AI & ML
The Critical Renyi Order for Sharp Minimax Channel Design
arXiv math.IT0 views
arXiv:2603.21197v2 Announce Type: replace Abstract: We study categorical channel design under a bound on the maximum directed pairwise Renyi divergence. We determine exactly which orders make randomized response optimal in every dimension and at every finite budget: the orders strictly above one and at most two. In that range we identify the full information-trace frontier and its unique optimal anchored law. The channel is visibly thinned randomized response below a uniquely defined threshold and ordinary randomized response above it. A fixed-second-moment inequality and a second-order variational argument reduce arbitrary channel columns to singleton templates. Above order two, an explicit subset-selection channel beats every mixture of singleton templates in a finite dimension. The trace frontier also gives the exact finite-sample minimax risk among all unbiased real-valued vector estimators, and the asymptotic minimax risk among all estimators for every budget sequence with diverging total information. Appendices compare pure local privacy and distinguish homogeneous shuffle contamination from arbitrary neighboring datasets.
Source:https://arxiv.org/abs/2603.21197PreviousZero-knowledge and Quantum CSS Codes Are EquivalentNextHierarchical Joint Source-Channel Coding with Constrained Information Leakage
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