k-Means Clustering with Hölder Divergences

Frank Nielsen, Ke Sun, Stéphane Marchand-Maillet

Research output: Chapter in Book/Report/Conference proceedingConference contribution

3 Scopus citations

Abstract

We introduced two novel classes of Hölder divergences and Hölder pseudo-divergences that are both invariant to rescaling, and that both encapsulate the Cauchy-Schwarz divergence and the skew Bhattacharyya divergences. We review the elementary concepts of those parametric divergences, and perform a clustering analysis on two synthetic datasets. It is shown experimentally that the symmetrized Hölder divergences consistently outperform significantly the Cauchy-Schwarz divergence in clustering tasks.
Original languageEnglish (US)
Title of host publicationLecture Notes in Computer Science
PublisherSpringer Nature
Pages856-863
Number of pages8
ISBN (Print)9783319684444
DOIs
StatePublished - Oct 24 2017

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