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New in PNAS: Minority collapse in deep learning, unfairness for minority groups in high-stakes decisionmaking

New in PNAS: Minority collapse in deep learning, unfairness for minority groups in high-stakes decisionmaking

Posted on: October 2021

Our recent PNAS paper introduced the Layer-Peeled Model in deep learning that can: 1) predict a hitherto unknown phenomenon termed "Minority Collapse" in imbalanced training; and 2) explain neural collapse discovered by Papyan, Han and Donoho (PNAS, 2020). When minority collapse occurs, the deep learning classifiers on minor classes are simply identical to each other. This limitation can lead to severe fairness issues for minority groups in high-stakes decisionmaking.

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