In this paper we study the range assignment problem in static ad-hoc networks on metric spaces. We consider the h-strong connectivity and h-broadcast problems on trees, high dimens...
Vector Space Model (VSM) has been at the core of information retrieval for the past decades. VSM considers the documents as vectors in high dimensional space. In such a vector spa...
Traditional visualization techniques for multidimensional data sets, such as parallel coordinates, glyphs, and scatterplot matrices, do not scale well to high numbers of dimension...
Jing Yang, Matthew O. Ward, Elke A. Rundensteiner,...
Recent years have witnessed a dramatic increase in the quantity of image data collected, due to advances in fields such as medical imaging, reconnaissance, surveillance, astronomy...
Dimension reduction is popular for learning predictive models in high-dimensional spaces. It can highlight the relevant part of the feature space and avoid the curse of dimensiona...