60 citations · 115 across the 7 of their papers we have counts for
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cs.LG2023
Learning Cautiously in Federated Learning with Noisy and Heterogeneous Clients
Chenrui Wu, Zexi Li, Fangxin Wang +1
Federated learning (FL) is a distributed framework for collaboratively training with privacy guarantees. In real-world scenarios, clients may have Non-IID data (local class imbalan…
cs.LG2023★ 6 cited
Learning to Backdoor Federated Learning
Henger Li, Chen Wu, Sencun Zhu +1
In a federated learning (FL) system, malicious participants can easily embed backdoors into the aggregated model while maintaining the model's performance on the main task. To this…