boolean functions 1correlated sources 1distributed hypothesis testing 1fisher information 1KL divergence 1
From the 1 of 2 linked papers with an AI index.
2 papers
cs.IT2026
On The Most Discriminative Boolean Functions for Correlated Sources
Jun Chen, Shun Watanabe, Lei Yu
The paper investigates which pairs of Boolean functions best separate two correlated binary sources by maximizing Kullback-Leibler divergence (and Fisher information), proving that…
cs.IT2026
UMVUE-Type Estimators under Bregman Losses
Akira Kamatsuka, Shun Watanabe
We study unbiased estimation under Bregman losses and develop an extension of the classical theory of uniformly minimum variance unbiased estimators (UMVUEs). Exploiting bias--vari…