5 citations · 10 across the 7 of their papers we have counts for
7 papers
Empirical Likelihood-Based Fairness Auditing: Distribution-Free Certification and Flagging
Jie Tang, Chuanlong Xie, Xianli Zeng +1
Machine learning models in high-stakes applications, such as recidivism prediction and automated personnel selection, often exhibit systematic performance disparities across sensit…
Minimax Optimal Fair Classification with Bounded Demographic Disparity
Xianli Zeng, Guang Cheng, Edgar Dobriban
Mitigating the disparate impact of statistical machine learning methods is crucial for ensuring fairness. While extensive research aims to reduce disparity, the effect of using a \…
FairRR: Pre-Processing for Group Fairness through Randomized Response
Xianli Zeng, Joshua Ward, Guang Cheng
The increasing usage of machine learning models in consequential decision-making processes has spurred research into the fairness of these systems. While significant work has been…
Bayes-Optimal Fair Classification with Linear Disparity Constraints via Pre-, In-, and Post-processing
Xianli Zeng, Kevin Jiang, Guang Cheng +1
Machine learning algorithms may have disparate impacts on protected groups. To address this, we develop methods for Bayes-optimal fair classification, aiming to minimize classifica…
Fair Bayes-Optimal Classifiers Under Predictive Parity
Xianli Zeng, Edgar Dobriban, Guang Cheng
Increasing concerns about disparate effects of AI have motivated a great deal of work on fair machine learning. Existing works mainly focus on independence- and separation-based me…
Bayes-Optimal Classifiers under Group Fairness
Xianli Zeng, Edgar Dobriban, Guang Cheng
Machine learning algorithms are becoming integrated into more and more high-stakes decision-making processes, such as in social welfare issues. Due to the need of mitigating the po…
Double Cross Validation for the Number of Factors in Approximate Factor Models
Xianli Zeng, Yingcun Xia, Linjun Zhang
Determining the number of factors is essential to factor analysis. In this paper, we propose {an efficient cross validation (CV)} method to determine the number of factors in appro…