11 citations · 12 across the 7 of their papers we have counts for
4 papers · 1 filter
Minimum Entropy Coupling with Bottleneck
M. Reza Ebrahimi, Jun Chen, Ashish Khisti
This paper investigates a novel lossy compression framework operating under logarithmic loss, designed to handle situations where the reconstruction distribution diverges from the…
Information Compression in the AI Era: Recent Advances and Future Challenges
Jun Chen, Yong Fang, Ashish Khisti +3
This survey articles focuses on emerging connections between the fields of machine learning and data compression. While fundamental limits of classical (lossy) data compression are…
Rate-Distortion-Perception Tradeoff for Gaussian Vector Sources
Jingjing Qian, Sadaf Salehkalaibar, Jun Chen +5
This paper studies the rate-distortion-perception (RDP) tradeoff for a Gaussian vector source coding problem where the goal is to compress the multi-component source subject to dis…
Rate-Distortion-Perception Tradeoff Based on the Conditional-Distribution Perception Measure
Sadaf Salehkalaibar, Jun Chen, Ashish Khisti +1
This paper studies the rate-distortion-perception (RDP) tradeoff for a memoryless source model in the asymptotic limit of large block-lengths. The perception measure is based on a…