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Using available information as privileged information in SVM+
Received date: 2015-09-10
Online published: 2017-08-30
In machine learning, some information is only available during learning phase. Learning using privileged information (LUPI) can provide an effective solution to the problem. Such information is called privileged information. To deal with the issue that only partial privileged information of training data is available, this paper presents an intuitive but effective strategy called extended support vector machine+ (eSVM+). Specifically, for data without privileged information, available information is used as privileged information simultaneously and further cooperate it into the SVM+ formulation. In addition, for a regular supervised learning paradigm, a similar idea is adopted that all training data are both available and privileged. Naturally, it is extended SVM (eSVM), and also a special aspect of SVM+. Experimental results show that the proposed strategy can boost generalization performance of the classifier on two benchmark expression databases, BU-3DFE and Bosphorus.
DONG Yong, SUN Guangling, LIU Zhi . Using available information as privileged information in SVM+[J]. Journal of Shanghai University, 2017 , 23(4) : 524 -534 . DOI: 10.12066/j.issn.1007-2861.1675
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