图 书 馆
与beta过程共享动态系统的特征Sharing Features among Dynamical Systems with Beta Processes |
|
| 课程网址: | http://videolectures.net/nips09_fox_sfa/ |
| 主讲教师: | Emily Fox |
| 开课单位: | 华盛顿大学 |
| 开课时间: | 2010-01-19 |
| 课程语种: | 英语 |
| 中文简介: |  |
| 课程简介: | We propose a Bayesian nonparametric approach to relating multiple time series via a set of latent, dynamical behaviors. Using a beta process prior, we allow data-driven selection of the size of this set, as well as the pattern with which behaviors are shared among time series. Via the Indian buffet process representation of the beta process' predictive distributions, we develop an exact Markov chain Monte Carlo inference method. In particular, our approach uses the sum-product algorithm to efficiently compute Metropolis-Hastings acceptance probabilities, and explores new dynamical behaviors via birth/death proposals. We validate our sampling algorithm using several synthetic datasets, and also demonstrate promising unsupervised segmentation of visual motion capture data. |
| 关 键 词: | 贝叶斯方法; 动态行为; 时间序列 |
| 课程来源: | 视频讲座网 |
| 最后编审: | 2019-07-24：cwx |
| 阅读次数: | 39 |