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César Sabater

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#machine learning Preprint Jun 2026

Giskard : Byzantine Robust and Private Aggregation for Large-Scale Decentralized Learning

Giskard is presented, a scalable protocol for private and Byzantine-robust decentralized aggregation that reduces per-party communication complexity by close to three orders of magnitude over the closest competitor while exhibiting comparable robustness under up to $n/4 Byzantine parties.

Ousmane Touat, César Sabater, Mohamed Maouche et al. · 0 citations