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基于图的方差缩减方案的组合On combining graph-based variance reduction schemes |
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| 课程网址: | http://videolectures.net/aistats2010_gogate_ocgbv/ |
| 主讲教师: | Vibhav Gogate |
| 开课单位: | 华盛顿大学 |
| 开课时间: | 2010-01-07 |
| 课程语种: | 英语 |
| 中文简介: |  |
| 课程简介: | In this paper, we consider two variance reduction schemes that exploit the structure of the primal graph of the graphical model: Rao-Blackwellised w-cutset sampling and AND/OR sampling. We show that the two schemes are orthogonal and can be combined to further reduce the variance. Our combination yields a new family of estimators which trade time and space with variance. We demonstrate experimentally that the new estimators are superior, often yielding an order of magnitude improvement over previous schemes on several benchmarks. |
| 关 键 词: | 方差缩减; 组合; 图形模型 |
| 课程来源: | 视频讲座网 |
| 最后编审: | 2019-10-31：lxf |
| 阅读次数: | 30 |