Radial Basis Function Networks and Complexity Regularization in Function Learning and Classification

I
ICPR
2000
15th International Conference on Pattern Recognition (ICPR'00) - Volume 2
Abstract - Radial Basis Function Networks and Complexity Regularization in Function Learning and Classification

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15th International Conference on Pattern Recognition (ICPR'00) - Volume 2

Barcelona, Spain

September 03-September 08

ISBN: 0-7695-0750-6

	ASCII Text	x
	Balázs Kégl, Adam Krzyzak, Heinrich Niemann, "Radial Basis Function Networks and Complexity Regularization in Function Learning and Classification," Pattern Recognition, International Conference on, vol. 2, pp. 2081, 15th International Conference on Pattern Recognition (ICPR'00) - Volume 2, 2000.

	BibTex	x
	@article{ 10.1109/ICPR.2000.906022, author = {Balázs Kégl and Adam Krzyzak and Heinrich Niemann}, title = {Radial Basis Function Networks and Complexity Regularization in Function Learning and Classification}, journal ={Pattern Recognition, International Conference on}, volume = {2}, year = {2000}, isbn = {0-7695-0750-6}, pages = {2081}, doi = {http://doi.ieeecomputersociety.org/10.1109/ICPR.2000.906022}, publisher = {IEEE Computer Society}, address = {Los Alamitos, CA, USA}, }

	RefWorks Procite/RefMan/Endnote	x
	TY - CONF JO - Pattern Recognition, International Conference on TI - Radial Basis Function Networks and Complexity Regularization in Function Learning and Classification SN - 0-7695-0750-6 SP EP A1 - Balázs Kégl, A1 - Adam Krzyzak, A1 - Heinrich Niemann, PY - 2000 VL - 2 JA - Pattern Recognition, International Conference on ER -

Balázs Kégl, Queen's University

Adam Krzyzak, Concordia University

Heinrich Niemann, University of Erlangen-N?rnberg

DOI Bookmark: http://doi.ieeecomputersociety.org/10.1109/ICPR.2000.906022

In this paper, we apply complexity regularization to learn normalized radial basis function networks in nonparametric classification. We study convergence and the rates of convergence of the empirically trained networks and verify the results in computer experiments.

Citation:

Balázs Kégl, Adam Krzyzak, Heinrich Niemann, "Radial Basis Function Networks and Complexity Regularization in Function Learning and Classification," icpr, vol. 2, pp.2081, 15th International Conference on Pattern Recognition (ICPR'00) - Volume 2, 2000

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