Generalization Performance of Radial Basis Function Networks
文献类型:期刊论文
作者 | Lei, Yunwen1; Ding, Lixin1; Zhang, Wensheng2![]() |
刊名 | IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS
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出版日期 | 2015-03-01 |
卷号 | 26期号:3页码:551-564 |
关键词 | Learning theory local Rademacher complexity radial basis function (RBF) networks structural risk minimization (SRM) |
英文摘要 | This 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. |
WOS标题词 | Science & Technology ; Technology |
类目[WOS] | Computer Science, Artificial Intelligence ; Computer Science, Hardware & Architecture ; Computer Science, Theory & Methods ; Engineering, Electrical & Electronic |
研究领域[WOS] | Computer Science ; Engineering |
关键词[WOS] | MODEL SELECTION ; NEURAL-NETWORKS ; APPROXIMATION ; COMPLEXITY ; BOUNDS ; RISK ; REGULARIZATION ; TRACTABILITY ; REGRESSION ; ERROR |
收录类别 | SCI |
语种 | 英语 |
WOS记录号 | WOS:000351834400011 |
公开日期 | 2015-12-24 |
源URL | [http://ir.ia.ac.cn/handle/173211/9999] ![]() |
专题 | 精密感知与控制研究中心_人工智能与机器学习 |
作者单位 | 1.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 |
推荐引用方式 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. |
入库方式: OAI收割
来源:自动化研究所
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