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» Nonlinear functional regression: a functional RKHS approach
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IJON
2008
156views more  IJON 2008»
13 years 5 months ago
Structural identifiability of generalized constraint neural network models for nonlinear regression
Identifiability becomes an essential requirement for learning machines when the models contain physically interpretable parameters. This paper presents two approaches to examining...
Shuang-Hong Yang, Bao-Gang Hu, Paul-Henry Courn&eg...
CORR
2010
Springer
92views Education» more  CORR 2010»
13 years 1 months ago
Regression on fixed-rank positive semidefinite matrices: a Riemannian approach
The paper addresses the problem of learning a regression model parameterized by a fixed-rank positive semidefinite matrix. The focus is on the nonlinear nature of the search space...
Gilles Meyer, Silvere Bonnabel, Rodolphe Sepulchre
IJCNN
2008
IEEE
13 years 11 months ago
Fully complex-valued radial basis function networks for orthogonal least squares regression
— We consider a fully complex-valued radial basis function (RBF) network for regression application. The locally regularised orthogonal least squares (LROLS) algorithm with the D...
Sheng Chen, Xia Hong, Chris J. Harris
ESANN
2004
13 years 6 months ago
On fields of nonlinear regression models
Abstract. In the context of nonlinear regression, we consider the problem of explaining a variable y from a vector x of explanatory variables and from a vector t of conditionning v...
Bruno Pelletier, Robert Frouin
INFORMATICALT
2006
129views more  INFORMATICALT 2006»
13 years 5 months ago
On the Identification of Hammerstein Systems Having Saturation-like Functions with Positive Slopes
Abstract. The aim of the given paper is the development of an approach for parametric identification of Hammerstein systems with piecewise linear nonlinearities, i.e., when the sat...
Rimantas Pupeikis