Programme

The programme of the International Conference on Statistics and Related Fields (ICON STARF) is the following:

Monday 12 July 2021

Moderator: Yannick Baraud

14:00-14:30 Welcome speech, Yannick Baraud, University of Luxembourg
14:30-15:45 Estimation of smooth functionals of high-dimensional parameters: bias reduction and efficiency, Vladimir Koltchinskii, School of Mathematics, Georgia Institute of Technology
15:45-17:00 Thoughts on Deep Learning, Ronald DeVore, Texas A&M University
Break
17:30-18:45 Novel approaches for network data modelling and analysis, Sofia Olhede, EPFL

Tuesday 13 July 2021

Moderator: Giovanni Peccati

10:00-11:15 Randomized Concentration Inequalities with Applications, Qi-Man Shao, Southern University of Science and Technology
11:15-12:30 Statistical analysis of machine learning methods Johannes Schmidt-Hieber, University of Twente
Lunch break

Moderator: Hélène Halconruy

16:30-17:30 A universal law of robustness via isoperimetry, Sébastien Bubeck, Microsoft Research
17:30-18:30 Inference for High-dimensional Maximin Effects in Heterogeneous Regression Models Using a Sampling Approach, Zijian Guo, Rutgers University

Wednesday 14 July 2021

Moderator: Guillaume Maillard

10:30-11:30 Precise analysis of some Purely Random Forests, Sylvain Arlot, Université Paris-Saclay
11:30-12:30 Optimal change-point detection and localization, Nicolas Verzelen, INRA
Lunch Break
15:00-16:00 Distribution-Free Robust Linear Regression, Nikita Zhivotovskiy, ETH Zürich
16:00-17:00 Uncertainty quantification for penalized M-estimators in high-dimensions, Pierre Bellec, Rutgers University
Break
17:30-18:30 Tensor models for high dimensional data with complex dependencies, Shuheng Zhou, University of California

Thursday 15 July 2021

Moderator: Hélène Halconruy

Moderator: Christophe Ley

16:30-17:30 Estimating means of bounded random variables by betting, Aaditya Ramdas, Carnegie Mellon University
17:30-18:30 Asymptotic properties of robust mean estimators, Stanislav Minsker, University of South California

Friday 16 July 2021

Moderator: Mark Podolskij

14:00-15:15 Bayesian non-linear inverse problems and PDEs, Richard Nickl, University of Cambridge
15:15-16:30 Machine Learning and Inverse Problems: Convergence and Adaptation, Rebecca Willett, University of Chicago
Break

Moderator: Yannick Baraud

17:00-18:15 A modern take on Huber regression, Po-Ling Loh, University of Cambridge