A sketched Gaussian mechanism is shown to have privacy loss that shrinks as the sketch dimension grows, giving communication-efficient federated learning with stronger privacy per noise budget.
An elementary proof of a theorem of Johnson and Linden- strauss.Random Structures & Algorithms, 22(1):60–65, 2003
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Sketched Gaussian Mechanism for Private Federated Learning
A sketched Gaussian mechanism is shown to have privacy loss that shrinks as the sketch dimension grows, giving communication-efficient federated learning with stronger privacy per noise budget.