1 citations · 1 across the 9 of their papers we have counts for
Showing 2024Show all
3 papers · 1 filter
cs.LG2024
FedBaF: Federated Learning Aggregation Biased by a Foundation Model
Jong-Ik Park, Srinivasa Pranav, José M. F. Moura +1
Foundation models are now a major focus of leading technology organizations due to their ability to generalize across diverse tasks. Existing approaches for adapting foundation mod…
cs.LG2024
Federated Learning with Flexible Architectures
Jong-Ik Park, Carlee Joe-Wong
Traditional federated learning (FL) methods have limited support for clients with varying computational and communication abilities, leading to inefficiencies and potential inaccur…
cs.LG2024★ 1 cited
Fair Concurrent Training of Multiple Models in Federated Learning
Marie Siew, Haoran Zhang, Jong-Ik Park +6
Federated learning (FL) enables collaborative learning across multiple clients. In most FL work, all clients train a single learning task. However, the recent proliferation of FL a…