2 citations · 3 across the 4 of their papers we have counts for
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cs.CR2022
XMAM:X-raying Models with A Matrix to Reveal Backdoor Attacks for Federated Learning
Jianyi Zhang, Fangjiao Zhang, Qichao Jin +3
Federated Learning (FL) has received increasing attention due to its privacy protection capability. However, the base algorithm FedAvg is vulnerable when it suffers from so-called…
cs.CR2022★ 1 cited
Dap-FL: Federated Learning flourishes by adaptive tuning and secure aggregation
Qian Chen, Zilong Wang, Jiawei Chen +2
Federated learning (FL), an attractive and promising distributed machine learning paradigm, has sparked extensive interest in exploiting tremendous data stored on ubiquitous mobile…
cs.CR2022
CFL: Cluster Federated Learning in Large-scale Peer-to-Peer Networks
Qian Chen, Zilong Wang, Yilin Zhou +3
Federated learning (FL) has sparked extensive interest in exploiting the private data on clients' local devices. However, the parameter server setting of FL not only has high bandw…