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cs.LG2024
Mjolnir: Breaking the Shield of Perturbation-Protected Gradients via Adaptive Diffusion
Xuan Liu, Siqi Cai, Qihua Zhou +3
Perturbation-based mechanisms, such as differential privacy, mitigate gradient leakage attacks by introducing noise into the gradients, thereby preventing attackers from reconstruc…
cs.LG2022★ 1 cited
Feature Correlation-guided Knowledge Transfer for Federated Self-supervised Learning
Yi Liu, Song Guo, Jie Zhang +3
To eliminate the requirement of fully-labeled data for supervised model training in traditional Federated Learning (FL), extensive attention has been paid to the application of Sel…