activity
20222024
most citedTowards Federated Learning against Noisy Labels via Local Self-Regularization

63 citations · 97 across the 6 of their papers we have counts for

collaborators
Showing cs.DCShow all

2 papers · 1 filter

cs.DC2023

FedBIAD: Communication-Efficient and Accuracy-Guaranteed Federated Learning with Bayesian Inference-Based Adaptive Dropout

Jingjing Xue, Min Liu, Sheng Sun +3

Federated Learning (FL) emerges as a distributed machine learning paradigm without end-user data transmission, effectively avoiding privacy leakage. Participating devices in FL are…

cs.DC2023★ 1 cited

FedTrip: A Resource-Efficient Federated Learning Method with Triplet Regularization

Xujing Li, Min Liu, Sheng Sun +3

In the federated learning scenario, geographically distributed clients collaboratively train a global model. Data heterogeneity among clients significantly results in inconsistent…