图 书 馆
混合累积分布网络Mixed Cumulative Distribution Networks |
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| 课程网址: | http://videolectures.net/aistats2011_silva_cumulative/ |
| 主讲教师: | Ricardo Silva |
| 开课单位: | 伦敦大学学院 |
| 开课时间: | 2011-05-06 |
| 课程语种: | 英语 |
| 中文简介: |  |
| 课程简介: | Directed acyclic graphs (DAGs) are a popular framework to express multivariate probability distributions. Acyclic directed mixed graphs (ADMGs) are generalizations of DAGs that can succinctly capture much richer sets of conditional independencies, and are especially useful in modeling the effects of latent variables implicitly. Unfortunately there are currently no good parameterizations of general ADMGs. In this paper, we apply recent work on cumulative distribution networks and copulas to propose one one general construction for ADMG models. We consider a simple parameter estimation approach, and report some encouraging experimental results. |
| 关 键 词: | 混合累积分布; 网络 |
| 课程来源: | 视频讲座网 |
| 最后编审: | 2021-02-04：nkq |
| 阅读次数: | 33 |