5 papers
On The Most Discriminative Boolean Functions for Correlated Sources
Jun Chen, Shun Watanabe, Lei Yu
Motivated by a conjecture of Amari and Kobayashi, we study the problem of identifying pairs of Boolean functions that maximize the Kullback-Leibler divergence between two distribut…
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…
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…
Gaussian Rate-Distortion-Perception Coding and Entropy-Constrained Scalar Quantization
Li Xie, Liangyan Li, Jun Chen +2
This paper investigates the best known bounds on the quadratic Gaussian distortion-rate-perception function with limited common randomness for the Kullback-Leibler divergence-based…
On the Message Passing Efficiency of Polar and Low-Density Parity-Check Decoders
Dawei Yin, Yuan Li, Xianbin Wang +8
This study focuses on the efficiency of message-passing-based decoding algorithms for polar and low-density parity-check (LDPC) codes. Both successive cancellation (SC) and belief…