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cs.LG2024
FedSAC: Dynamic Submodel Allocation for Collaborative Fairness in Federated Learning
Zihui Wang, Zheng Wang, Lingjuan Lyu +6
Collaborative fairness stands as an essential element in federated learning to encourage client participation by equitably distributing rewards based on individual contributions. E…
cs.LG2024
FedPFT: Federated Proxy Fine-Tuning of Foundation Models
Zhaopeng Peng, Xiaoliang Fan, Yufan Chen +5
Adapting Foundation Models (FMs) for downstream tasks through Federated Learning (FL) emerges a promising strategy for protecting data privacy and valuable FMs. Existing methods fi…