图 书 馆
预测一场比赛的结果Predicting the Outcome of a Game |
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| 课程网址: | http://videolectures.net/eccs07_wolpert_pog/ |
| 主讲教师: | David Wolpert |
| 开课单位: | 美国宇航局 |
| 开课时间: | 2007-11-26 |
| 课程语种: | 英语 |
| 中文简介: |  |
| 课程简介: | Optimization of many complex systems is often viewed as a black-box optimization problem. Such problems are often difficult to solve using conventional techniques, for a variety of reasons, such as the absence of derivatives, mixed data types, and so on. Techniques such as Genetic Algorithms, Estimation of Distribution Algorithms such as MIMIC and the CE method, and more recently, mathematically rigorous approaches such as Probability Collectives have been used for black-box optimization. It turns out that many of these techniques fall under the category of Monte Carlo Optimization. In this technique, we present a brief statistical analysis of Monte Carlo Optimization (MCO), and show that it is identical to Parametric Machine Learning (PL). Owing to this identity, we can use PL techniques to improve the performance of MCO. Then, we present a new version of the black-box optimization technique of Probability Collectives., and demonstrate the use of PL techniques to improve its optimization performance. |
| 关 键 词: | 蒙特卡罗优化; 黑盒优化; 混合数据类型; 遗传算法; 分布估计算法 |
| 课程来源: | 视频讲座网 |
| 最后编审: | 2020-09-17：chenxin |
| 阅读次数: | 81 |