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A Sub-4 Approximation for Fair $k$-Means

Cheng, Kangke et al.
arXiv (All) · Papers
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computational-geometrymachine-learning
Fairness in clustering has attracted sustained research interest, motivated by the need to ensure equitable representation of protected groups in machine learning applications. We study fair $k$-means clustering in Euclidean space, where the proportion of each protected group in every cluster must l
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