16 citations · 46 across the 7 of their papers we have counts for
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cs.LG2020★ 7 cited
Fairkit, Fairkit, on the Wall, Who's the Fairest of Them All? Supporting Data Scientists in Training Fair Models
Brittany Johnson, Jesse Bartola, Rico Angell +4
Modern software relies heavily on data and machine learning, and affects decisions that shape our world. Unfortunately, recent studies have shown that because of biases in data, so…
cs.CL2020
Clustering-based Inference for Biomedical Entity Linking
Rico Angell, Nicholas Monath, Sunil Mohan +2
Due to large number of entities in biomedical knowledge bases, only a small fraction of entities have corresponding labelled training data. This necessitates entity linking models…