Optimal Rates for Regularization of Statistical Inverse Learning Problems

Autor: Gilles Blanchard, Nicole Mücke

Publikováno v: Foundations of Computational Mathematics
Foundations of Computational Mathematics, Springer Verlag, 2018, 18 (4), pp.971-1013. ⟨10.1007/s10208-017-9359-7⟩

We consider a statistical inverse learning (also called inverse regression) problem, where we observe the image of a function f through a linear operator A at i.i.d. random design points $$X_i$$ , superposed with an additive noise. The distribution o

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