We present an algorithm to approximate large dataset by Radial Basis
Function (RBF) techniques. The method couples a fast domain decomposition
procedure with a localized stabilization method. The resulting algorithm
can eciently deal with large problems and it is robust with respect
to the typical instability of kernel methods.
%0 Conference Paper
%1 cavoretto2015approximation
%A Cavoretto, Roberto
%A De Marchi, Stefano
%A De Rossi, Alessandra
%A Perracchione, Emma
%A Santin, Gabriele
%B CMMSE 2015 : Proceedings of the 15th International Conference on
Mathematical Methods in Science and Engineering
%D 2015
%E Vigo-Aguiar, J.
%K from:mhartmann ians imported vorlaeufig
%P 317--326
%T RBF approximation of large datasets by partition of unity and local
stabilization
%X We present an algorithm to approximate large dataset by Radial Basis
Function (RBF) techniques. The method couples a fast domain decomposition
procedure with a localized stabilization method. The resulting algorithm
can eciently deal with large problems and it is robust with respect
to the typical instability of kernel methods.
%@ 978-84-617-2230-3
@inproceedings{cavoretto2015approximation,
abstract = {We present an algorithm to approximate large dataset by Radial Basis
Function (RBF) techniques. The method couples a fast domain decomposition
procedure with a localized stabilization method. The resulting algorithm
can eciently deal with large problems and it is robust with respect
to the typical instability of kernel methods.},
added-at = {2018-07-20T10:54:53.000+0200},
author = {Cavoretto, Roberto and De Marchi, Stefano and De Rossi, Alessandra and Perracchione, Emma and Santin, Gabriele},
biburl = {https://puma.ub.uni-stuttgart.de/bibtex/2a9f8b1e176e45799edcc4ff42e422259/mathematik},
booktitle = {CMMSE 2015 : Proceedings of the 15th International Conference on
Mathematical Methods in Science and Engineering},
editor = {Vigo-Aguiar, J.},
file = {:http\://www.mathematik.uni-stuttgart.de/fak8/ians/publications/files/CaDeRoPeSa2015b_www_RBF_PU_WSVD.pdf:PDF},
interhash = {711b0af26ddc7f6cc99a6c992b908782},
intrahash = {a9f8b1e176e45799edcc4ff42e422259},
isbn = {978-84-617-2230-3},
issn = {2312-0177},
keywords = {from:mhartmann ians imported vorlaeufig},
owner = {santinge},
pages = {317--326},
timestamp = {2019-12-18T14:37:55.000+0100},
title = {RBF approximation of large datasets by partition of unity and local
stabilization},
year = 2015
}