SIA OpenIR  > 机器人学研究室
Fast Learning With Polynomial Kernels
Lin SB(林绍波)1,2; Zeng, Jinshan3
Department机器人学研究室
Source PublicationIEEE Transactions on Cybernetics
ISSN2168-2267
2019
Volume49Issue:10Pages:3780-3792
Indexed BySCI ; EI
EI Accession number20182905567539
WOS IDWOS:000473443900015
Contribution Rank1
KeywordKernel Methods Learning Systems Learning Theory Polynomial Kernel
Abstract

This paper proposes a new learning system of low computational cost, called fast polynomial kernel learning (FPL), based on regularized least squares with polynomial kernel and subsampling. The almost optimal learning rate as well as the feasibility verifications including the subsampling mechanism and solvability of FPL are provided in the framework of learning theory. Our theoretical assertions are verified by numerous toy simulations and real data applications. The studies in this paper show that FPL can reduce the computational burden of kernel methods without sacrificing its generalization ability very much.

Language英语
WOS SubjectAutomation & Control Systems ; Computer Science, Artificial Intelligence ; Computer Science, Cybernetics
WOS KeywordBIG DATA ; REGULARIZATION ; APPROXIMATION ; RATES
WOS Research AreaAutomation & Control Systems ; Computer Science
Funding ProjectNational Natural Science Foundation of China[11771012] ; National Natural Science Foundation of China[61502342] ; State Key Laboratory of Robotics[2018-O05] ; NNSFC[61603162] ; NNSFC[11501440] ; NNSFC[61772246] ; NNSFC[61603163] ; Doctoral Start-Up Foundation of Jiangxi Normal University ; National Natural Science Foundation of China[11771012] ; National Natural Science Foundation of China[61502342] ; State Key Laboratory of Robotics[2018-O05] ; NNSFC[61603162] ; NNSFC[11501440] ; NNSFC[61772246] ; NNSFC[61603163] ; Doctoral Start-Up Foundation of Jiangxi Normal University
Citation statistics
Cited Times:2[WOS]   [WOS Record]     [Related Records in WOS]
Document Type期刊论文
Identifierhttp://ir.sia.cn/handle/173321/22139
Collection机器人学研究室
Corresponding AuthorZeng, Jinshan
Affiliation1.Department of Mathematics, Wenzhou University, Wenzhou 325035, China
2.State Key Laboratory of Robotics, Shenyang Institute of Automation, Chinese Academy of Sciences, Shenyang 110016, China
3.School of Computer and Information Engineering, Jiangxi Normal University, Nanchang 330022, China
Recommended Citation
GB/T 7714
Lin SB,Zeng, Jinshan. Fast Learning With Polynomial Kernels[J]. IEEE Transactions on Cybernetics,2019,49(10):3780-3792.
APA Lin SB,&Zeng, Jinshan.(2019).Fast Learning With Polynomial Kernels.IEEE Transactions on Cybernetics,49(10),3780-3792.
MLA Lin SB,et al."Fast Learning With Polynomial Kernels".IEEE Transactions on Cybernetics 49.10(2019):3780-3792.
Files in This Item:
File Name/Size DocType Version Access License
Fast Learning With P(1160KB)期刊论文作者接受稿开放获取CC BY-NC-SAView Application Full Text
Related Services
Recommend this item
Bookmark
Usage statistics
Export to Endnote
Google Scholar
Similar articles in Google Scholar
[Lin SB(林绍波)]'s Articles
[Zeng, Jinshan]'s Articles
Baidu academic
Similar articles in Baidu academic
[Lin SB(林绍波)]'s Articles
[Zeng, Jinshan]'s Articles
Bing Scholar
Similar articles in Bing Scholar
[Lin SB(林绍波)]'s Articles
[Zeng, Jinshan]'s Articles
Terms of Use
No data!
Social Bookmark/Share
File name: Fast Learning With Polynomial Kernels .pdf
Format: Adobe PDF
All comments (0)
No comment.
 

Items in the repository are protected by copyright, with all rights reserved, unless otherwise indicated.