中国科学院机构知识库网格
Chinese Academy of Sciences Institutional Repositories Grid
margin-based transfer learning

文献类型:会议论文

作者Su Bai ; Xu Wei ; Shen Yidong
出版日期2009
会议名称6th International Symposium on Neural Networks
会议日期2009
会议地点Wuhan, PEOPLES R CHINA
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Huazhong Univ Sci & Technol, Chinese Univ Hong Kong, Natl Nat Sci Fdn China, IEEE Wuhan Sect, IEEE Computat Intelligence Soc, Int Neural Network Soc, Asia Pacific Neural Network Assembly, Euorpean Neural Network Soc, Hubei Province, Syst Engn Soc, IEEE Hong Kong Joint Chapter Robot & Automat & Control Syst
会议录出版者SIXTH INTERNATIONAL SYMPOSIUM ON NEURAL NETWORKS (ISNN 2009)
会议录出版地HEIDELBERGER PLATZ 3, D-14197 BERLIN, GERMANY
ISSN号1867-5662
ISBN号978-3-642-01215-0
源URL[http://124.16.136.157/handle/311060/8322]  
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,Xu Wei,Shen Yidong. margin-based transfer learning[C]. 见:6th International Symposium on Neural Networks. Wuhan, PEOPLES R CHINA. 2009.

入库方式: OAI收割

来源:软件研究所

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