—A variety of clustering algorithms have recently been proposed to handle data that is not linearly separable; spectral clustering and kernel k-means are two of the main methods....
This article addresses the problem of efficient multi-robot patrolling in a known environment. The proposed approach assigns regions to each mobile agent. Every region is represen...
Abstract. We use a parallel direct solver based on the Schur complement method for solving large sparse linear systems arising from the finite element method. A domain decompositi...
Clustered architectures are a solution to the bottleneck of centralized register files in superscalar and VLIW processors. The main challenge associated with clustered architectu...
The recent years have witnessed a surge of interest in graphbased semi-supervised learning methods. The common denominator of these methods is that the data are represented by the...