Title: Federated Learning in Unreliable and Resource-Constrained Cellular Wireless Networks
Date: May 26, 2021; Time: 11AM EDT
Registration: Please register at https://albany.zoom.us/meeting/register/tJYvd-irrDMuH9ImDFQ65_9LugOGR4J-fEBg
Abstract: Federated learning is a machine learning setting where the centralized location trains a learning model by using remote devices. Federated learning algorithms cannot be employed in wireless networks unless the unreliable and resource-constrained nature of the wireless medium is taken into account. In this talk, I shall present a federated learning algorithm that is suitable for cellular wireless networks in a real-world scenario. I shall discuss its convergence properties, and the effects of local computation steps and communication steps on its convergence. Through experiments on real and synthetic datasets, I shall demonstrate the convergence of the proposed algorithm.
Bio: Ekram Hossain (IEEE Fellow) is a Professor in the Department of Electrical and Computer Engineering at University of Manitoba, Winnipeg, Canada. He is a Member (Class of 2016) of the College of the Royal Society of Canada, a Fellow of the Canadian Academy of Engineering, and also a Fellow of the Engineering Institute of Canada (http://home.cc.umanitoba.ca/~hossaina). He received his Ph.D. in Electrical Engineering from University of Victoria, Canada, in 2001. Dr. Hossain’s current research interests include design, analysis, and optimization of wireless communication networks (with emphasis on beyond 5G/6G cellular), applied machine learning and game theory, and network economics. He was elevated to an IEEE Fellow “for contributions to spectrum management and resource allocation in cognitive and cellular radio networks”. He was listed as a Clarivate Analytics Highly Cited Researcher in Computer Science in 2017, 2018, 2019, and 2020. Dr. Hossain has won several research awards including the “2017 IEEE Communications Society Best Survey Paper Award, the 2011 IEEE Communications Society Fred Ellersick Prize Paper Award, University of Manitoba Merit Award in 2010, 2013, 2014, and 2015 (for Research and Scholarly Activities), and the IEEE Wireless Communications and Networking Conference 2012 (WCNC’12) Best Paper Award. He received the 2017 IEEE ComSoc TCGCC (Technical Committee on Green Communications & Computing) Distinguished Technical Achievement Recognition Award “for outstanding technical leadership and achievement in green wireless communications and networking”. Currently he serves as the Editor-in-Chief of the IEEE Press and an Editor for IEEE Transactions on Mobile Computing. Previously, he served as an Area Editor for the IEEE Transactions on Wireless Communications in the area of “Resource Management and Multiple Access” (2009-2011) and an Editor for the IEEE Journal on Selected Areas in Communications – Cognitive Radio Series (2011-2014). He serves as the Director of Magazines for the IEEE Communications Society (2020-2021). Dr. Hossain was an elected Member of the Board of Governors of the IEEE Communications Society for the term 2018-2020. He is a Distinguished Lecturer of the IEEE Communications Society. He is a registered Professional Engineer in the province of Manitoba, Canada.
About the Monthly Virtual Seminar Series: The IEEE TCCN Special Interest Group for AI and Machine Learning in Security conducts a monthly virtual seminar series to highlight the challenges in securing the next generation (xG) wireless networks. The talks will feature cutting edge research addressing both technical and policy issues to advance the state-of-the-art in security techniques, architectures, and algorithms for wireless communications.