106 citations · 307 across the 18 of their papers we have counts for
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cs.LG2019
Practical Compositional Fairness: Understanding Fairness in Multi-Component Recommender Systems
Xuezhi Wang, Nithum Thain, Anu Sinha +4
How can we build recommender systems to take into account fairness? Real-world recommender systems are often composed of multiple models, built by multiple teams. However, most res…
cs.LG2019★ 27 cited
Transfer of Machine Learning Fairness across Domains
Candice Schumann, Xuezhi Wang, Alex Beutel +3
If our models are used in new or unexpected cases, do we know if they will make fair predictions? Previously, researchers developed ways to debias a model for a single problem doma…