A note on the regularized proximal point algorithm

Authors:
Fenghui Wang
Affiliations:
Department of Mathematics, Luoyang Normal University, Luoyang, China 471022
Venue:
Journal of Global Optimization
Year:
2011

Citing 4
Cited 1

On the convergence of the proximal point algorithm for convex minimization

SIAM Journal on Control and Optimization
A Weak-to-Strong Convergence Principle for Fejé-Monotone Methods in Hilbert Spaces

Mathematics of Operations Research
A Regularization Method for the Proximal Point Algorithm

Journal of Global Optimization
A note on a paper "A regularization method for the proximal point algorithm"

Journal of Global Optimization

On the contraction-proximal point algorithms with multi-parameters

Journal of Global Optimization

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Abstract

Recently, Xu (J Glob Optim 36:115---125 (2006)) introduced a regularized proximal point algorithm for approximating a zero of a maximal monotone operator. In this note, we shall prove the strong convergence of this algorithm under some weaker conditions.