We show how to achieve differential privacy with no or reduced added noise, based on the empirical noise in the data itself. Unlike previous works on noiseless privacy, the empirical viewpoint avoids making any explicit assumptions about the random process generating the data.

翻译：根据数据本身的实证噪音,我们展示了如何在不增加或减少噪音的情况下实现差异隐私。 与以往关于无噪音隐私的工作不同,经验观点避免了对生成数据的随机过程做出任何明确假设。