论文标题
对平衡问题的亚级别型方法的定量分析
Quantitative analysis of a subgradient-type method for equilibrium problems
论文作者
论文摘要
我们使用源自称为“证明挖掘”的数学逻辑子学分的技术来提供克服速率，并且 - 在度量规则性假设下 - 亚级型型算法的收敛速率解决了解决平衡问题，以在convex optife opts conteve optipers中的稳定点集中均不固定的固定点集。该算法归因于H. Iiduka和I. Yamada，他们在2009年没有提供任何融合证明。该案例研究说明了第二篇作者在以前的论文中给出的基于逻辑的摘要定量分析的摘要定量分析。
We use techniques originating from the subdiscipline of mathematical logic called `proof mining' to provide rates of metastability and - under a metric regularity assumption - rates of convergence for a subgradient-type algorithm solving the equilibrium problem in convex optimization over fixed-point sets of firmly nonexpansive mappings. The algorithm is due to H. Iiduka and I. Yamada who in 2009 gave a noneffective proof of its convergence. This case study illustrates the applicability of the logic-based abstract quantitative analysis of general forms of Fejér monotonicity as given by the second author in previous papers.
