Date：2024/01/18 (四)  10:30~12:00

Venue：電資大樓 工EC2002

Topic： A Look at Federated Learning from Different Perspectives

Professor Tony Q.S. Quek visited the 6G Communications and Sensing Research Center to give a talk entitled "A Look at Federated Learning from Different Perspectives".

Prof. Quek discussed the importance and applications of Federated Learning in the field of wireless communications. He began by describing how machine learning has shown high performance in handling complex computations and models, with a special emphasis on the decentralized learning paradigm - the federated learning infrastructure, model training algorithms, and analytical frameworks for quantifying the rate of convergence. Prof. Quek explored federal learning from different perspectives, including wireless federal learning, over-the-air federal learning, data heterogeneity, and learning efficiency, and shared some of the most recent research results in this area, providing multiple innovative perspectives to understand federal learning and address its inherent challenges.

The talk provided participants with an in-depth understanding of the multiple facets of federal learning, which is an important inspiration not only for academic researchers, but also for real-world industrial applications.