3 papers
math.ST2026
A Minimax Theory of Nonparametric Regression Under Covariate Shift
Petr Zamolodtchikov
We consider nonparametric regression under covariate shift, where we observe samples from both the target distribution and a related but distinct source distribution. We introduce…
math.ST2025
On empirical Hodge Laplacians under the manifold hypothesis
Jan-Paul Lerch, Martin Wahl, Petr Zamolodtchikov
Given i.i.d. observations uniformly distributed on a closed submanifold of the Euclidean space, we study higher-order generalizations of graph Laplacians, so-called Hodge Laplacian…
math.ST2024
Generative Modelling via Quantile Regression
Johannes Schmidt-Hieber, Petr Zamolodtchikov
We link conditional generative modelling to quantile regression. We propose a suitable loss function and derive minimax convergence rates for the associated risk under smoothness a…