[New blog post!] A gentle, (mostly) non-technical introduction to game-theoretic statistics, e-values, and my recent paper with Aaditya Ramdas on combining evidence across asymmetric information sets. Originally posted in the UChicago Data Science Institute Blog.
We develop anytime-valid inference methods for estimating & testing the time-varying mean score difference between two sequential forecasters. Published in Operations Research.
We develop a statistical inference approach for counterfactually evaluating and comparing abstaining classifiers using nonparametric causal inference. Published in NeurIPS.
We address an intriguing challenge for anytime-valid sequential inference that arises when combining evidence processes constructed using different information sets. Under review.