Programme

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

  • Keynote speakers: 1 hour talk + 15 minutes for questions
  • Invited speakers: 50 minutes talk + 10 minutes for questions

Monday 12 July 2021

  • 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 Emmanuel Candès

Tuesday 13 July 2021

  • 10:00-11:15 Randomized Concentration Inequalities with Applications, Qi-Man Shao, University of Honk-Kong
  • 11:15-12:30 Statistical analysis of machine learning methods Johannes Schmidt-Hieber, University of Twente
  • Lunch break
  • 16:30-17:30 Inference for High-dimensional Maximin Effects in Heterogeneous Regression Models Using a Sampling Approach, Zijian Guo, Rutgers University
  • 17:30-18:30 A universal law of robustness via isoperimetry, Sébastien Bubeck, Microsoft Research

Wednesday 14 July 2021

  • 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

  • 10:00-11:15 Novel approaches for network data modelling and analysis, Sofia Ohlede, EPFL
  • 11:15-12:30 Nanostatistics, Axel Munk, Georg-August-Universität Göttingen
  • Lunch Break
  • 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

  • 14:00-15:15 On Information theoretic limitations for inference in some statistical inverse problems arising with PDEs’, Richard Nickl, University of Cambridge
  • 15:15-16:30 Machine Learning and Inverse Problems: Convergence and Adaptation, Rebecca Willett, University of Chicago
  • Break
  • 17:00-18:15 A modern take on Huber regression, Po-Ling Loh, University of Wisconsin – Madison