6 citations · 24 across the 15 of their papers we have counts for
3 papers · 1 filter
Navigating Ensemble Configurations for Algorithmic Fairness
Michael Feffer, Martin Hirzel, Samuel C. Hoffman +3
Bias mitigators can improve algorithmic fairness in machine learning models, but their effect on fairness is often not stable across data splits. A popular approach to train more s…
Exploring Code Style Transfer with Neural Networks
Karl Munson, Anish Savla, Chih-Kai Ting +3
Style is a significant component of natural language text, reflecting a change in the tone of text while keeping the underlying information the same. Even though programming langua…
An Empirical Study of Modular Bias Mitigators and Ensembles
Michael Feffer, Martin Hirzel, Samuel C. Hoffman +3
There are several bias mitigators that can reduce algorithmic bias in machine learning models but, unfortunately, the effect of mitigators on fairness is often not stable when meas…