In this paper, we explore the use of hierarchically structured multiprocessor tasks (M-tasks) for programming multi-core cluster systems. These systems often have hierarchically s...
This paper investigates a new learning formulation called dynamic group sparsity. It is a natural extension of the standard sparsity concept in compressive sensing, and is motivat...
Clustering is a data mining problem which finds dense regions in a sparse multi-dimensional data set. The attribute values and ranges of these regions characterize the clusters. ...
Detection of web attacks is an important issue in current defense-in-depth security framework. In this paper, we propose a novel general framework for adaptive and online detectio...
Wei Wang 0012, Florent Masseglia, Thomas Guyet, Re...
In this paper we present a method for impulse noise removal that makes use of spectral clustering and graph regularization. The image is modeled as a graph and local spectral anal...
Olivier Lezoray, Vinh-Thong Ta, Abderrahim Elmoata...