Given a set of categories, with or without a preexisting hierarchy among them, we consider the problem of assigning documents to one or more of these categories from the point of ...
Stephen D'Alessio, Keitha A. Murray, Robert Schiaf...
Abstract—In this paper, we introduce a reconstruction framework that explicitly accounts for image geometry when defining the spatial interaction between pixels in the filterin...
"This book is about the fundamentals of data structures and algorithms--the basic elements from which large and complex software artifacts are built. To develop a solid unders...
Linear Discriminant Analysis (LDA) is a popular statistical approach for dimensionality reduction. LDA captures the global geometric structure of the data by simultaneously maximi...
This paper investigates a new learning formulation called structured sparsity, which is a naturalextensionofthestandardsparsityconceptinstatisticallearningandcompressivesensing. B...