20 citations · 48 across the 19 of their papers we have counts for
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cs.LG2024
FedBRB: An Effective Solution to the Small-to-Large Scenario in Device-Heterogeneity Federated Learning
Ziyue Xu, Mingfeng Xu, Tianchi Liao +2
Recently, the success of large models has demonstrated the importance of scaling up model size. This has spurred interest in exploring collaborative training of large-scale models…
cs.LG2024★ 3 cited
Clients Collaborate: Flexible Differentially Private Federated Learning with Guaranteed Improvement of Utility-Privacy Trade-off
Yuecheng Li, Lele Fu, Tong Wang +6
To defend against privacy leakage of user data, differential privacy is widely used in federated learning, but it is not free. The addition of noise randomly disrupts the semantic…