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稀疏的多输出高斯过程Sparse Multi-output Gaussian Processes |
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| 课程网址: | http://videolectures.net/aispds08_alvarez_smogp/ |
| 主讲教师: | Mauricio Alvarez |
| 开课单位: | 曼彻斯特大学 |
| 开课时间: | 2008-08-05 |
| 课程语种: | 英语 |
| 中文简介: |  |
| 课程简介: | In this work we propose a sparse approximation for the full covariance matrix involved in the multiple output convolution process. We exploit the fact that each of the outputs is conditional independent of all others given the input process. This leads to an approximation for the covariance matrix which keeps intact the covariances of each output and approximates the cross-covariances terms with a low rank matrix. It has a similar form to the Partially Independent Training Conditional (PITC) approximation for a single output GP. |
| 关 键 词: | 稀疏的; 多输出; 高斯 |
| 课程来源: | 视频讲座网 |
| 最后编审: | 2019-10-31：lxf |
| 阅读次数: | 52 |