47 citations · 71 across the 4 of their papers we have counts for
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cs.CR2020★ 47 cited
Privacy and Robustness in Federated Learning: Attacks and Defenses
Lingjuan Lyu, Han Yu, Xingjun Ma +5
As data are increasingly being stored in different silos and societies becoming more aware of data privacy issues, the traditional centralized training of artificial intelligence (…
cs.LG2020★ 18 cited
Robust Federated Recommendation System
Chen Chen, Jingfeng Zhang, Anthony K. H. Tung +2
Federated recommendation systems can provide good performance without collecting users' private data, making them attractive. However, they are susceptible to low-cost poisoning at…