3 papers
cs.LG2025
BiMi Sheets: Infosheets for bias mitigation methods
MaryBeth Defrance, Guillaume Bied, Maarten Buyl +2
Over the past 15 years, hundreds of bias mitigation methods have been proposed in the pursuit of fairness in machine learning (ML). However, algorithmic biases are domain-, task-,…
cs.CV2025
Biased Heritage: How Datasets Shape Models in Facial Expression Recognition
Iris Dominguez-Catena, Daniel Paternain, Mikel Galar +3
In recent years, the rapid development of artificial intelligence (AI) systems has raised concerns about our ability to ensure their fairness, that is, how to avoid discrimination…
cs.LG2024
ABCFair: an Adaptable Benchmark approach for Comparing Fairness Methods
MaryBeth Defrance, Maarten Buyl, Tijl De Bie
Numerous methods have been implemented that pursue fairness with respect to sensitive features by mitigating biases in machine learning. Yet, the problem settings that each method…