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  • title: Random Cuts are Optimal for Explainable k-Medians
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            Random Cuts are Optimal for Explainable k-Medians
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            Random Cuts are Optimal for Explainable k-Medians

            Dec 10, 2023

            Speakers

            KM

            Konstantin Makarychev

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            LS

            Liren Shan

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            About

            We show that the RandomCoordinateCut algorithm gives the optimal competitive ratio for explainable k-medians in ℓ_1. The problem of explainable k-medians was introduced by Dasgupta, Frost, Moshkovitz, and Rashtchian in 2020. Several groups of authors independently proposed a simple polynomial-time randomized algorithm for the problem and showed that this algorithm is O(log k loglog k) competitive. We provide a tight analysis of the algorithm and prove that its competitive ratio is upper bounded…

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            NeurIPS 2023

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