题名 | A direct search algorithm based on kernel density estimator for nonlinear optimization |
作者 | |
发表日期 | 2014 |
会议录名称 | 2014 10th International Conference on Natural Computation, ICNC 2014
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页码 | 297-302 |
摘要 | In this paper, we propose a direct search algorithm based on kernel density estimator for the nonlinear optimization problems. It estimates the objective function by the kernel density estimator with the local samples only, and then approximates the ascent direction of the objective function with the one of the estimator. The proposed optimization approach features the derivative-free with much likely generating an ascent direction. We not only theoretically show that the search direction, which is used in the proposed algorithm towards maximizing the objective function, is the ascent direction of the objective function, but also empirically investigate the effectiveness of the search direction. |
DOI | 10.1109/ICNC.2014.6975851 |
URL | 查看来源 |
语种 | 英语English |
Scopus入藏号 | 2-s2.0-84926640794 |
引用统计 | |
文献类型 | 会议论文 |
条目标识符 | https://repository.uic.edu.cn/handle/39GCC9TT/6509 |
专题 | 北师香港浸会大学 |
作者单位 | 1.Department of Computer Science, Hong Kong Baptist University,China 2.BNU-HKBU, United International College,Zhuhai,China |
第一作者单位 | 北师香港浸会大学 |
推荐引用方式 GB/T 7714 | Cheung,Yiu Ming,Gu,Fangqing. A direct search algorithm based on kernel density estimator for nonlinear optimization[C], 2014: 297-302. |
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