An Adaptive Univariate Global Optimization Algorithm and Its Convergence Rate under the Wiener Measure

被引：0
|
作者：
Calvin, James [1 ]
机构：
[1] New Jersey Inst Technol, Dept Comp Sci, Newark, NJ 07102 USA
来源：
INFORMATICA | 2011年 / 22卷 / 04期
基金：
美国国家科学基金会;
关键词：
optimization; statistical models; convergence;
D O I：
暂无
中图分类号：
TP [自动化技术、计算机技术];
学科分类号：
0812 ;
摘要：
We describe an adaptive algorithm for approximating the global minimum of a continuous univariate function. The convergence rate of the error is studied for the case of a random objective function distributed according to the Wiener measure.
引用
收藏
页码：471 / 488
页数：18
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