42 citations · 77 across the 8 of their papers we have counts for
8 papers
Achieving Counterfactual Fairness for Causal Bandit
Wen Huang, Lu Zhang, Xintao Wu
In online recommendation, customers arrive in a sequential and stochastic manner from an underlying distribution and the online decision model recommends a chosen item for each arr…
Fairness through Equality of Effort
Wen Huang, Yongkai Wu, Lu Zhang +1
Fair machine learning is receiving an increasing attention in machine learning fields. Researchers in fair learning have developed correlation or association-based measures such as…
Fairness-aware Classification: Criterion, Convexity, and Bounds
Yongkai Wu, Lu Zhang, Xintao Wu
Fairness-aware classification is receiving increasing attention in the machine learning fields. Recently research proposes to formulate the fairness-aware classification as constra…
FairGAN: Fairness-aware Generative Adversarial Networks
Depeng Xu, Shuhan Yuan, Lu Zhang +1
Fairness-aware learning is increasingly important in data mining. Discrimination prevention aims to prevent discrimination in the training data before it is used to conduct predict…
On Discrimination Discovery and Removal in Ranked Data using Causal Graph
Yongkai Wu, Lu Zhang, Xintao Wu
Predictive models learned from historical data are widely used to help companies and organizations make decisions. However, they may digitally unfairly treat unwanted groups, raisi…
Achieving non-discrimination in prediction
Lu Zhang, Yongkai Wu, Xintao Wu
Discrimination-aware classification is receiving an increasing attention in data science fields. The pre-process methods for constructing a discrimination-free classifier first rem…
A causal framework for discovering and removing direct and indirect discrimination
Lu Zhang, Yongkai Wu, Xintao Wu
Anti-discrimination is an increasingly important task in data science. In this paper, we investigate the problem of discovering both direct and indirect discrimination from the his…
Achieving non-discrimination in data release
Lu Zhang, Yongkai Wu, Xintao Wu
Discrimination discovery and prevention/removal are increasingly important tasks in data mining. Discrimination discovery aims to unveil discriminatory practices on the protected a…