图 书 馆
低等级和缺失数据的分类Classification with Low Rank and Missing Data |
|
| 课程网址: | http://videolectures.net/icml2015_livni_classification/ |
| 主讲教师: | Roi Livni |
| 开课单位: | 耶路撒冷希伯来大学 |
| 开课时间: | 2015-09-27 |
| 课程语种: | 英语 |
| 中文简介: |  |
| 课程简介: | We consider classification and regression tasks where we have missing data and assume that the (clean) data resides in a low rank subspace. Finding a hidden subspace is known to be computationally hard. Nevertheless, using a non-proper formulation we give an efficient agnostic algorithm that classifies as good as the best linear classifier coupled with the best low-dimensional subspace in which the data resides. A direct implication is that our algorithm can linearly (and non-linearly through kernels) classify provably as well as the best classifier that has access to the full data. |
| 关 键 词: | 缺失数据; 回归任务; 最佳分类器 |
| 课程来源: | 视频讲座网 |
| 数据采集: | 2022-12-12：chenjy |
| 最后编审: | 2022-12-12：chenjy |
| 阅读次数: | 15 |