图 书 馆
如何独立选择高斯过程回归协方差的基础How to choose the covariance for Gaussian process regression independently of the basis |
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| 课程网址: | http://videolectures.net/gpip06_franz_hccgp/ |
| 主讲教师: | Matthias O. Franz |
| 开课单位: | 马克斯普朗克研究所 |
| 开课时间: | 信息不详。欢迎您在右侧留言补充。 |
| 课程语种: | 英语 |
| 中文简介: |  |
| 课程简介: | In Gaussian process regression, both the basis functions and their prior distribution are simultaneously specified by the choice of the covariance function. In certain problems one would like to choose the covariance independently of the basis functions (e. g., in polynomial signal processing or Wiener and Volterra analysis). We propose a solution to this problem that approximates the desired covariance function at a finite set of input points for arbitrary choices of basis functions. Our experiments show that this additional degree of freedom can lead to improved regression performance. |
| 关 键 词: | 计算机科学; 机器学习; 高斯过程 |
| 课程来源: | 视频讲座网 |
| 最后编审: | 2019-11-17：cwx |
| 阅读次数: | 14 |