Large Scale Online Kernel Learning
Lu, Jing1; Hoi, Steven C. H.1; Wang, Jialei2; Zhao, Peilin3; Liu, Zhi-Yong4
Source PublicationJOURNAL OF MACHINE LEARNING RESEARCH
2016
Volume17
SubtypeArticle
AbstractIn this paper, we present a new framework for large scale online kernel learning, making kernel methods efficient and scalable for large-scale online learning applications. Unlike the regular budget online kernel learning scheme that usually uses some budget maintenance strategies to bound the number of support vectors, our framework explores a completely different approach of kernel functional approximation techniques to make the subsequent online learning task efficient and scalable. Specifically, we present two different online kernel machine learning algorithms: (i) Fourier Online Gradient Descent (FOGD) algorithm that applies the random Fourier features for approximating kernel functions; and (ii) Nystrom Online Gradient Descent (NOGD) algorithm that applies the Nystrom method to approximate large kernel matrices. We explore these two approaches to tackle three online learning tasks: binary classification, multi-class classification, and regression. The encouraging results of our experiments on large-scale datasets validate the effectiveness and efficiency of the proposed algorithms, making them potentially more practical than the family of existing budget online kernel learning approaches.
KeywordOnline Learning Kernel Approximation Large Scale Machine Learning
WOS HeadingsScience & Technology ; Technology
WOS KeywordCLASSIFICATION ; ALGORITHMS ; PERCEPTRON ; LIBRARY ; SVM
Indexed BySCI
Language英语
Funding OrganizationSingapore MOE tier 1 research grant(C220/MSS14C003)
WOS Research AreaAutomation & Control Systems ; Computer Science
WOS SubjectAutomation & Control Systems ; Computer Science, Artificial Intelligence
WOS IDWOS:000391485400001
Citation statistics
Document Type期刊论文
Identifierhttp://ir.ia.ac.cn/handle/173211/13386
Collection复杂系统管理与控制国家重点实验室_机器人理论与应用
Affiliation1.Singapore Management Univ, Sch Informat Syst, 80 Stamford Rd, Singapore 178902, Singapore
2.Univ Chicago, Dept Comp Sci, 5050 S Lake Shore Dr Apt S2009, Chicago, IL 60637 USA
3.ASTAR, Inst Infocomm Res, 1 Fusionopolis Way,21-01 Connexis, Singapore 138632, Singapore
4.Chinese Acad Sci, State Key Lab Management & Control Complex Syst, 95 Zhongguancun East Rd, Beijing 100190, Peoples R China
Recommended Citation
GB/T 7714
Lu, Jing,Hoi, Steven C. H.,Wang, Jialei,et al. Large Scale Online Kernel Learning[J]. JOURNAL OF MACHINE LEARNING RESEARCH,2016,17.
APA Lu, Jing,Hoi, Steven C. H.,Wang, Jialei,Zhao, Peilin,&Liu, Zhi-Yong.(2016).Large Scale Online Kernel Learning.JOURNAL OF MACHINE LEARNING RESEARCH,17.
MLA Lu, Jing,et al."Large Scale Online Kernel Learning".JOURNAL OF MACHINE LEARNING RESEARCH 17(2016).
Files in This Item:
There are no files associated with this item.
Related Services
Recommend this item
Bookmark
Usage statistics
Export to Endnote
Google Scholar
Similar articles in Google Scholar
[Lu, Jing]'s Articles
[Hoi, Steven C. H.]'s Articles
[Wang, Jialei]'s Articles
Baidu academic
Similar articles in Baidu academic
[Lu, Jing]'s Articles
[Hoi, Steven C. H.]'s Articles
[Wang, Jialei]'s Articles
Bing Scholar
Similar articles in Bing Scholar
[Lu, Jing]'s Articles
[Hoi, Steven C. H.]'s Articles
[Wang, Jialei]'s Articles
Terms of Use
No data!
Social Bookmark/Share
All comments (0)
No comment.
 

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