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cs.LG2024
FUGNN: Harmonizing Fairness and Utility in Graph Neural Networks
Renqiang Luo, Huafei Huang, Shuo Yu +4
Fairness-aware Graph Neural Networks (GNNs) often face a challenging trade-off, where prioritizing fairness may require compromising utility. In this work, we re-examine fairness t…
cs.CY2024
Algorithmic Fairness: A Tolerance Perspective
Renqiang Luo, Tao Tang, Feng Xia +5
Recent advancements in machine learning and deep learning have brought algorithmic fairness into sharp focus, illuminating concerns over discriminatory decision making that negativ…
cs.LG2024
FairGT: A Fairness-aware Graph Transformer
Renqiang Luo, Huafei Huang, Shuo Yu +2
The design of Graph Transformers (GTs) generally neglects considerations for fairness, resulting in biased outcomes against certain sensitive subgroups. Since GTs encode graph info…