图 书 馆
稀疏典范相关分析Sparse Canonical Correlation Analysis |
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| 课程网址: | http://videolectures.net/sip08_hardoon_scca/ |
| 主讲教师: | David R. Hardoon |
| 开课单位: | 伦敦全球大学 |
| 开课时间: | 2008-12-18 |
| 课程语种: | 英语 |
| 中文简介: |  |
| 课程简介: | We present a novel method for solving Canonical Correlation Analy- sis (CCA) in a sparse convex framework using a least squares approach. The presented method focuses on the scenario when one is interested in (or limited to) a primal representation for the first view while having a dual rep- resentation for the second view. Sparse CCA (SCCA) minimises the number of features used in both the primal and dual pro jections while maximising the correlation between the two views. The method is demonstrated on two paired corpuses of English-French and English-Spanish for mate-retrieval. We are able to observe, in the mate-retreival, that when the number of the original features is large SCCA outperforms Kernel CCA (KCCA), learning the common semantic space from a sparse set of features. |
| 关 键 词: | 最小二乘法; 双重表示; 双重投影 |
| 课程来源: | 视频讲座网 |
| 最后编审: | 2019-09-21：cwx |
| 阅读次数: | 355 |