6 citations · 18 across the 7 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…
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…
Lale: Consistent Automated Machine Learning
Guillaume Baudart, Martin Hirzel, Kiran Kate +2
Automated machine learning makes it easier for data scientists to develop pipelines by searching over possible choices for hyperparameters, algorithms, and even pipeline topologies…
Mining Documentation to Extract Hyperparameter Schemas
Guillaume Baudart, Peter D. Kirchner, Martin Hirzel +1
AI automation tools need machine-readable hyperparameter schemas to define their search spaces. At the same time, AI libraries often come with good human-readable documentation. Wh…
A semi-supervised deep learning algorithm for abnormal EEG identification
Subhrajit Roy, Kiran Kate, Martin Hirzel
Systems that can automatically analyze EEG signals can aid neurologists by reducing heavy workload and delays. However, such systems need to be first trained using a labeled datase…