k-means++: few more steps yield constant approximation

no code implementations • ICML 2020 • Davin Choo, Christoph Grunau, Julian Portmann, Václav Rozhoň

The k-means++ algorithm of Arthur and Vassilvitskii (SODA 2007) is a state-of-the-art algorithm for solving the k-means clustering problem and is known to give an O(log k)-approximation in expectation.

Clustering