Game-theoretic Statistics and Sequential Anytime-Valid Inference
This is the supporting webpage for the tutorial at ICML on Jul 14, 2025 in Vancouver, Canada.
Location: TBD. Download Slides (check back the day of tutorial).
Sequential anytime-valid inference (SAVI) provides measures of statistical evidence and uncertainty --- e-values and e-processes for testing and confidence sequences for estimation --- that remain valid at all stopping times. These allow for continuous monitoring and analysis of accumulating data and optional stopping for any reason. These methods crucially rely on nonnegative martingales, which are wealth processes of a player in a betting game, thus yielding the area of "game-theoretic statistics". This tutorial will present the game-theoretic philosophy, intuition, language and mathematics behind SAVI, as summarized in a recent survey in Statistical Science and a new book, to appear as the first edition of Foundations and Trends in Statistics.
Objectives, outline and some key references will be placed on this page.