Large Scale Online Kernel Learning
Lu, Jing1; Hoi, Steven C. H.1; Wang, Jialei2; Zhao, Peilin3; Liu, Zhi-Yong4
2016
发表期刊JOURNAL OF MACHINE LEARNING RESEARCH
卷号17
文章类型Article
摘要In 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.
关键词Online Learning Kernel Approximation Large Scale Machine Learning
WOS标题词Science & Technology ; Technology
关键词[WOS]CLASSIFICATION ; ALGORITHMS ; PERCEPTRON ; LIBRARY ; SVM
收录类别SCI
语种英语
项目资助者Singapore MOE tier 1 research grant(C220/MSS14C003)
WOS研究方向Automation & Control Systems ; Computer Science
WOS类目Automation & Control Systems ; Computer Science, Artificial Intelligence
WOS记录号WOS:000391485400001
引用统计
被引频次:13[WOS]   [WOS记录]     [WOS相关记录]
文献类型期刊论文
条目标识符http://ir.ia.ac.cn/handle/173211/13386
专题复杂系统管理与控制国家重点实验室_机器人理论与应用
作者单位1.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
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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).
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