A Sub-4 Approximation for Fair $k$-Means
This work proposes an approximation algorithm that combines a linear programming relaxation with geometric transformations of the input to construct candidate center sets in fair $k-means clustering in Euclidean space and satisfies all fairness constraints exactly.
Kang Cheng, Guan-Lin Mo, Shi-Hong Song et al.
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