[Forum SIS] Seminar Saharon Rosset @ Bicocca (October 9, 2019)

[Aldo Solari]

The Department of Economics, Management and Statistics (DEMS) of the
University of Milano-Bicocca is glad to announce the following seminar:


"Optimal and Maximin Procedures for Multiple Testing Problems"
Saharon Rosset (University of Tel Aviv)


October 9, 2019 | 11:00 | Room 2104
University of Milano-Bicocca, Building U7, 2nd Floor
Via Bicocca Degli Arcimboldi 8, 20126 Milano


Abstract:
Multiple testing problems are a staple of modern statistics. The
fundamental objective is to reject as many false null hypotheses as
possible, subject to controlling an overall measure of false discovery,
like family-wise error rate (FWER) or false discovery rate (FDR). We
formulate multiple testing of simple hypotheses as an infinite-dimensional
optimization problem, seeking the most powerful rejection policy which
guarantees strong control of the selected measure. We show that for
exchangeable hypotheses, for FWER or FDR and relevant notions of power,
these problems lead to infinite programs that can provably be solved. We
explore maximin rules for complex alternatives, and show they can be found
in practice, leading to improved practical procedures compared to existing
alternatives. We derive explicit optimal tests for FWER or FDR control for
three independent normal means. We find that the power gain over natural
competitors is substantial in all settings examined. We apply our optimal
maximin rule to subgroup analyses in systematic reviews from the Cochrane
library, leading to an increased number of findings compared to existing
alternatives.

Manuscript: https://arxiv.org/pdf/1804.10256

(Joint work with Ruth Heller, Amichai Painsky and Udi Aharoni).


Speaker:
Saharon Rosset is Professor of Statistics at Tel Aviv University. His
research interests are in statistical learning theory and methodology, data
mining and statistical genetics. Prior to his tenure at Tel Aviv, he
received his PhD from Stanford University in 2003 under the supervision of
Professors Jerome Friedman and Trevor Hastie and spent four years as a
Research Staff Member at IBM Research in New York. His work has been
published in the most prestigious journals in the fields of statistics and
machine learning and he has an H-index over 40 on Google Scholar. He is a
five-time winner of major data mining competitions, including KDD Cup (four
times) and INFORMS Data Mining Challenge, and two time winner of the best
paper award at KDD.
https://m.tau.ac.il/~saharon

Best regards,
Aldo Solari
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