An Interior Point Algorithm for Minimum Sum-of-Squares Clustering

@article{Merle1999AnIP,
  title={An Interior Point Algorithm for Minimum Sum-of-Squares Clustering},
  author={Olivier du Merle and Pierre Hansen and Brigitte Jaumard and Nenad Mladenovi{\'c}},
  journal={SIAM J. Sci. Comput.},
  year={1999},
  volume={21},
  pages={1485-1505}
}
An exact algorithm is proposed for minimum sum-of-squares nonhierarchical clustering, i.e., for partitioning a given set of points from a Euclidean m-space into a given number of clusters in order to minimize the sum of squared distances from all points to the centroid of the cluster to which they belong. This problem is expressed as a constrained hyperbolic program in 0-1 variables. The resolution method combines an interior point algorithm, i.e., a weighted analytic center column generation… 
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