DocumentCode
508196
Title
Variable Weighted Learning Algorithm and Its Convergence Rate
Author
Fangyuan Yu ; Zhenfa Hu
Author_Institution
Sch. of Sci., Hubei Automotive Ind. Inst., Shiyan, China
Volume
1
fYear
2009
fDate
14-16 Aug. 2009
Firstpage
373
Lastpage
377
Abstract
Variable weighted learning Algorithm based on empirical data is introduced and the classical principle empirical risk minimization becomes its special case.The estimates of the convergence rate are given via integral operators and their approximations.
Keywords
convergence; integral equations; learning (artificial intelligence); minimisation; convergence rate; empirical risk minimization; integral operators; variable weighted learning; Automotive engineering; Biological system modeling; Computer industry; Convergence; Extraterrestrial measurements; Hilbert space; Kernel; Machine learning; Probability distribution; Risk management; Empirical risk minimization; Variable weighted learning algorithm; integral operators;
fLanguage
English
Publisher
ieee
Conference_Titel
Natural Computation, 2009. ICNC '09. Fifth International Conference on
Conference_Location
Tianjin
Print_ISBN
978-0-7695-3736-8
Type
conf
DOI
10.1109/ICNC.2009.397
Filename
5365948
Link To Document