research
∙
02/03/2023
Towards active learning: A stopping criterion for the sequential sampling of grain boundary degrees of freedom
Many materials processes and properties depend on the anisotropy of the ...
share
research
∙
05/31/2022
On rate optimal private regression under local differential privacy
We consider the problem of estimating a regression function from anonymi...
research
∙
11/26/2021
Efficient prediction of grain boundary energies from atomistic simulations via sequential design
Data based materials science is the new promise to accelerate materials ...
research
∙
07/27/2021
L_1 density estimation from privatised data
We revisit the classical problem of nonparametric density estimation, bu...
research
∙
04/19/2021
Asymptotic equivalence for nonparametric regression with dependent errors: Gauss-Markov processes
For the class of Gauss-Markov processes we study the problem of asymptot...
research
∙
10/08/2020
Adaptive spectral density estimation by model selection under local differential privacy
We study spectral density estimation under local differential privacy. A...
research
∙
07/14/2019
Pointwise adaptive kernel density estimation under local approximate differential privacy
We consider non-parametric density estimation in the framework of local ...
research
∙
03/05/2019
Local differential privacy: Elbow effect in optimal density estimation and adaptation over Besov ellipsoids
We address the problem of non-parametric density estimation under the ad...
research
∙
05/11/2018
