43 citations · 56 across the 5 of their papers we have counts for
5 papers
MCMH: Learning Multi-Chain Multi-Hop Rules for Knowledge Graph Reasoning
Lu Zhang, Mo Yu, Tian Gao +1
Multi-hop reasoning approaches over knowledge graphs infer a missing relationship between entities with a multi-hop rule, which corresponds to a chain of relationships. We extend e…
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…
PC-Fairness: A Unified Framework for Measuring Causality-based Fairness
Yongkai Wu, Lu Zhang, Xintao Wu +1
A recent trend of fair machine learning is to define fairness as causality-based notions which concern the causal connection between protected attributes and decisions. However, on…
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…