TP3a.2

Over-the-Air Aggregation for Min-Max Multi-Model Federated Learning over Fading Channels

Chong Zhang, University of Toronto, Canada; Min Dong, Ontario Tech University, Canada; Ben Liang, University of Toronto, Canada; Ali Afana, Yahia Ahmed, Ericsson Canada, Canada
Session:
TP3a: Federated Learninng Lecture
Track:
Networks and Graphs
Location:
Scripps
Presentation Time:
Tue, 28 Oct, 13:55 - 14:20 PT (UTC -7)
Presentation
Discussion
Resources
No resources available.
Session TP3a
TP3a.1: LLM-enhanced Bayesian optimization for model partitioning in large-scale split federated learning
Haotian Xiang, University of Georgia, United States; Jun You, Jia Yan, HKUST (Guangzhou), China; Qin Lu, University of Georgia, United States
TP3a.2: Over-the-Air Aggregation for Min-Max Multi-Model Federated Learning over Fading Channels
Chong Zhang, University of Toronto, Canada; Min Dong, Ontario Tech University, Canada; Ben Liang, University of Toronto, Canada; Ali Afana, Yahia Ahmed, Ericsson Canada, Canada
TP3a.3: Coordinated Online Client Selection for Energy-Harvesting Over-the-Air Federated Learning
Jiayu Mao, Aylin Yener, The Ohio State University, United States
TP3a.4: Enhancing Efficiency and Privacy in Federated Learning via Partial Model Sharing
Dawit Kiros Redie, Stefan Werner, Norwegian University of Science and Technology, Norway; Reza Arablouei, CSIRO’s Data61, Australia
Contacts