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Identifiability becomes an essential requirement for learning machines when the models contain physically interpretable parameters. This paper presents two approaches to examining...
The bootstrap resampling method may be efficiently used to estimate the generalization error of a family of nonlinear regression models, as artificial neural networks. The main dif...
Geoffroy Simon, Amaury Lendasse, Vincent Wertz, Mi...
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...
A simulation-based methodology is proposed to map the mean of steady-state cycle time as a function of throughput and product mix for manufacturing systems. Nonlinear regression m...
Feng Yang, Jingang Liu, Mustafa Tongarlak, Bruce E...