AI RESEARCH
Bayes with No Shame: Admissibility Geometries of Predictive Inference
arXiv CS.LG
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ArXi:2603.05335v2 Announce Type: replace-cross Four distinct admissibility geometries govern sequential and distribution-free inference: Blackwell risk dominance over convex risk sets, anytime-valid admissibility within the nonnegative supermartingale cone, marginal coverage validity over exchangeable prediction sets, and Ces\`aro approachability (CAA) admissibility, which reaches the risk-set boundary via approachability-style arguments rather than explicit priors. We prove a criterion separation theorem: the four classes of admissible procedures are pairwise non-nested.