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research article
Regularization networks: fast weight calculation via Kalman filtering
De Nicolao, G.
•
Ferrari-Trecate, G.
Regularization networks are nonparametric estimators obtained from the application of Tychonov regularization or Bayes estimation to the hypersurface reconstruction problem. Their main drawback is that the computation of the weights scales as $O(n^3)$ where $n$ is the number of data. In this paper we show that for a class of monodimensional problems, the complexity can be reduced to $O(n)$ by a suitable algorithm based on spectral factorization and Kalman filtering. Moreover, the procedure applies also to smoothing splines.
Type
research article
Authors
De Nicolao, G.
•
Ferrari-Trecate, G.
Publication date
2001
Published in
Volume
12
Issue
2
Start page
228
End page
235
Peer reviewed
REVIEWED
EPFL units
Available on Infoscience
January 10, 2017
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