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cs.LG2023
FedSSA: Semantic Similarity-based Aggregation for Efficient Model-Heterogeneous Personalized Federated Learning
Liping Yi, Han Yu, Zhuan Shi +4
Federated learning (FL) is a privacy-preserving collaboratively machine learning paradigm. Traditional FL requires all data owners (a.k.a. FL clients) to train the same local model…
cs.LG2023★ 4 cited
pFedLoRA: Model-Heterogeneous Personalized Federated Learning with LoRA Tuning
Liping Yi, Han Yu, Gang Wang +2
Federated learning (FL) is an emerging machine learning paradigm in which a central server coordinates multiple participants (clients) collaboratively to train on decentralized dat…