Entropic SMML defines a one-parameter family of coding rules that interpolates between Bayesian average-case and minimax worst-case codelengths, with a PAC-Bayes variational form and asymptotic regimes for regular parametric models.
Title resolution pending
2 Pith papers cite this work. Polarity classification is still indexing.
2
Pith papers citing it
fields
math.ST 2years
2026 2representative citing papers
citing papers explorer
-
Entropic Strict Minimum Message Length and Its Connections to PAC-Bayes and NML
Entropic SMML defines a one-parameter family of coding rules that interpolates between Bayesian average-case and minimax worst-case codelengths, with a PAC-Bayes variational form and asymptotic regimes for regular parametric models.
- Information Geometry and Asymptotic Theory for SMML Estimators