Aurelien Lucchi
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126
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ML×1Crypto×1Optimization and Control×1
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2026
Byzantine-Robust and Differentially Private Federated Optimization under Weaker Assumptions
The paper proposes Byz-Clip21-SGD2M, a novel algorithm that achieves high-probability convergence guarantees for Federated Learning by integrating robust aggregation, double momentum, and clipping, relaxing restrictive assumptions found in prior work.
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