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Generalization Performance of Radial Basis Function Networks
Lei, Yunwen1; Ding, Lixin1; Zhang, Wensheng2
Source PublicationIEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS
2015-03-01
Volume26Issue:3Pages:551-564
SubtypeArticle
AbstractThis paper studies the generalization performance of radial basis function (RBF) networks using local Rademacher complexities. We propose a general result on controlling local Rademacher complexities with the L-1-metric capacity. We then apply this result to estimate the RBF networks' complexities, based on which a novel estimation error bound is obtained. An effective approximation error bound is also derived by carefully investigating the Holder continuity of the l(p) loss function's derivative. Furthermore, it is demonstrated that the RBF network minimizing an appropriately constructed structural risk admits a significantly better learning rate when compared with the existing results. An empirical study is also performed to justify the application of our structural risk in model selection.
KeywordLearning Theory Local Rademacher Complexity Radial Basis Function (Rbf) Networks Structural Risk Minimization (Srm)
WOS HeadingsScience & Technology ; Technology
WOS KeywordMODEL SELECTION ; NEURAL-NETWORKS ; APPROXIMATION ; COMPLEXITY ; BOUNDS ; RISK ; REGULARIZATION ; TRACTABILITY ; REGRESSION ; ERROR
Indexed BySCI
Language英语
WOS Research AreaComputer Science ; Engineering
WOS SubjectComputer Science, Artificial Intelligence ; Computer Science, Hardware & Architecture ; Computer Science, Theory & Methods ; Engineering, Electrical & Electronic
WOS IDWOS:000351834400011
Citation statistics
Document Type期刊论文
Identifierhttp://ir.ia.ac.cn/handle/173211/9999
Collection精密感知与控制研究中心_人工智能与机器学习
Affiliation1.Wuhan Univ, Sch Comp, State Key Lab Software Engn, Wuhan 430072, Peoples R China
2.Chinese Acad Sci, Inst Automat, Beijing 100190, Peoples R China
Recommended Citation
GB/T 7714
Lei, Yunwen,Ding, Lixin,Zhang, Wensheng. Generalization Performance of Radial Basis Function Networks[J]. IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS,2015,26(3):551-564.
APA Lei, Yunwen,Ding, Lixin,&Zhang, Wensheng.(2015).Generalization Performance of Radial Basis Function Networks.IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS,26(3),551-564.
MLA Lei, Yunwen,et al."Generalization Performance of Radial Basis Function Networks".IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS 26.3(2015):551-564.
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