3.5k citations · 3.7k across the 15 of their papers we have counts for
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stat.ML2020
Minimum discrepancy principle strategy for choosing in -NN regression
Yaroslav Averyanov, Alain Celisse
We present a novel data-driven strategy to choose the hyperparameter in the -NN regression estimator without using any hold-out data. We treat the problem of choosing the hy…
stat.ML2020
Early stopping and polynomial smoothing in regression with reproducing kernels
Yaroslav Averyanov, Alain Celisse
In this paper, we study the problem of early stopping for iterative learning algorithms in a reproducing kernel Hilbert space (RKHS) in the nonparametric regression framework. In p…
math.ST2020
Analyzing the discrepancy principle for kernelized spectral filter learning algorithms
Alain Celisse, Martin Wahl
We investigate the construction of early stopping rules in the nonparametric regression problem where iterative learning algorithms are used and the optimal iteration number is unk…