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.
In: 2021 IEEE 27th International Conference on Parallel and Distributed Systems (ICPADS)
1 Pith paper cite this work. Polarity classification is still indexing.
1
Pith paper citing it
fields
cs.LG 1years
2025 1verdicts
UNVERDICTED 1representative citing papers
citing papers explorer
-
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.