UM
Kernel-based sparse regression with the correntropy-induced loss
Chen, Hong; Wang, Yulong
2018-01
Source PublicationAPPLIED AND COMPUTATIONAL HARMONIC ANALYSIS
ISSN1063-5203
Volume44Issue:1Pages:144-164
AbstractThe correntropy-induced loss (C-loss) has been employed in learning algorithms to improve their robustness to non-Gaussian noise and outliers recently. Despite its success on robust learning, only little work has been done to study the generalization performance of regularized regression with the C-loss. To enrich this theme, this paper investigates a kernel-based regression algorithm with the C-loss and l(1)-regularizer in data dependent hypothesis spaces. The asymptotic learning rate is established for the proposed algorithm in terms of novel error decomposition and capacity-based analysis technique. The sparsity characterization of the derived predictor is studied theoretically. Empirical evaluations demonstrate its advantages over the related approaches. (C) 2016 Elsevier Inc. All rights reserved.
KeywordLearning theory Kernel-based regression Correntropy-induced loss Sparsity Learning rate
DOI10.1016/j.acha.2016.04.004
URLView the original
Indexed BySCI
Language英语
WOS Research AreaMathematics
WOS SubjectMathematics, Applied
WOS IDWOS:000412970500006
PublisherACADEMIC PRESS INC ELSEVIER SCIENCE
The Source to ArticleWOS
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Citation statistics
Cited Times [WOS]:3   [WOS Record]     [Related Records in WOS]
Document TypeJournal article
CollectionUniversity of Macau
Recommended Citation
GB/T 7714
Chen, Hong,Wang, Yulong. Kernel-based sparse regression with the correntropy-induced loss[J]. APPLIED AND COMPUTATIONAL HARMONIC ANALYSIS,2018,44(1):144-164.
APA Chen, Hong,&Wang, Yulong.(2018).Kernel-based sparse regression with the correntropy-induced loss.APPLIED AND COMPUTATIONAL HARMONIC ANALYSIS,44(1),144-164.
MLA Chen, Hong,et al."Kernel-based sparse regression with the correntropy-induced loss".APPLIED AND COMPUTATIONAL HARMONIC ANALYSIS 44.1(2018):144-164.
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