[Statlist] ETH Young Data Science Researcher Seminar Zurich, Virtual Seminar by Tomas Vaškevičius, University of Oxford

[Maurer Letizia]

We are glad to announce the following talk in the virtual ETH Young Data Science Researcher Seminar Zurich

"Exponential-tail excess risk bounds without Bernstein condition “  
by Tomas Vaškevičius, University of Oxford

Time: Thursday, 10 March 2022, 15.00 - 16.00
Place: Zoom at https://ethz.zoom.us/j/62895316484


if you like to join, we meet at ETH Zürich, HG G 19.2, to watch the zoom together 


Abstract: The local Rademacher complexity framework is one of the most successful toolboxes for establishing sharp excess risk bounds for statistical estimators based on empirical risk minimization. However, the applicability of this toolbox hinges on the so-​called Bernstein condition, often limiting direct application domains to proper and convex problem settings. In this talk, we will show how to obtain exponential-​tail local Rademacher complexity excess risk bounds under an alternative condition. This alternative condition, leading to a more recent notion of localization via offset Rademacher complexities, is known to hold for some estimators in non-​convex and improper settings. We will discuss applications of this theory to model selection aggregation and iterative regularization problems.

M. Azadkia, G. Chinot, J. Hörrmann, M. Löffler, A. Taeb, N. Zhivotovskiy


Please take note of the Covid certificate and mask requirements for joining this lecture. Further details can be found here, https://ethz.ch/services/en/news-and-events/coronavirus.html

Seminar website: https://math.ethz.ch/sfs/news-and-events/young-data-science.html

Young Data Science Researcher Seminar Zurich – Seminar for Statistics | ETH Zurich
math.ethz.ch