most citedDifferentially Private Generative Adversarial Networks for Time Series, Continuous, and Discrete Open Data

1 citations · 1 across the 2 of their papers we have counts for

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2 papers

cs.CR2023

A Cautionary Tale: On the Role of Reference Data in Empirical Privacy Defenses

Caelin G. Kaplan, Chuan Xu, Othmane Marfoq +2

Within the realm of privacy-preserving machine learning, empirical privacy defenses have been proposed as a solution to achieve satisfactory levels of training data privacy without…

cs.CR2019★ 1 cited

Differentially Private Generative Adversarial Networks for Time Series, Continuous, and Discrete Open Data

Lorenzo Frigerio, Anderson Santana de Oliveira, Laurent Gomez +1

Open data plays a fundamental role in the 21th century by stimulating economic growth and by enabling more transparent and inclusive societies. However, it is always difficult to c…