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Régression linéaire au sens des moindres carrés à partir de sous-espaces vectoriels aléatoires
Régression linéaire au sens des moindres carrés à partir de sous-espaces vectoriels aléatoires
Exposé en français mais transparents en anglais I will present recent works on least-squares regression using randomly generated subspaces.In this approach, the regression function is the empirical risk minimizer in a low dimensional randomly generated subspace of a high (possibly infinite) dimensional function space. This approach can be seen as an alternative to usual penalization techniques. Approximation error and excess risk bounds are derived and the issue of numerical complexity will be discussed.This is joint work with Odalric Maillard and is described in the following papers: - Compressed Least-Squares […]