DataSift orders data-pool points by predicted effect on demographic parity and uses a bandit over partitions to acquire them, improving fairness with less data than baselines.
Using upper confidence bounds for online learning
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Data Acquisition for Improving Model Fairness using Reinforcement Learning
DataSift orders data-pool points by predicted effect on demographic parity and uses a bandit over partitions to acquire them, improving fairness with less data than baselines.