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cs.CR2023★ 1 cited
Geometry of Sensitivity: Twice Sampling and Hybrid Clipping in Differential Privacy with Optimal Gaussian Noise and Application to Deep Learning
Hanshen Xiao, Jun Wan, Srinivas Devadas
We study the fundamental problem of the construction of optimal randomization in Differential Privacy. Depending on the clipping strategy or additional properties of the processing…
cs.CR2022
PAC Privacy: Automatic Privacy Measurement and Control of Data Processing
Hanshen Xiao, Srinivas Devadas
We propose and study a new privacy definition, termed Probably Approximately Correct (PAC) Privacy. PAC Privacy characterizes the information-theoretic hardness to recover sensitiv…