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K-means clustering struggles with big data due to the NP-hard Minimum Sum-of-Squares Clustering problem. A new method targets this issue with a data-native global optimization approach. This could improve clustering results, but we don't know yet how it holds up in practice.
“arXiv:2607.15835v1 Announce Type: new Abstract: Big data clustering remains challenging: the Minimum Sum-of-Squares Clustering (MSSC) problem underlying K-means is NP-hard, and existing methods either reach poor local minima or require proh…”
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K-means, Minimum Sum-of-Squares Clustering, arXiv
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Aug 5, 2026