143 citations · 149 across the 5 of their papers we have counts for
5 papers
SAFES: Sequential Privacy and Fairness Enhancing Data Synthesis for Responsible AI
Spencer Giddens, Xiaon Lang, Fang Liu
As data-driven and AI-based decision making gains widespread adoption across disciplines, it is crucial that both data privacy and decision fairness are appropriately addressed. Al…
Enhancing Trade-offs in Privacy, Utility, and Computational Efficiency through MUltistage Sampling Technique (MUST)
Xingyuan Zhao, Ruyu Zhou, Fang Liu
Applying a randomized algorithm to a subset rather than the entire dataset amplifies privacy guarantees. We propose a class of subsampling methods ``MUltistage Sampling Technique (…
Sentiment Analysis and Effect of COVID-19 Pandemic using College SubReddit Data
Tian Yan, Fang Liu
Background: The COVID-19 pandemic has affected our society and human well-being in various ways. In this study, we investigate how the pandemic has influenced people's emotions and…
Assessment of Bayesian Expected Power via Bayesian Bootstrap
Fang Liu
The Bayesian expected power (BEP) has become increasingly popular in sample size determination and assessment of the probability of success (POS) for a future trial. The BEP takes…
Generalized Gaussian Mechanism for Differential Privacy
Fang Liu
Assessment of disclosure risk is of paramount importance in the research and applications of data privacy techniques. The concept of differential privacy (DP) formalizes privacy in…