图 书 馆
使用标签均值的半监督学习Semi-Supervised Learning Using Label Mean |
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| 课程网址: | http://videolectures.net/icml09_li_ssl/ |
| 主讲教师: | Yu-Feng Li |
| 开课单位: | 南京大学 |
| 开课时间: | 2009-08-26 |
| 课程语种: | 英语 |
| 中文简介: |  |
| 课程简介: | Semi-Supervised Support Vector Machines (S3VMs) typically directly estimate the label assignments for the unlabeled instances. This is often inefficient even with recent advances in the efficient training of the (supervised) SVM. In this paper, we show that S3VMs, with knowledge of the means of the class labels of the unlabeled data, is closely related to the supervised SVM with known labels on all the unlabeled data. This motivates us to first estimate the label means of the unlabeled data. Two versions of the meanS3VM, which work by maximizing the margin between the label means, are proposed. The first one is based on multiple kernel learning, while the second one is based on alternating optimization. Experiments show that both of the proposed algorithms achieve highly competitive and sometimes even the best performance as compared to the state-of-the-art semi-supervised learners. Moreover, they are more efficient than existing S3VMs. |
| 关 键 词: | 半监督; 向量机; 未标记数据 |
| 课程来源: | 视频讲座网 |
| 最后编审: | 2019-04-23：lxf |
| 阅读次数: | 117 |