图 书 馆
半监督学习与敌对的失踪的标签信息Semi-Supervised Learning with Adversarially Missing Label Information |
|
| 课程网址: | http://videolectures.net/nips2010_syed_ssl/ |
| 主讲教师: | Umar Syed |
| 开课单位: | 宾夕法尼亚大学 |
| 开课时间: | 2011-01-12 |
| 课程语种: | 英语 |
| 中文简介: |  |
| 课程简介: | We address the problem of semi-supervised learning in an adversarial setting. Instead of assuming that labels are missing at random, we analyze a less favorable scenario where the label information can be missing partially and arbitrarily, which is motivated by several practical examples. We present nearly matching upper and lower generalization bounds for learning in this setting under reasonable assumptions about available label information. Motivated by the analysis, we formulate a convex optimization problem for parameter estimation, derive an efficient algorithm, and analyze its convergence. We provide experimental results on several standard data sets showing the robustness of our algorithm to the pattern of missing label information, outperforming several strong baselines. |
| 关 键 词: | 计算机科学; 机器学习; 半监督学习 |
| 课程来源: | 视频讲座网 |
| 最后编审: | 2019-11-16：cwx |
| 阅读次数: | 36 |