Clustering with Bregman Divergences
The Journal of Machine Learning Research
SODA '07 Proceedings of the eighteenth annual ACM-SIAM symposium on Discrete algorithms
Pattern learning and recognition on statistical manifolds: an information-geometric review
SIMBAD'13 Proceedings of the Second international conference on Similarity-Based Pattern Recognition
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Voronoi diagrams are fundamental geometric structures that partition the space into elementary regions of influence defining discrete proximity graphs and dually well-shaped Delaunay triangulations [Aurenhammer & Klein, 2000]. In this video, we explain and illustrate a recent generalization of Voronoi diagrams [Nielsen et al., 2007] to a wide class of distortion measures called Bregman divergences [Banerjee et al., 2005].