63 citations · 65 across the 7 of their papers we have counts for
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cs.CR2021
Smoothed Differential Privacy
Ao Liu, Yu-Xiang Wang, Lirong Xia
Differential privacy (DP) is a widely-accepted and widely-applied notion of privacy based on worst-case analysis. Often, DP classifies most mechanisms without additive noise as non…
cs.CR2019★ 63 cited
Differential Privacy for Eye-Tracking Data
Ao Liu, Lirong Xia, Andrew Duchowski +3
As large eye-tracking datasets are created, data privacy is a pressing concern for the eye-tracking community. De-identifying data does not guarantee privacy because multiple datas…
cs.CR2018
How Private Are Commonly-Used Voting Rules?
Ao Liu, Yun Lu, Lirong Xia +1
Differential privacy has been widely applied to provide privacy guarantees by adding random noise to the function output. However, it inevitably fails in many high-stakes voting sc…