Title: Learning Scheduling and Optimization in Federated Edge Learning
Time and Date: Tuesday, Nov. 14, 2023, 9:00AM US Eastern Time (New York Time)
Presenter: Dr. Yu Wang, Professor in the Department of Computer and Information Sciences, Temple University, Philadelphia, Pennsylvania 19122, USA
Venue: https://zoom.us/j/9172542706 (Password: 4Zn7xZ)
Abstract: Edge computing and federated learning (FL) have gained popularity since they provide a promising edge learning framework that mitigates the limitations of long latency, high cost, and privacy concerns in cloud-based centralized learning. While most existing works on federated edge learning focus on optimizing the training of the global model in edge systems, the concurrent training of multiple FL models from different applications in a shared edge cloud can lead to edge resource competition and affect the training performance of each model. Hence, in this talk, I will present our recent works in addressing this challenge by proposing optimization algorithms to jointly select FL participants and learning rates or topologies for each model, with an aim of minimizing the total training cost. Particularly, I will first introduce a multi-stage optimization framework that allows FL models to select their participants and learning rates or learning topologies. Then, I will describe a quantum assisted algorithm to tackle the joint participant selection and learning scheduling problem using both quantum and classical computing. Finally, I will summarize the talk with discussions about future directions in federated edge learning.
Bio: Dr. Yu Wang is currently a Professor in the Department of Computer and Information Sciences at Temple University. He holds a Ph.D. from Illinois Institute of Technology, an MEng and a BEng from Tsinghua University, all in Computer Science. His research interest includes wireless networks, smart sensing, and mobile computing. He has published over 200 papers in peer reviewed journals and conferences. He has served as general chair, program chair, program committee member, etc. for many international conferences (such as IEEE MASS, IEEE IPCCC, ACM MobiHoc, IEEE INFOCOM, IEEE GLOBECOM, IEEE ICC), and has served as Editorial Board Member for several international journals (including IEEE Transactions on Parallel and Distributed Systems and IEEE Transactions on Cloud Computing). He is a recipient of Ralph E. Powe Junior Faculty Enhancement Awards from Oak Ridge Associated Universities (2006), Outstanding Faculty Research Award from College of Computing and Informatics at the University of North Carolina at Charlotte (2008), Fellow of IEEE (2018), and ACM Distinguished Member (2020).