maximum margin transfer learning
文献类型：会议论文
| 作者 | Su Bai ; Shen Yi-Dong |
| 出版日期 | 2009 |
| 会议名称 | World Summit on Genetic and Evolutionary Computation (GEC 09) |
| 会议日期 | JUN 12-14, |
| 会议地点 | Shanghai, PEOPLES R CHINA |
| 关键词 | Labels Semiconducting germanium compounds |
| 英文摘要 | To achieve good generalization in supervised learning, the training and testing examples are usually required to be drawn from the same source distribution. However, in many cases, this identical distribution assumption might be violated when a task from one new domain(target domain) comes, while there are only labeled data from a similar old domain(auxiliary domain). Labeling the new data can be costly and it would also be a waste to throw away all the old data. In this paper, we present a discriminative approach that utilizes the intrinsic geometry of input patterns revealed by unlabeled data, points and derive a maximum-margin formulation of unsupervised transfer learning. Two alternative solutions are proposed to solve the problem. Experimental results on many real data. sets demonstrate the effectiveness and the potential of the proposed methods. |
| 会议主办者 | ACM SIGEVO |
| 会议录 | 2009 World Summit on Genetic and Evolutionary Computation, 2009 GEC Summit - Proceedings of the 1st ACM/SIGEVO Summit on Genetic and Evolutionary Computation, GEC09
 |
| 会议录出版者 | WORLD SUMMIT ON GENETIC AND EVOLUTIONARY COMPUTATION (GEC 09) |
| 会议录出版地 | 1515 BROADWAY, NEW YORK, NY 10036-9998 USA |
| ISBN号 | 978-1-60558-326-6 |
| 源URL | [http://124.16.136.157/handle/311060/8198]  |
| 专题 | 软件研究所_计算机科学国家重点实验室 _会议论文 |
| 推荐引用方式 GB/T 7714 | Su Bai,Shen Yi-Dong. maximum margin transfer learning[C]. 见:World Summit on Genetic and Evolutionary Computation (GEC 09). Shanghai, PEOPLES R CHINA. JUN 12-14,. |
入库方式： OAI收割
来源：软件研究所
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