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CARVY-FL: Client Anticlustering for Robust Voting in Provably Secure Federated Learning
Federated learning (FL) enables collaborative training without directly sharing raw data, but remains vulnerable to malicious clients. Voting-based FL improves robustness by partitioning clients into groups, training one model per group, and aggregating predictions by plurality voting. However, unde
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