Towards Optimal Lower Bounds for k-median and k-means Coresets. (arXiv:2202.12793v1 [cs.DS])

Given a set of points in a metric space, the $(k,z)$-clustering problem
consists of finding a set of $k$ points called centers, such that the sum of
distances raised to the power of $z$ of every data point to its closest center
is minimized. Special cases include the famous k-median problem ($z = 1$) and
k-means problem ($z = 2$). The $k$-median and $k$-means problems are at the
heart of modern data analysis and massive data applications have given raise …

arxiv k-means