46 citations · 104 across the 35 of their papers we have counts for
5 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…
Automatically Debugging AutoML Pipelines using Maro: ML Automated Remediation Oracle (Extended Version)
Julian Dolby, Jason Tsay, Martin Hirzel
Machine learning in practice often involves complex pipelines for data cleansing, feature engineering, preprocessing, and prediction. These pipelines are composed of operators, whi…
Low-Code Programming Models
Martin Hirzel
Traditionally, computer programming has been the prerogative of professional developers using textual programming languages such as C, Java, or Python. Low-code programming promise…
Comments on Comments: Where Code Review and Documentation Meet
Nikitha Rao, Jason Tsay, Martin Hirzel +1
A central function of code review is to increase understanding; helping reviewers understand a code change aids in knowledge transfer and finding bugs. Comments in code largely ser…
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…