6 citations · 9 across the 9 of their papers we have counts for
11 papers
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…
On Rate-Optimal Partitioning Classification from Observable and from Privatised Data
Balázs Csanád Csáji, László Györfi, Ambrus Tamás +1
In this paper we revisit the classical method of partitioning classification and prove novel convergence rates under relaxed conditions, both for observable (non-privatised) and fo…
Distribution-free tests for lossless feature selection in classification and regression
László Györfi, Tamás Linder, Harro Walk
We study the problem of lossless feature selection for a -dimensional feature vector and label for binary classification as well as nonparametri…
Repeated Observations for Classification
Hüseyin Afşer, László Györfi, Harro Walk
We study the problem nonparametric classification with repeated observations. Let $\bX$ be the dimensional feature vector and let denote the label taking values in $\{1,\do…
Lossless Transformations and Excess Risk Bounds in Statistical Inference
László Györfi, Tamás Linder, Harro Walk
We study the excess minimum risk in statistical inference, defined as the difference between the minimum expected loss in estimating a random variable from an observed feature vect…
Convergence rates for shallow neural networks learned by gradient descent
Alina Braun, Michael Kohler, Sophie Langer +1
In this paper we analyze the error of neural network regression estimates with one hidden layer. Under the assumption that the Fourier transform of the regression function de…