Not All Noise is Accounted Equally: How Differentially Private Learning Benefits from Large Sampling Rates

Friedrich Dörmann, Osvald Frisk, Lars Nørvang Andersen, Christian Fischer Pedersen. Not All Noise is Accounted Equally: How Differentially Private Learning Benefits from Large Sampling Rates. In 31st IEEE International Workshop on Machine Learning for Signal Processing, MLSP 2021, Gold Coast, Australia, October 25-28, 2021. pages 1-6, IEEE, 2021. [doi]

Abstract

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