20 citations · 21 across the 4 of their papers we have counts for
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cs.LG2020★ 1 cited
Learning Interpretable Concept-Based Models with Human Feedback
Isaac Lage, Finale Doshi-Velez
Machine learning models that first learn a representation of a domain in terms of human-understandable concepts, then use it to make predictions, have been proposed to facilitate i…
cs.LG2020
When Does Uncertainty Matter?: Understanding the Impact of Predictive Uncertainty in ML Assisted Decision Making
Sean McGrath, Parth Mehta, Alexandra Zytek +2
As machine learning (ML) models are increasingly being employed to assist human decision makers, it becomes critical to provide these decision makers with relevant inputs which can…