45 citations · 80 across the 9 of their papers we have counts for
4 papers · 1 filter
Fairness Increases Adversarial Vulnerability
Cuong Tran, Keyu Zhu, Ferdinando Fioretto +1
The remarkable performance of deep learning models and their applications in consequential domains (e.g., facial recognition) introduces important challenges at the intersection of…
SF-PATE: Scalable, Fair, and Private Aggregation of Teacher Ensembles
Cuong Tran, Keyu Zhu, Ferdinando Fioretto +1
A critical concern in data-driven processes is to build models whose outcomes do not discriminate against some demographic groups, including gender, ethnicity, or age. To ensure no…
Differential Privacy and Fairness in Decisions and Learning Tasks: A Survey
Ferdinando Fioretto, Cuong Tran, Pascal Van Hentenryck +1
This paper surveys recent work in the intersection of differential privacy (DP) and fairness. It reviews the conditions under which privacy and fairness may have aligned or contras…
Bias and Variance of Post-processing in Differential Privacy
Keyu Zhu, Pascal Van Hentenryck, Ferdinando Fioretto
Post-processing immunity is a fundamental property of differential privacy: it enables the application of arbitrary data-independent transformations to the results of differentiall…