图 书 馆
监督学习任务集合中成对实例的特征学习Feature-Learning from Pairs of Examples in Collections of Supervised Learning Tasks |
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| 课程网址: | http://videolectures.net/slsfs05_maurer_flpec/ |
| 主讲教师: | Andreas Maurer |
| 开课单位: | 斯特尔莫成像 |
| 开课时间: | 2007-02-25 |
| 课程语种: | 英语 |
| 中文简介: |  |
| 课程简介: | We present an algorithm which uses example pairs of equal or unequal class labels to select a projection on a kernel-induced Hilbert space. A representation of .nite dimensional projections as bounded lin- ear functionals on a space of Hilbert-Schmidt operators is exploited to give bounds on the Rademacher complexity of the class of hypotheses searched, leading to PAC-type performance guarantees for the resulting feature maps. The proposed algorithm returns the projection onto the span of the principal eigenvectors of an empirical operator constructed in terms of the example pairs. Experiments demonstrate an e¤ective trans- fer of knowledge between di¤erent but related learning tasks. |
| 关 键 词: | 有界线性函数; 主特征向量; 知识转换 |
| 课程来源: | 视频讲座网 |
| 最后编审: | 2019-09-21：cwx |
| 阅读次数: | 63 |