A clustering framework within the sparse modeling and dictionary learning setting is introduced in this work. Instead of searching for the set of centroid that best fit the data, ...
Pablo Sprechmann, Ignacio Ramirez, Guillermo Sapir...
In this paper a novel approach for semi-supervised hyperspectral unmixing is presented. First, it is shown that this problem inherently accepts a sparse solution. Then, based on t...
Konstantinos Themelis, Athanasios A. Rontogiannis,...
In this paper we present a novel approach to describe sound mixtures which is based on a geometric viewpoint. In this approach we extend the idea of a nearest-neighbor representat...
We present a new general class of methods for the computation of high-dimensional integrals. The quadrature schemes result by truncation and discretization of the anchored-ANOVA d...
The limiting factor for efficiency of sparse linear solvers is the memory bandwidth. In this work, we utilize GPU’s high memory bandwidth for implementation of a sparse iterative...