Research Semester Programme Machine Learning TheorySeminar++


Seminar++ meetings consist of a one-hour lecture building up to an open problem, followed by an hour of brainstorming time. The meeting is intended for interested researchers including PhD students. These meetings are freely accessible without registration. Cookies and tea will be provided in the half-time break.

This lecture is part of a series of 8.

Rianne de Heide

Rianne de Heide
Assistant Professor at the Vrije Universiteit Amsterdam.

Multiple testing with e-values: overview and open problems

Abstract: Researchers in genomics and neuroimaging often perform hundreds of thousands of hypothesis tests simultaneously. The scale of these multiple hypothesis testing problems is enormous, and with extreme dimensionality comes extreme risk for false positives. The field of multiple testing addresses this problem in various ways. Recently, the new theory of hypothesis testing with e-values has been brought to the field of multiple testing. In this talk I will give an overview of the most important frameworks in multiple testing and recent developments in multiple testing with e-values. Finally, I will open the discussion for open problems in this area, focusing on FDP estimation and confidence with e-values. This will create a framework for fully interactive multiple testing.