图 书 馆
依赖狄利克雷建设过程Construction of Dependent Dirichlet Processes |
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| 课程网址: | http://videolectures.net/nips2010_lin_cdd/ |
| 主讲教师: | Dahua Lin |
| 开课单位: | 麻省理工学院 |
| 开课时间: | 2011-01-12 |
| 课程语种: | 英语 |
| 中文简介: |  |
| 课程简介: | We present a method for constructing dependent Dirichlet processes. The new approach exploits the intrinsic relationship between Dirichlet and Poisson processes in order to create a Markov chain of Dirichlet processes suitable for use as a prior over evolving mixture models. The method allows for the creation, removal, and location variation of component models over time while maintaining the property that the random measures are marginally DP distributed. Additionally, we derive a Gibbs sampling algorithm for model inference and test it on both synthetic and real data. Empirical results demonstrate that the approach is effective in estimating dynamically varying mixture models. |
| 关 键 词: | 计算机科学; 生物信息学; 狄利克雷过程 |
| 课程来源: | 视频讲座网 |
| 最后编审: | 2020-06-02：毛岱琦(课程编辑志愿者) |
| 阅读次数: | 41 |