boolean functions 1correlated sources 1distributed hypothesis testing 1fisher information 1KL divergence 1
From the 1 of 3 linked papers with an AI index.
3 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.IT2025
On the Fundamental Limits of Integrated Sensing and Communications Under Logarithmic Loss
Jun Chen, Lei Yu, Yonglong Li +3
We study a unified information-theoretic framework for integrated sensing and communications (ISAC), applicable to both monostatic and bistatic sensing scenarios. Special attention…
cs.IT2024
Channel-Aware Optimal Transport: A Theoretical Framework for Generative Communication
Xiqiang Qu, Ruibin Li, Jun Chen +2
Optimal transport has numerous applications, particularly in machine learning tasks involving generative models. In practice, the transportation process often encounters an informa…