most citedFedCompass: Efficient Cross-Silo Federated Learning on Heterogeneous Client Devices using a Computing Power Aware Scheduler

2 citations · 2 across the 1 of their papers we have counts for

collaborators

1 paper

cs.LG2023★ 2 cited

FedCompass: Efficient Cross-Silo Federated Learning on Heterogeneous Client Devices using a Computing Power Aware Scheduler

Zilinghan Li, Pranshu Chaturvedi, Shilan He +6

Cross-silo federated learning offers a promising solution to collaboratively train robust and generalized AI models without compromising the privacy of local datasets, e.g., health…