The Hardness of Approximation of Euclidean k-Means

@inproceedings{Awasthi2015TheHO,
  title={The Hardness of Approximation of Euclidean k-Means},
  author={Pranjal Awasthi and M. Charikar and Ravishankar Krishnaswamy and A. Sinop},
  booktitle={SoCG},
  year={2015}
}
The Euclidean $k$-means problem is a classical problem that has been extensively studied in the theoretical computer science, machine learning and the computational geometry communities. In this problem, we are given a set of $n$ points in Euclidean space $R^d$, and the goal is to choose $k$ centers in $R^d$ so that the sum of squared distances of each point to its nearest center is minimized. The best approximation algorithms for this problem include a polynomial time constant factor… Expand
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