[Statlist] FDS Seminar talk with Rina Foygel Barber - 27 May 2021, 16:00-17:00 CEST

[Maurer Letizia]

We are pleased to announce the following online talk in our ETH Foundations of Data Science Seminar series 

"Distribution-​free inference for regression: discrete, continuous, and in between“ 
by Rina Foygel Barber, The University of Chicago

Date and Time: Thursday, 20 May 2021, 16:00-17:00 CEST
Place: Zoom at https://www.airmeet.com/e/c4b11430-adb4-11eb-ab0c-3f3ae677ddc0

Abstract: "In data analysis problems where we are not able to rely on distributional assumptions, what types of inference guarantees can still be obtained? Many popular methods, such as holdout methods, cross-​validation methods, and conformal prediction, are able to provide distribution-​free guarantees for predictive inference, but the problem of providing inference for the underlying regression function (for example, inference on the conditional meanE[Y|X]) is more challenging. If X takes only a small number of possible values, then inference on E[Y|X] is trivial to achieve. At the other extreme, if the features X are continuously distributed, we show that any confidence interval for E[Y|X] must have non-​vanishing width, even as sample size tends to infinity - this is true regardless of smoothness properties or other desirable features of the underlying distribution. In between these two extremes, we find several distinct regimes - in particular, it is possible for distribution-​free confidence intervals to have vanishing width if and only if the effective support size of the distribution ofXis smaller than the square of the sample size. This work is joint with Yonghoon Lee. Bio: Rina Foygel Barber is a Louis Block Professor in the Department of Statistics at the University of Chicago. She was a NSF postdoctoral fellow during 2012-​13 in the Department of Statistics at Stanford University, supervised by Emmanuel Candès. She received her PhD in Statistics at the University of Chicago in 2012, advised by Mathias Drton and Nati Srebro, and a MS in Mathematics at the University of Chicago in 2009. Prior to graduate school, she was a mathematics teacher at the Park School of Baltimore from 2005 to 2007."

Organisers: A. Bandeira, H. Bölcskei, P. Bühlmann, J. Buhmann, N. He, T. Hofmann, A. Krause, R. Kyng, A. Lapidoth, H.-A. Loeliger, M. Maathuis, N. Meinshausen, S. Mishra, G. Rätsch, Ch. Schwab, D. Steurer, S. van de Geer, F. Yang, R. Zenklusen

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