图 书 馆
分层数据的树形结构分断Tree-Structured Stick Breaking for Hierarchical Data |
|
| 课程网址: | http://videolectures.net/nips2010_adams_tss/ |
| 主讲教师: | Ryan Prescott Adams |
| 开课单位: | 多伦多大学 |
| 开课时间: | 2011-01-12 |
| 课程语种: | 英语 |
| 中文简介: |  |
| 课程简介: | Many data are naturally modeled by an unobserved hierarchical structure. In this paper we propose a flexible nonparametric prior over unknown data hierarchies. The approach uses nested stick-breaking processes to allow for trees of unbounded width and depth, where data can live at any node and are infinitely exchangeable. One can view our model as providing infinite mixtures where the components have a dependency structure corresponding to an evolutionary diffusion down a tree. By using a stick-breaking approach, we can apply Markov chain Monte Carlo methods based on slice sampling to perform Bayesian inference and simulate from the posterior distribution on trees. We apply our method to hierarchical clustering of images and topic modeling of text data. |
| 关 键 词: | 层次结构; 自然建模; 马尔可夫链蒙特卡罗方法; 贝叶斯推理 |
| 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: | 59 |