1 citations · 3 across the 9 of their papers we have counts for
12 papers
Towards active learning: A stopping criterion for the sequential sampling of grain boundary degrees of freedom
Timo Schmalofski, Martin Kroll, Holger Dette +1
Many materials processes and properties depend on the anisotropy of the energy of grain boundaries, i.e.~on the fact that this energy is a function of the five geometric degrees of…
Efficient prediction of grain boundary energies from atomistic simulations via sequential design
Martin Kroll, Timo Schmalofski, Holger Dette +1
Data based materials science is the new promise to accelerate materials design. Especially in computational materials science, data generation can easily be automatized. Usually, t…
Multivariate density estimation from privatised data: universal consistency and minimax rates
László Györfi, Martin Kroll
We revisit the classical problem of nonparametric density estimation but impose local differential privacy constraints. Under such constraints, the original multivariate data $X_1,…
Asymptotic equivalence for nonparametric regression with dependent errors: Gauss-Markov processes
Holger Dette, Martin Kroll
For the class of Gauss-Markov processes we study the problem of asymptotic equivalence of the nonparametric regression model with errors given by the increments of the process and…
Adaptive spectral density estimation by model selection under local differential privacy
Martin Kroll
We study spectral density estimation under local differential privacy. Anonymization is achieved through truncation followed by Laplace perturbation. We select our estimator from a…
Pointwise adaptive kernel density estimation under local approximate differential privacy
Martin Kroll
We consider non-parametric density estimation in the framework of local approximate differential privacy. In contrast to centralized privacy scenarios with a trusted curator, in th…
Local differential privacy: Elbow effect in optimal density estimation and adaptation over Besov ellipsoids
Cristina Butucea, Amandine Dubois, Martin Kroll +1
We address the problem of non-parametric density estimation under the additional constraint that only privatised data are allowed to be published and available for inference. For t…
Rate optimal estimation of quadratic functionals in inverse problems with partially unknown operator and application to testing problems
Martin Kroll
We consider the estimation of quadratic functionals in a Gaussian sequence model where the eigenvalues are supposed to be unknown and accessible through noisy observations only. Im…
Nonparametric Poisson regression from independent and weakly dependent observations by model selection
Martin Kroll
We consider the non-parametric Poisson regression problem where the integer valued response is the realization of a Poisson random variable with parameter . The aim is to…
Nonparametric intensity estimation from noisy observations of a Poisson process under unknown error distribution
Martin Kroll
We consider the nonparametric estimation of the intensity function of a Poisson point process in a circular model from indirect observations . These observations em…
Concentration inequalities for Poisson point processes with application to adaptive intensity estimation
Martin Kroll
We derive concentration inequalities for maxima of empirical processes associated with Poisson point processes. The proofs are based on a careful application of Ledoux's entropy me…
Automated Cryptanalysis of Bloom Filter Encryptions of Health Records
Martin Kroll, Simone Steinmetzer
Privacy-preserving record linkage with Bloom filters has become increasingly popular in medical applications, since Bloom filters allow for probabilistic linkage of sensitive perso…