What Can Machine Learning Teach Us about Communications
Paper in proceedings, 2019
In this paper, we discuss the application of machine-learning techniques to two communications problems and focus on what can be learned from the resulting systems. We were pleasantly surprised that the observed gains in one example have a simple explanation that only became clear in hindsight. In essence, deep learning discovered a simple and effective strategy that had not been considered earlier.
Stochastic systems
Machine learning
Information theory
Deep learning
Author
Mengke Lian
Duke University
Christian Häger
Chalmers, Electrical Engineering, Communication and Antenna Systems, Communication Systems
Henry D. Pfister
Duke University
IEEE International Symposium on Information Theory - Proceedings
21578095 (ISSN)
Vol. 15 January 2019 8613331Guangzhou, China,
Coding for terabit-per-second fiber-optical communications (TERA)
European Commission (Horizon 2020), 2017-01-01 -- 2019-12-31.
Areas of Advance
Information and Communication Technology
Subject Categories
Telecommunications
Communication Systems
Information Science
Electrical Engineering, Electronic Engineering, Information Engineering
Signal Processing
Computer Science
DOI
10.1109/ITW.2018.8613331