2 papers
cs.LG2024
Towards Harmless Rawlsian Fairness Regardless of Demographic Prior
Xuanqian Wang, Jing Li, Ivor W. Tsang +1
Due to privacy and security concerns, recent advancements in group fairness advocate for model training regardless of demographic information. However, most methods still require p…
cs.LG2024
Alpha and Prejudice: Improving -sized Worst-case Fairness via Intrinsic Reweighting
Jing Li, Yinghua Yao, Yuangang Pan +3
Worst-case fairness with off-the-shelf demographics achieves group parity by maximizing the model utility of the worst-off group. Nevertheless, demographic information is often una…