The paper proves sharp O(ε² log(1/ε)/log log(1/ε)) regret bounds for unregularized Bayes rules with compactly supported priors via polynomial approximation, improving on prior regularized results with extra log factors.
Compound decision theory and empirical
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Sharp regret-Hellinger bounds for Gaussian empirical Bayes via polynomial approximation
The paper proves sharp O(ε² log(1/ε)/log log(1/ε)) regret bounds for unregularized Bayes rules with compactly supported priors via polynomial approximation, improving on prior regularized results with extra log factors.