图 书 馆
变分贝叶斯的全局解析解Global Analytic Solution for Variational Bayesian |
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| 课程网址: | http://videolectures.net/nips2010_nakajima_gas/ |
| 主讲教师: | Shinichi Nakajima |
| 开课单位: | 尼康公司 |
| 开课时间: | 2011-03-25 |
| 课程语种: | 英语 |
| 中文简介: |  |
| 课程简介: | Bayesian methods of matrix factorization (MF) have been actively explored recently as promising alternatives to classical singular value decomposition. In this paper, we show that, despite the fact that the optimization problem is non-convex, the global optimal solution of variational Bayesian (VB) MF can be computed analytically by solving a quartic equation. This is highly advantageous over a popular VBMF algorithm based on iterated conditional modes since it can only find a local optimal solution after iterations. We further show that the global optimal solution of empirical VBMF (hyperparameters are also learned from data) can also be analytically computed. We illustrate the usefulness of our results through experiments. |
| 关 键 词: | 计算机科学; 机器学习; 贝叶斯学习 |
| 课程来源: | 视频讲座网 |
| 最后编审: | 2020-06-06：zyk |
| 阅读次数: | 81 |