## Simple and sharp analysis of k-means||

### Vaclav Rozhon

Keywords: [ Unsupervised Learning ] [ Unsupervised and Semi-Supervised Learning ]

Abstract: We present a simple analysis of k-means|| (Bahmani et al., PVLDB 2012) - a distributed variant of the k-means++ algorithm (Arthur and Vassilvitskii, SODA 2007). Moreover, the bound on the number of rounds is improved from $O(\log n)$ to $O(\log n / \log\log n)$, which we show to be tight.