A Regularization Method for the Proximal Point Algorithm

被引：0

作者：

Hong-Kun Xu

机构：

[1] University of KawZulu-Natal,School of Mathematical Sciences

来源：

Journal of Global Optimization | 2006年 / 36卷

关键词：

maximal monotone operator; projection; proximal point algorithm; regularization method; resolvent identity; strong convergence; 49J40; 47J20; 65J15;

D O I：

暂无

中图分类号：

学科分类号：

摘要：

A regularization method for the proximal point algorithm of finding a zero for a maximal monotone operator in a Hilbert space is proposed. Strong convergence of this algorithm is proved.

引用

页码：115 / 125

页数：10

共 9 条

[1]

Güler O.(1991)On the convergence of the proximal point algorithm for convex optimization SIAM Journal of Control Optimization 29 403-419

[2]

Kamimura S.(2003)Strong convergence of a proximal-type algorithm in a Banach space SIAM Journal of Optimization 13 938-945

[3]

Takahashi W.(1996)Combining the proximal algorithm and Tikhonov regularization Optimization 37 239-252

[4]

Lehdili N.(1976)Monotone operators and the proximal point algorithm SIAM Journal of Control Optimization 14 877-898

[5]

Moudafi A.(2000)Forcing strong convergence of proximal point iterations in a Hilbert space Mathematical Programming, Series A 87 189-202

[6]

Rockafellar R.T.(2002)Iterative algorithms for nonlinear operators Journal of the London Mathematical Society 66 240-256

[7]

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[8]

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[9]

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