Loss-based clustering of clients enables robust federated learning against strong Byzantine attacks with bounded optimality gaps using only the server and one honest client.
IEEE signal processing magazine37(3), 50–60 (2020)
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Robust Federated Learning under Adversarial Attacks via Loss-Based Client Clustering
Loss-based clustering of clients enables robust federated learning against strong Byzantine attacks with bounded optimality gaps using only the server and one honest client.