Feb. 13, 2024, 5:43 a.m. | MohammadHossein Bateni Vincent Cohen-Addad Alessandro Epasto Silvio Lattanzi

cs.LG updates on arXiv.org arxiv.org

We present a scalable algorithm for the individually fair ($p$, $k$)-clustering problem introduced by Jung et al. and Mahabadi et al. Given $n$ points $P$ in a metric space, let $\delta(x)$ for $x\in P$ be the radius of the smallest ball around $x$ containing at least $n / k$ points. A clustering is then called individually fair if it has centers within distance $\delta(x)$ of $x$ for each $x\in P$. While good approximation algorithms are known for this problem no …

algorithm clustering cs.ds cs.lg delta fair k-means least scalable space

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