3 citations · 3 across the 2 of their papers we have counts for
3 papers
Unifying Re-Identification, Attribute Inference, and Data Reconstruction Risks in Differential Privacy
Bogdan Kulynych, Juan Felipe Gomez, Georgios Kaissis +4
Differentially private (DP) mechanisms are difficult to interpret and calibrate because existing methods for mapping standard privacy parameters to concrete privacy risks -- re-ide…
Optimizing Noise Distributions for Differential Privacy
Atefeh Gilani, Juan Felipe Gomez, Shahab Asoodeh +3
We propose a unified optimization framework for designing continuous and discrete noise distributions that ensure differential privacy (DP) by minimizing Rényi DP, a variant of DP,…
AI-Machine Learning-Enabled Tokamak Digital Twin
William Tang, Eliot Feibush, Ge Dong +9
In addressing the Department of Energy's April, 2022 announcement of a Bold Decadal Vision for delivering a Fusion Pilot Plant by 2035, associated software tools need to be develop…