Multigroup Robustness: Ensuring Subgroups Are Not Harmed by Unrelated Data Corruption

Multigroup robust learning algorithms ensure that the effects of dataset corruption on every subpopulation-of-interest are bounded by the amount of corruption to data within that subpopulation, even when the data corruption is not distributed uniformly over subpopulations.