We present a method to represent unstructured scalar fields at multiple levels of detail. Using a parallelizable classification algorithm to build a cluster hierarchy, we generate...
We consider a hierarchical two-layer model of natural signals in which both layers are learned from the data. Estimation is accomplished by Score Matching, a recently proposed est...
We consider a class of learning problems that involve a structured sparsityinducing norm defined as the sum of -norms over groups of variables. Whereas a lot of effort has been pu...
In this paper, we propose a tree-based multidimensional structure, GeM-Tree, which indexes both images and videos within a single general framework utilizing Earth Mover’s Dista...
Abstract. Hierarchical classification problems gained increasing attention within the machine learning community, and several methods for hierarchically structured taxonomies have...