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Tao Zhang

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Preprint Aug 2026

FedGSA: Geometry-Consistent Subspace Aggregation for Differentially Private Federated LoRA

FedGSA, a geometry-consistent aggregation framework for differentially private federated LoRA, is proposed and it is proved that FedGSA incurs no additional privacy loss beyond client-side DP training and establishes its convergence under standard assumptions.

Lele Zheng, Rui Hu, Tao Zhang et al. · 0 citations

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