25 citations · 101 across the 9 of their papers we have counts for
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cs.LG2021★ 9 cited
Predicting Early Dropout: Calibration and Algorithmic Fairness Considerations
Marzieh Karimi-Haghighi, Carlos Castillo, Davinia Hernandez-Leo +1
In this work, the problem of predicting dropout risk in undergraduate studies is addressed from a perspective of algorithmic fairness. We develop a machine learning method to predi…
cs.LG2020
Addressing multiple metrics of group fairness in data-driven decision making
Marius Miron, Songül Tolan, Emilia Gómez +1
The Fairness, Accountability, and Transparency in Machine Learning (FAT-ML) literature proposes a varied set of group fairness metrics to measure discrimination against socio-demog…