Robustness of the hybrid extragradient proximal-point algorithm

被引:10
作者
Burachik, RS [1 ]
Scheimberg, S
Svaiter, BF
机构
[1] Univ Fed Rio de Janeiro, Inst Matemat, Rio De Janeiro, Brazil
[2] Inst Matematica Pura & Aplicada, Rio De Janeiro, Brazil
关键词
maximal monotone operators; proximal-point algorithm; extragradient method; enlargement of a maximal monotone operator;
D O I
10.1023/A:1017523331361
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
The hybrid extragradient proximal-point method recently proposed by Solodov and Svaiter has the distinctive feature of allowing a relative error tolerance. We extend the error tolerance of this method, proving that it converges even if a summable error is added to the relative error. Furthermore, the extragradient step may be performed inexactly with a summable error. We present a convergence analysis, which encompasses other well-known variations of the proximal-point method, previously unrelated. We establish weak global convergence under mild assumptions.
引用
收藏
页码:117 / 136
页数:20
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