- Christian Alexander Sohler
- Silvio Lattanzi
In this paper, we develop a new variant of $k$-means++ seeding that in expectation achieves a constant approximation guarantee. We obtain this result by a simple combination of $k$-means++ sampling with a local search strategy.
We evaluate our algorithm empirically and show that it also improves the quality of a solution in practice.