The $k$-means method is a popular algorithm for clustering, known for its speed in practice. This stands in contrast to its exponential worst-case running-time. To explain the speed of the $k$-means method, a smoothed analysis has been conducted. We sketch this smoothed analysis and a generalization to Bregman divergences

Manthey, Bodo

English

University of Twente Research Information

Towards explaining the speed of k-means

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https://ris.utwente.nl/ws/files/6538767/NVTI_kMeans_Manthey.pdf

Towards explaining the speed of $k$-means

Towards explaining the speed of $k$ -means

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University of Twente Research Information

Towards explaining the speed of kkk-means

Abstract

Similar works

Full text

Available Versions

University of Twente Research Information

Towards explaining the speed of $k$ -means