26 citations · 26 across the 1 of their papers we have counts for
3 papers
cs.LG2019
Predictive Multiplicity in Classification
Charles T. Marx, Flavio du Pin Calmon, Berk Ustun
Prediction problems often admit competing models that perform almost equally well. This effect challenges key assumptions in machine learning when competing models assign conflicti…
cs.LG2019★ 26 cited
Repairing without Retraining: Avoiding Disparate Impact with Counterfactual Distributions
Hao Wang, Berk Ustun, Flavio P. Calmon
When the performance of a machine learning model varies over groups defined by sensitive attributes (e.g., gender or ethnicity), the performance disparity can be expressed in terms…
stat.ML2018
Actionable Recourse in Linear Classification
Berk Ustun, Alexander Spangher, Yang Liu
Machine learning models are increasingly used to automate decisions that affect humans - deciding who should receive a loan, a job interview, or a social service. In such applicati…