图 书 馆
被动和主动学习的下界Lower Bounds for Passive and Active Learning |
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| 课程网址: | http://videolectures.net/nips2011_raginsky_passiveactive/ |
| 主讲教师: | Maxim Raginsky |
| 开课单位: | 杜克大学 |
| 开课时间: | 2012-09-06 |
| 课程语种: | 英语 |
| 中文简介: |  |
| 课程简介: | We develop unified information-theoretic machinery for deriving lower bounds for passive and active learning schemes. Our bounds involve the so-called Alexander's capacity function. The supremum of this function has been recently rediscovered by Hanneke in the context of active learning under the name of "disagreement coefficient". For passive learning, our lower bounds match the upper bounds of Gine and Koltchinskii up to constants and generalize analogous results of Massart and Nedelec. For active learning, we provide first known lower bounds based on the capacity function rather than the disagreement coefficient. |
| 关 键 词: | 信息理论机制; 被动学习; 主动学习 |
| 课程来源: | 视频讲座网 |
| 最后编审: | 2019-09-06：lxf |
| 阅读次数: | 53 |