasibility problems in Hilbert and in Banach spaces [J].