DP-MacAdam combines adaptive clipping and Adam-style momentum in DP-SGD by sharing bias-free empirical gradient statistics, achieving higher utility than DP-SGD, AdaClip, and DP-Adam without manual clipping threshold tuning.
DP-AdamW: Investigating De- coupled Weight Decay and Bias Correction in Private Deep Learning,
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DP-MacAdam: Differentially Private Mechanism with Adaptive Clipping and Adaptive Momentum
DP-MacAdam combines adaptive clipping and Adam-style momentum in DP-SGD by sharing bias-free empirical gradient statistics, achieving higher utility than DP-SGD, AdaClip, and DP-Adam without manual clipping threshold tuning.