图 书 馆
增强和克服负二项过程Augment-and-Conquer Negative Binomial Processes |
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| 课程网址: | http://videolectures.net/machine_zhou_negative/ |
| 主讲教师: | Mingyuan Zhou |
| 开课单位: | 杜克大学 |
| 开课时间: | 2013-01-14 |
| 课程语种: | 英语 |
| 中文简介: |  |
| 课程简介: | By developing data augmentation methods unique to the negative binomial (NB) distribution, we unite seemingly disjoint count and mixture models under the NB process framework. We develop fundamental properties of the models and derive efficient Gibbs sampling inference. We show that the gamma-NB process can be reduced to the hierarchical Dirichlet process with normalization, highlighting its unique theoretical, structural and computational advantages. A variety of NB processes with distinct sharing mechanisms are constructed and applied to topic modeling, with connections to existing algorithms, showing the importance of inferring both the NB dispersion and probability parameters. |
| 关 键 词: | 负二项; 归一化; Gibbs抽样 |
| 课程来源: | 视频讲座网 |
| 最后编审: | 2019-05-15：lxf |
| 阅读次数: | 62 |