### 10th World Congress in Probability and Statistics

## Plenary Lectures

## IMS Medallion Lecture (Daniela Witten)

### Selective inference for trees

Daniela Witten (University of Washington)

###### Session Chair

Ja-Yong Koo (Korea University)

## IMS Medallion Lecture (Andrea Montanari)

### High-dimensional interpolators: From linear regression to neural tangent models

Andrea Montanari (Stanford University)

[Based on joint papers with: Michael Celentano, Behrooz Ghorbani, Song Mei, Theodor Misiakiewicz, Feng Ruan, Youngtak Sohn, Jun Yan, Yiqiao Zhong]

###### Session Chair

Myunghee Cho Paik (Seoul National University)

## Blackwell Lecture (Gabor Lugosi)

### Estimating the mean of a random vector

Gabor Lugosi (ICREA & Pompeu Fabra Universit)

###### Session Chair

Byeong Uk Park (Seoul National University)

## Tukey Lecture (Sara van de Geer)

### Max-margin classification and other interpolation methods

Sara van de Geer (Swiss Federal Institute of Technology Zürich)

This is joint work with Geoffrey Chinot, Felix Kuchelmeister and Matthias Löffler.

References

T. Liang and P. Sur. A precise high-dimensional asymptotic theory for boosting and minimum-$\ell_1$-norm interpolated classifiers, 2020. arXiv:2002.01586.

Y. Plan and R. Vershynin. One-bit compressed sensing by linear programming. Communications on Pure and Applied Mathematics, 66(8):1275–1297, 2013.

J. Tukey. Analyzing data: Sanctification or detective work? American Psychologist, 24:83–91, 1969.

P. Wojtaszczyk. Stability and instance optimality for gaussian measurements in compressed sensing. Foundations of Computational Mathematics, 10(1): 1–13, 2010.

###### Session Chair

Adam Jakubowski (Nicolaus Copernicus University)