A theoretical and empirical study finds that unbiased second-moment estimates in private Adam can be harmful in high dimensions, and that scale-then-privatize outperforms the alternatives on a small transformer task.
Private empirical risk minimization: Efficient algorithms and tight error bounds
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On Design Principles for Private Adaptive Optimizers
A theoretical and empirical study finds that unbiased second-moment estimates in private Adam can be harmful in high dimensions, and that scale-then-privatize outperforms the alternatives on a small transformer task.