Jan. 31, 2024, 3:45 p.m. | Daniel Hsu Jizhou Huang Brendan Juba

cs.LG updates on arXiv.org arxiv.org

We study the problem of auditing classifiers with the notion of statistical subgroup fairness. Kearns et al. (2018) has shown that the problem of auditing combinatorial subgroups fairness is as hard as agnostic learning. Essentially all work on remedying statistical measures of discrimination against subgroups assumes access to an oracle for this problem, despite the fact that no efficient algorithms are known for it. If we assume the data distribution is Gaussian, or even merely log-concave, then a recent line …

classifiers cs.cc cs.cy cs.lg data discrimination fairness notion oracle polynomial statistical study subgroups work

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