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research report
Regularization networks: Fast weight calculation via Kalman filtering
Ferrari-Trecate, G. De Nicolao AND G.
2000
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 report
Authors
Ferrari-Trecate, G. De Nicolao AND G.
Publication date
2000
Peer reviewed
REVIEWED
EPFL units
Available on Infoscience
January 10, 2017
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