SDS Seminar Series – Aaditya Ramdas, Carnegie Mellon University

The Fall 2024 SDS Seminar Series continues on November 1st from 2:00 p.m. to 3:00 p.m. with Dr. Aaditya Ramdas (Associate Professor, Department of Statistics and Data Science, Carnegie Mellon University). This event is in-person in the Avaya Room (POB 2.302).    

Title: A Game-Theoretic Theory of Statistical Evidence

Abstract: This talk will describe an approach towards testing hypotheses and estimating functionals that is based on games. In short, to test a (possibly composite, nonparametric) hypothesis, we set up a game in which no betting strategy can make money under the null (the wealth is an "e-process" under the null). But if the null is false, then smart betting strategies will have exponentially increasing wealth. Thus, hypotheses are rewritten as constraints in games, the statistician is a gambler, test statistics are betting strategies, and the wealth obtained is directly a measure of evidence which is valid at any data-dependent stopping time (an e-value). The optimal betting strategies are typically Bayesian, but the guarantees are frequentist. This "game perspective" provides new statistically and computationally efficient solutions to many modern problems.