Decentralized Federated Learning: Enabling Collaborative AI With Enhanced Trust and Efficiency

Tutorial session related to Federated Learning at ECAI 2023

Link Details and Content

Alberto Huertas¹, Enrique Tomás Martínez², Pedro M. Sánchez², Gérôme Bovet³, Gregorio Martínez², Burkhard Stiller¹

¹ Communication Systems Group CSG, Department of Informatics IfI, University of Zurich UZH, Switzerland ² Department of Information and Communications Engineering, University of Murcia, Spain ³ Cyber-Defence Campus within armasuisse Science & Technology, Thun, Switzerland

This tutorial presents a rigorous examination of Decentralized Federated Learning (DFL), an emergent field that fortifies the intersection of collaboration, efficiency, and privacy in artificial intelligence systems. The tutorial systematically explores the underlying principles, architectures, components, security strategies, and optimization techniques inherent to DFL. Moreover, participants will have the opportunity to gain hands-on experience with Fedstellar, a platform for training DFL models, and delve into real-world use cases, effectively marrying theory with practice. Attendees will gain an understanding of practical applications, as well as a vision of future trends, encapsulating the transformative potential of DFL in the realm of Artificial Intelligence (AI) and associated domains.