Gaussian Differential Privacy

7 May 2019Jinshuo DongAaron RothWeijie J. Su

Differential privacy has seen remarkable success as a rigorous and practical formalization of data privacy in the past decade. This privacy definition and its divergence based relaxations, however, have several acknowledged weaknesses, either in handling composition of private algorithms or in analyzing important primitives like privacy amplification by subsampling... (read more)

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