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