Professor Lei Yu from Nankai University was invited to give an online academic report on the subject of "Common Information Distributed Channel Synthesis and the Reverse Shannon Theorem" in the afternoon of October 14th, 2022. The report was hosted by Lin Zhou, a professor from the School of Cyber Science and Technology of Beihang University. More than 20 professors and students participated in the report online.
In the report, Prof. Yu first introduced how to measure the amount of information between two random variables, pointed out that the representation of correlation coefficient and mutual information in traditional statistical methods did not give an operational explanation, and then introduced the concepts of Wyner common information and exact common information, and introduced the proof of related theorems. Next, Prof. Yu compared the relationship between perceptual coding and channel synthesis problems, and pointed out that the latter two problems can be equated to the analysis of perceptual coding under certain circumstances. As for the channel synthesis problem, its essence is the inverse problem of Shannon's channel coding theorem. Furthermore, Prof. Yu introduced his research ideas and results on the exact channel synthesis problem. For perceptual coding problem, the essence is to increase the constraints on TV distance in source coding problem, but the constraints are weaker than those of channel synthesis problem.
At the end of the lecture, Prof. Yu answered the questions raised by the professors and students, and conducted in-depth communication and discussion with the professors and students on perceptual coding and other issues.
【Brief Introduction of the Speaker】
Dr. Yu was selected into the "100 Young Discipline Leaders Training Program" of Nankai University in 2021. He is currently an associate professor and doctoral supervisor at the School of Statistics and Data Science of Nankai University. He graduated from the University of Science and Technology of China (USTC) with a PhD in electronic information engineering in 2015. After that, he did post-doctoral research at the University of Science and Technology of China (USTC), the National University of Singapore (NUS) and the University of California, Berkeley. Dr. Yu's current research interests include information theory, probability theory, combinatorics, etc. His research topics include measurement concentration, isoperimetric problems, functional inequalities and other theoretical studies. At present, he has solved or partially solved several related public problems and conjectures.
