9 citations · 9 across the 4 of their papers we have counts for
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math.ST2026
On public and private binary classification with metric space valued predictors
László Györfi, Martin Kroll, Harro Walk
We consider the problem of binary classification in a framework where the predictor takes values in an arbitrary separable metric space and the label values in…
math.ST2026
Metric space valued Fréchet regression
László Györfi, Pierre Humbert, Batiste Le Bars
We consider the problem of estimating the Fréchet and conditional Fréchet mean from data taking values in separable metric spaces. Unlike Euclidean spaces, where well-established m…
math.ST2020
Strongly universally consistent nonparametric regression and classification with privatised data
Thomas Berrett, László Györfi, Harro Walk
In this paper we revisit the classical problem of nonparametric regression, but impose local differential privacy constraints. Under such constraints, the raw data $(X_1,Y_1),\ldot…