27 citations · 65 across the 4 of their papers we have counts for
3 papers · 1 filter
Toward a better trade-off between performance and fairness with kernel-based distribution matching
Flavien Prost, Hai Qian, Qiuwen Chen +3
As recent literature has demonstrated how classifiers often carry unintended biases toward some subgroups, deploying machine learned models to users demands careful consideration o…
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…
Putting Fairness Principles into Practice: Challenges, Metrics, and Improvements
Alex Beutel, Jilin Chen, Tulsee Doshi +6
As more researchers have become aware of and passionate about algorithmic fairness, there has been an explosion in papers laying out new metrics, suggesting algorithms to address i…