Spectral Clustering with Jensen-type kernels and their multi-point extensions

Motivated by multi-distribution divergences, which originate in information theory, we propose a notion of `multi-point' kernels, and study their applications. We study a class of kernels based on Jensen type divergences and show that these can be extended to measure similarity among multiple points. We study tensor flattening methods and develop a multi-point (kernel) spectral clustering (MSC) method. We further emphasize on a special case of the proposed kernels, which is a multi-point extension of the linear (dot-product) kernel and show the existence of cubic time tensor flattening algorithm in this case. Finally, we illustrate the usefulness of our contributions using standard data sets and image segmentation tasks.Comment: To appear in IEEE Computer Society Conference on Computer Vision and Pattern Recognitio

Influence of Ni doping on the electronic structure of Ni_2MnGa

The modifications in the electronic structure of Ni_{2+x}Mn_{1-x}Ga by Ni doping have been studied using full potential linearized augmented plane wave method and ultra-violet photoemission spectroscopy. Ni 3d related electron states appear due to formation of Ni clusters. We show the possibility of changing the minority-spin DOS with Ni doping, while the majority-spin DOS remains almost unchanged. The total magnetic moment decreases with excess Ni. The total energy calculations corroborate the experimentally reported changes in the Curie temperature and the martensitic transition temperature with x.Comment: 4 pages, 4 figures, accepted in Phys. Rev.