most citedFLAIN: Mitigating Backdoor Attacks in Federated Learning via Flipping Weight Updates of Low-Activation Input Neurons

4 citations · 6 across the 3 of their papers we have counts for

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cs.LG2026

Federated Active Learning Under Extreme Non-IID and Global Class Imbalance

Chen-Chen Zong, Sheng-Jun Huang

Federated active learning (FAL) seeks to reduce annotation cost under privacy constraints, yet its effectiveness degrades in realistic settings with severe global class imbalance a…

cs.LG2024★ 4 cited

FLAIN: Mitigating Backdoor Attacks in Federated Learning via Flipping Weight Updates of Low-Activation Input Neurons

Binbin Ding, Penghui Yang, Sheng-Jun Huang

Federated learning (FL) enables multiple clients to collaboratively train machine learning models under the coordination of a central server, while maintaining privacy. However, th…