2 citations · 3 across the 5 of their papers we have counts for
6 papers
Confidence envelopes for the false discoveries with heterogeneous data
Romain Périer, Gilles Blanchard, Sebastian Döhler +2
In the context of selective inference, confidence envelopes for the false discoveries allow the user to select any subset of null hypotheses while having a statistical guarantee on…
POLTER: Policy Trajectory Ensemble Regularization for Unsupervised Reinforcement Learning
Frederik Schubert, Carolin Benjamins, Sebastian Döhler +2
The goal of Unsupervised Reinforcement Learning (URL) is to find a reward-agnostic prior policy on a task domain, such that the sample-efficiency on supervised downstream tasks is…
Controlling false discovery exceedance for heterogeneous tests
Sebastian Döhler, Etienne Roquain
Several classical methods exist for controlling the false discovery exceedance (FDX) for large scale multiple testing problems, among them the Lehmann-Romano procedure ([LR] below)…
Improving the Benjamini-Hochberg Procedure for Discrete Tests
Sebastian Döhler, Guillermo Durand, Etienne Roquain
To find interesting items in genome-wide association studies or next generation sequencing data, a crucial point is to design powerful false discovery rate (FDR) controlling proced…
A discrete modification of the Benjamini-Yekutieli procedure
Sebastian Döhler
The Benjamini-Yekutieli procedure is a multiple testing method that controls the false discovery rate under arbitrary dependence of the -values. A modification of this and relat…
A sufficient criterion for control of generalised error rates in multiple testing
Sebastian Döhler
Based on the work of Romano and Shaikh (2006) and Lehmann and Romano (2005) we give a sufficient criterion for controlling generalised error rates for arbitrarily dependent p-value…