5 citations · 6 across the 3 of their papers we have counts for
5 papers
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…
Post-processing of Differentially Private Data: A Fairness Perspective
Keyu Zhu, Ferdinando Fioretto, Pascal Van Hentenryck
Post-processing immunity is a fundamental property of differential privacy: it enables arbitrary data-independent transformations to differentially private outputs without affectin…
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…
Optimal Pricing For MHR and -Regular Distributions
Yiannis Giannakopoulos, Diogo Poças, Keyu Zhu
We study the performance of anonymous posted-price selling mechanisms for a standard Bayesian auction setting, where bidders have i.i.d. valuations for a single item. We show t…