图 书 馆
灵活高效的高斯过程模型Flexible and efficient Gaussian process models |
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| 课程网址: | http://videolectures.net/gpip06_snelson_fegpm/ |
| 主讲教师: | Edward Snelson |
| 开课单位: | 伦敦大学学院 |
| 开课时间: | 2007-02-25 |
| 课程语种: | 英语 |
| 中文简介: |  |
| 课程简介: | I will briefly describe our work on the sparse pseudo-input Gaussian process (SPGP), where we refine the sparse approximation by selecting `pseudo-inputs' using gradient methods. I will then describe several extensions to this framework. Firstly we incorporate supervised dimensionality reduction to deal with high dimensional input spaces. Secondly we develop a version of the SPGP that can handle input-dependent noise. These extensions allow GP methods to be applied to a wider variety of modelling tasks than previously possible. |
| 关 键 词: | 高斯过程; 梯度方法; 伪输入 |
| 课程来源: | 视频讲座网 |
| 最后编审: | 2020-06-12：王勇彬(课程编辑志愿者) |
| 阅读次数: | 143 |