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On the Curse of Dimensionality in Supervised Learning of Smooth Regression Functions

✍ Scribed by Elia Liitiäinen; Francesco Corona; Amaury Lendasse


Book ID
106483097
Publisher
Springer US
Year
2011
Tongue
English
Weight
345 KB
Volume
34
Category
Article
ISSN
1370-4621

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A variety of statistical problems (e.g. the x-intercept in linear regression, the abscissa of the point of intersection of two simple linear regression lines or the point of extremum in quadratic regression) can be viewed as questions of inference on nonlinear functions of the parameters in the gene