2 citations · 2 across the 2 of their papers we have counts for
6 papers · 1 filter
Private Rate-Double-Robust Inference
Máté Kormos, Aad van der Vaart
We reconcile privacy protection and rate-double-robust inference. The privacy of individuals is protected by a local privacy mechanism: injecting noise into their sensitive data, r…
Adaptation using spatially distributed Gaussian Processes
Botond Szabo, Amine Hadji, Aad van der Vaart
We consider the accuracy of an approximate posterior distribution in nonparametric regression problems by combining posterior distributions computed on subsets of the data defined…
Optimal testing using combined test statistics across independent studies
Botond Szabó, Aad van der Vaart, Lasse Vuursteen +1
Combining test statistics from independent trials or experiments is a popular method of meta-analysis. However, there is very limited theoretical understanding of the power of the…
Adaptive and Efficient Isotonic Estimation in Wicksell's Problem
Francesco Gili, Geurt Jongbloed, Aad van der Vaart
We consider nonparametric estimation in Wicksell's problem which has relevant applications in astronomy for estimating the distribution of the positions of the stars in a galaxy gi…
Semi-parametric Bernstein-von Mises in Linear Inverse Problems
Adel Magra, Aad van der Vaart, Harry van Zanten
We consider a Bayesian approach for the recovery of scalar parameters arising in inverse problems. We consider a general signal-in white noise model where we have access to two ind…
Misspecified Bernstein-Von Mises theorem for hierarchical models
Geerten Koers, Botond Szabó, Aad van der Vaart
We derive a Bernstein von-Mises theorem in the context of misspecified, non-i.i.d., hierarchical models parametrized by a finite-dimensional parameter of interest. We apply our res…