Improved Guarantees for k-means++ and k-means++ Parallel

In this paper, we study k-means and k-means, the two most popular algorithms for the classic k-means clustering problem. We provide novel analyses and show improved approximation and bi-criteria approximation guarantees for k-means and k-means . Our results give a better theoretical justification for why these algorithms perform extremely well in practice.