图 书 馆
高维图形模型选择High-Dimensional Graphical Model Selection |
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| 课程网址: | http://videolectures.net/nips2011_anandkumar_conditions/ |
| 主讲教师: | Animashree Anandkumar |
| 开课单位: | 加利福尼亚大学 |
| 开课时间: | 2012-01-25 |
| 课程语种: | 英语 |
| 中文简介: |  |
| 课程简介: | We consider the problem of Ising and Gaussian graphical model selection given n i.i.d. samples from the model. We propose an efficient threshold-based algorithm for structure estimation based known as conditional mutual information test. This simple local algorithm requires only low-order statistics of the data and decides whether two nodes are neighbors in the unknown graph. Under some transparent assumptions, we establish that the proposed algorithm is structurally consistent (or sparsistent) when the number of samples scales as n= Omega(J_{min}^{-4} log p), where p is the number of nodes and J_{min} is the minimum edge potential. We also prove novel non-asymptotic necessary conditions for graphical model selection. |
| 关 键 词: | 图形模型选择; 结构估计算法; 低阶统计量 |
| 课程来源: | 视频讲座网 |
| 最后编审: | 2019-07-26：cwx |
| 阅读次数: | 45 |