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arXiv · 1810.10770

Geometry and clustering with metrics derived from separable Bregman divergences

Erika Gomes-Gonçalves·Henryk Gzyl·Frank Nielsen
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Abstract

Separable Bregman divergences induce Riemannian metric spaces that are isometric to the Euclidean space after monotone embeddings. We investigate fixed rate quantization and its codebook Voronoi diagrams, and report on experimental performances of partition-based, hierarchical, and soft clustering algorithms with respect to these Riemann-Bregman distances.

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Erika Gomes-Gonçalves, Henryk Gzyl, Frank Nielsen. 2018-10-25. Geometry and clustering with metrics derived from separable Bregman divergences. https://arxiv.org/abs/1810.10770

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