43 citations · 249 across the 65 of their papers we have counts for
5 papers · 1 filter
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…
SAFE: A Neural Survival Analysis Model for Fraud Early Detection
Panpan Zheng, Shuhan Yuan, Xintao Wu
Many online platforms have deployed anti-fraud systems to detect and prevent fraudulent activities. However, there is usually a gap between the time that a user commits a fraudulen…
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…
One-Class Adversarial Nets for Fraud Detection
Panpan Zheng, Shuhan Yuan, Xintao Wu +2
Many online applications, such as online social networks or knowledge bases, are often attacked by malicious users who commit different types of actions such as vandalism on Wikipe…