图 书 馆
完全分布式的大型数据集Fully Distributed EM for Very Large Datasets |
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| 课程网址: | http://videolectures.net/icml08_wolfe_fdem/ |
| 主讲教师: | Jason Wolfe |
| 开课单位: | 加州大学伯克利分校 |
| 开课时间: | 2008-07-30 |
| 课程语种: | 英语 |
| 中文简介: |  |
| 课程简介: | In EM and related algorithms, E-step computations distribute easily, because data items are independent given parameters. For very large data sets, however, even storing all of the parameters in a single node for the M-step can be impractical. We present a framework which fully distributes the entire EM procedure. Each node interacts with only parameters relevant to its data, sending messages to other nodes along a junction-tree topology. We demonstrate improvements over a MapReduce approach, on two tasks: word alignment and topic modeling. |
| 关 键 词: | 机器学习; 主题建模; MapReduce |
| 课程来源: | 视频讲座网 |
| 最后编审: | 2020-06-24：yumf |
| 阅读次数: | 29 |