2 papers
cs.LG2024
Metric-DST: Mitigating Selection Bias Through Diversity-Guided Semi-Supervised Metric Learning
Yasin I. Tepeli, Mathijs de Wolf, Joana P. Gonçalves
Selection bias poses a critical challenge for fairness in machine learning, as models trained on data that is less representative of the population might exhibit undesirable behavi…
cs.LG2024
DCAST: Diverse Class-Aware Self-Training Mitigates Selection Bias for Fairer Learning
Yasin I. Tepeli, Joana P. Gonçalves
Fairness in machine learning seeks to mitigate model bias against individuals based on sensitive features such as sex or age, often caused by an uneven representation of the popula…