  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.
