32 citations · 112 across the 6 of their papers we have counts for
3 papers · 1 filter
Group Fairness in Bandit Arm Selection
Candice Schumann, Zhi Lang, Nicholas Mattei +1
We propose a novel formulation of group fairness with biased feedback in the contextual multi-armed bandit (CMAB) setting. In the CMAB setting, a sequential decision maker must, at…
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…
Making the Cut: A Bandit-based Approach to Tiered Interviewing
Candice Schumann, Zhi Lang, Jeffrey S. Foster +1
Given a huge set of applicants, how should a firm allocate sequential resume screenings, phone interviews, and in-person site visits? In a tiered interview process, later stages (e…