pith:6YRNMN2E
Entropic Strict Minimum Message Length and Its Connections to PAC-Bayes and NML
Entropic SMML generalizes strict minimum message length into a tunable family that interpolates between Bayesian and minimax coding.
arxiv:2605.02099 v2 · 2026-05-03 · math.ST · stat.TH
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Claims
We show that entropic SMML admits a variational characterization as a Kullback--Leibler-regularized worst-case expected codelength, giving it a PAC--Bayes-type interpretation. We establish a joint asymptotic theory linking the sample size n and the risk parameter τ, showing that in regular parametric models the transition between Bayesian, robust, and minimax coding regimes occurs on a logarithmic scale.
The joint asymptotic theory and the affine partition property hold only under the assumption of regular parametric models and regular exponential families; the paper does not specify how the results degrade when these regularity conditions are violated.
Entropic SMML defines a risk-sensitive family of coding rules bridging Bayesian MML, PAC-Bayes, and NML minimax-regret via exponential certainty equivalents and tilted centroids in exponential families.
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| First computed | 2026-05-20T01:05:15.187082Z |
|---|---|
| Builder | pith-number-builder-2026-05-17-v1 |
| Signature | Pith Ed25519
(pith-v1-2026-05) · public key |
| Schema | pith-number/v1.0 |
Canonical hash
f622d63744648b0c029c7abbe190bd3509cdcb552d119461be6200bd923aa7ef
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Canonical record JSON
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