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International Symposium on Neural Networks

ISNN 2008: Advances in Neural Networks - ISNN 2008 pp 741–752Cite as

Theoretical Analysis of a Rigid Coreset Minimum Enclosing Ball Algorithm for Kernel Regression Estimation

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Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 5263))

Abstract

A rigid coreset minimum enclosing ball training machine for kernel regression estimation was proposed. First, it transfers the kernel regression estimation machine problem into a center-constrained minimum enclosing ball representation form, and subsequently trains the kernel methods using the proposed MEB algorithm. The primal variables of the kernel methods are recovered via KKT conditions. Then, detailed theoretical analysis and main theoretical results of our new algorithm are given. It can be concluded that our proposed MEB training algorithm is independent of sample dimension and the time complexity is linear in sample numbers, which greatly cuts down the complexity level and is expected to speedup the learning process obviously. Finally, comments about the future development directions are discussed.

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Author information

Authors and Affiliations

  1. Beijing Aeronautical Technology Research Center, Beijing, 100076, China

    Xunkai Wei

  2. Air Force Engineering University, Xian, 710038,  

    Xunkai Wei & Yinghong Li

Authors
  1. Xunkai Wei
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  2. Yinghong Li
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Editor information

Editors and Affiliations

  1. Department of Computer Science and Technology, Tsinghu University, 100084, Beijing, China

    Fuchun Sun

  2. Institute TAMS (Technical Aspects of Multimodal Systems), department of Informatics, University of Hamburg, Vogt-Koelln-Straße 30, 22527, Hamburg, Germany

    Jianwei Zhang

  3. Intel China Research Center, 8/F, Peking University, Department of Machine Intelligence, 100871, Beijing, China

    Ying Tan

  4. Department of Mathematics, Southeast University, 210096, Nanjing, China

    Jinde Cao

  5. Departamento de Control Automático, CINVESTAV-IPN, A.P. 14-740, Av.IPN 2508, 07360, México D.F., México

    Wen Yu

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© 2008 Springer-Verlag Berlin Heidelberg

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Wei, X., Li, Y. (2008). Theoretical Analysis of a Rigid Coreset Minimum Enclosing Ball Algorithm for Kernel Regression Estimation. In: Sun, F., Zhang, J., Tan, Y., Cao, J., Yu, W. (eds) Advances in Neural Networks - ISNN 2008. ISNN 2008. Lecture Notes in Computer Science, vol 5263. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-87732-5_83

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  • DOI: https://doi.org/10.1007/978-3-540-87732-5_83

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-87731-8

  • Online ISBN: 978-3-540-87732-5

  • eBook Packages: Computer ScienceComputer Science (R0)

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