267 citations · 506 across the 14 of their papers we have counts for
3 papers · 1 filter
Repairing Regressors for Fair Binary Classification at Any Decision Threshold
Kweku Kwegyir-Aggrey, A. Feder Cooper, Jessica Dai +3
We study the problem of post-processing a supervised machine-learned regressor to maximize fair binary classification at all decision thresholds. By decreasing the statistical dist…
Fair clustering via equitable group representations
Mohsen Abbasi, Aditya Bhaskara, Suresh Venkatasubramanian
What does it mean for a clustering to be fair? One popular approach seeks to ensure that each cluster contains groups in (roughly) the same proportion in which they exist in the po…
Equalizing Recourse across Groups
Vivek Gupta, Pegah Nokhiz, Chitradeep Dutta Roy +1
The rise in machine learning-assisted decision-making has led to concerns about the fairness of the decisions and techniques to mitigate problems of discrimination. If a negative d…