Title :
Total Jensen divergences: Definition, properties and clustering
Author :
Nielsen, Frank ; Nock, Richard
Author_Institution :
Ecole Polytech., Palaiseau, France
Abstract :
We present a novel class of divergences induced by a smooth convex function called total Jensen divergences that are invariant by construction to rotations, a feature inducing a conformal factor on ordinary Jensen divergences. We analyze the relationships between this novel class of total Jensen divergences and the total Bregman divergences. We then define total Jensen centroids, analyze their robustness, and prove that the k-means++ initialization that bypasses explicit centroid computations is good enough in practice to guarantee probabilistically a constant approximation factor to the optimal k-means clustering.
Keywords :
convex programming; parameter estimation; probability; conformal factor; constant approximation factor; explicit centroid computations; optimal k-means clustering; smooth convex function; total Jensen divergences; Diffusion tensor imaging; Distortion measurement; Ellipsoids; Generators; Radio frequency; Robustness; Symmetric matrices; Burbea-Rao divergences; Clustering; Jensen-Shannon divergence; centroids; k-means++;
Conference_Titel :
Acoustics, Speech and Signal Processing (ICASSP), 2015 IEEE International Conference on
Conference_Location :
South Brisbane, QLD
DOI :
10.1109/ICASSP.2015.7178324