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» Learning fault-tolerance in Radial Basis Function Networks
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ESANN
2001
13 years 8 months ago
Constructive density estimation network based on several different separable transfer functions
Networks estimating probability density are usually based on radial basis function of the same type. Feature Space Mapping constructive network based on separable functions, optimi...
Wlodzislaw Duch, Rafal Adamczak, Geerd H. F. Dierc...
NPL
1998
175views more  NPL 1998»
13 years 7 months ago
Prediction of Chaotic Time-Series with a Resource-Allocating RBF Network
Abstract. One of the main problems associated with arti cial neural networks online learning methods is the estimation of model order. In this paper, we report about a new approach...
Roman Rosipal, Milos Koska, Igor Farkas
ICANN
2001
Springer
13 years 12 months ago
Incremental Support Vector Machine Learning: A Local Approach
Abstract. In this paper, we propose and study a new on-line algorithm for learning a SVM based on Radial Basis Function Kernel: Local Incremental Learning of SVM or LISVM. Our meth...
Liva Ralaivola, Florence d'Alché-Buc
COLT
1994
Springer
13 years 11 months ago
Lower Bounds on the VC-Dimension of Smoothly Parametrized Function Classes
We examine the relationship between the VCdimension and the number of parameters of a smoothly parametrized function class. We show that the VC-dimension of such a function class ...
Wee Sun Lee, Peter L. Bartlett, Robert C. Williams...
TNN
2008
119views more  TNN 2008»
13 years 7 months ago
Selecting Useful Groups of Features in a Connectionist Framework
Abstract--Suppose for a given classification or function approximation (FA) problem data are collected using sensors. From the output of the th sensor, features are extracted, ther...
Debrup Chakraborty, Nikhil R. Pal