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题名:
margin-based transfer learning
作者: Su Bai ; Xu Wei ; Shen Yidong
会议名称: 6th International Symposium on Neural Networks
会议日期: 2009
出版日期: 2009
会议地点: Wuhan, PEOPLES R CHINA
出版者: SIXTH INTERNATIONAL SYMPOSIUM ON NEURAL NETWORKS (ISNN 2009)
出版地: HEIDELBERGER PLATZ 3, D-14197 BERLIN, GERMANY
ISSN: 1867-5662
ISBN: 978-3-642-01215-0
部门归属: Su, Bai; Shen, Yidong Chinese Acad Sci, Inst Software, State Key Lab Comp Sci, Beijing 100864, Peoples R China.
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
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.
内容类型: 会议论文
URI标识: http://ir.iscas.ac.cn/handle/311060/8322
Appears in Collections:计算机科学国家重点实验室 _会议论文

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Recommended Citation:
Su Bai,Xu Wei,Shen Yidong. margin-based transfer learning[C]. 见:6th International Symposium on Neural Networks. Wuhan, PEOPLES R CHINA. 2009.
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