7 citations · 12 across the 2 of their papers we have counts for
2 papers
cs.LG2021★ 5 cited
Can Active Learning Preemptively Mitigate Fairness Issues?
Frédéric Branchaud-Charron, Parmida Atighehchian, Pau Rodríguez +2
Dataset bias is one of the prevailing causes of unfairness in machine learning. Addressing fairness at the data collection and dataset preparation stages therefore becomes an essen…
cs.CY2020★ 7 cited
Like a Researcher Stating Broader Impact For the Very First Time
Grace Abuhamad, Claudel Rheault
In requiring that a statement of broader impact accompany all submissions for this year's conference, the NeurIPS program chairs made ethics part of the stake in groundbreaking AI…