Due to its communication efficiency and privacy-preserving capability, federated learning has emerged as a promising framework for machine learning in 5G-and-beyond wireless networks. Therefore, the novel designs of wireless networks to support the stable and fast operation of federated learning are of great interest. This talk will first highlight the reasons why federated learning becomes important in the future, briefly introduce communication- oriented research directions for realizing federated learning in wireless networks and then discuss state-of-the-art solutions for a massive multiple-input multiple-output (MIMO) network to efficiently support federated learning.
Speaker: Dr. Nguyen Chi Thanh, AMST, Hanoi
Time: 15:30, Tuesday, April 19, 2022
Venue: Webinar
NGUYEN CHI THANH received the Ph.D. degree in computer science from the Nagaoka University of Technology, Japan, in 2012. He is currently a Researcher with the Institute of Information Technology, AMST, Hanoi, Vietnam. His research interests include deep learning, computer vision, medical image analysis, and natural language processing.