Thomas Bottesch

Speeding up k-means by approximating Euclidean distances via block vectors

This paper introduces a new method to approximate Euclidean distances between points using block vectors in combination with the Hölder inequality. By defining lower bounds based on the proposed approximation, cluster algorithms can be considerably accelerated without loss of quality. In extensive e…