Existing clustering methods can be roughly classified into two categories: generative and discriminative approaches. Generative clustering aims to explain the data and thus is ad...
Abstract. Distributed cluster environments are becoming popular platforms for high performance computing in lieu of single-vendor supercomputers. However, the reliability and susta...
—Many registration scenarios involve aligning more than just two images. These image sets—called ensembles—are conventionally registered by choosing one image as a template, ...
Subspace clustering has many applications in computer vision, such as image/video segmentation and pattern classification. The major issue in subspace clustering is to obtain the ...
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...