Bayesian Adversarial Privacy [v2]

We have just reposted our paper Bayesian Adversarial Privacy on arXiv to reflect the revision we wrote in the past months, to address the (quite sensible) comments from the reviewers. Interestingly the discussants of my Akaike lecture made similar points. The main changes are in explaining more clearly the nature of the combined loss, with Antoine coming up with the use of illuminating R-U map representations, in enlarging the references to other approaches, in stressing that Eve was an Alice’s construct rather than a genuine adversary, but still integrating the case of “multiple Eves”, in mellowing our criticisms of DP, and in expanding the conclusion with limitations and extensions subsections.
Related
This entry was posted on September 11, 2026 at 12:26 am and is filed under Books, Statistics, University life with tags #ERCSyG, Akaike Lecture, Alice and Bob, arXiv, Bayesian decision theory, contextual integrity, differential privacy, Durham, game theory, ICML 2026, Japan, lecture, Ocean, persuasive privacy, privacy, probabilistic differential privacy, R, R-U map, revision, risk ratio, slides, synthetic data, the Japanese Societies of Statistical Science Conference, U) map, Université Paris Dauphine. You can follow any responses to this entry through the RSS 2.0 feed. You can leave a response, or trackback from your own site.
Leave a Reply