Robust support vector machines based on the rescaled hinge loss function

doi:10.1016/j.patcog.2016.09.045

CORC > 自动化研究所 > 中国科学院自动化研究所 > 模式识别国家重点实验室 > 多媒体计算与图形学团队

	Robust support vector machines based on the rescaled hinge loss function
	Xu, Guibiao1 ; Cao, Zheng 2; Hu, Bao-Gang1 ; Principe, Jose C.2
刊名	PATTERN RECOGNITION
	2017-03-01
卷号	63 页码:139-148
关键词	Support Vector Machine Robustness Rescaled Hinge Loss Half-quadratic Optimization
DOI	10.1016/j.patcog.2016.09.045
文献子类	Article
英文摘要	The support vector machine (SVM) is a popular classifier in machine learning, but it is not robust to outliers. In this paper, based on the Correntropy induced loss function, we propose the resealed hinge loss function which is a monotonic, bounded and nonconvex loss that is robust to outliers. We further show that the hinge loss is a special case of the proposed resealed hinge loss. Then, we develop a new robust SVM based on the resealed hinge loss. After using the half-quadratic optimization method, we find that the new robust SVM is equivalent to an iterative weighted SVM, which can help explain the robustness of iterative weighted SVM from a loss function perspective. Experimental results confirm that the new robust SVM not only performs better than SVM and the existing robust SVMs on the datasets that have outliers, but also presents better sparseness than SVM.
WOS关键词	CLASSIFICATION ; MINIMIZATION ; RECOGNITION ; CORRENTROPY ; SIGNAL
WOS研究方向	Computer Science ; Engineering
语种	英语
WOS记录号	WOS:000389785900011
资助机构	NSFC(61273196) ; China Scholarship Council
内容类型	期刊论文
源URL	[http://ir.ia.ac.cn/handle/173211/13367]
专题	自动化研究所_模式识别国家重点实验室_多媒体计算与图形学团队
作者单位	1.Chinese Acad Sci, Inst Automat, NLPR, Beijing 100190, Peoples R China 2.Univ Florida, CNEL, Dept Elect & Comp Engn, Gainesville, FL 32611 USA
推荐引用方式 GB/T 7714	Xu, Guibiao,Cao, Zheng,Hu, Bao-Gang,et al. Robust support vector machines based on the rescaled hinge loss function[J]. PATTERN RECOGNITION,2017,63:139-148.
APA	Xu, Guibiao,Cao, Zheng,Hu, Bao-Gang,&Principe, Jose C..(2017).Robust support vector machines based on the rescaled hinge loss function.PATTERN RECOGNITION,63,139-148.
MLA	Xu, Guibiao,et al."Robust support vector machines based on the rescaled hinge loss function".PATTERN RECOGNITION 63(2017):139-148.