Discriminative subgraphs are widely used to define the feature space for graph classification in large graph databases. Several scalable approaches have been proposed to mine disc...
Graph transduction methods label input data by learning a classification function that is regularized to exhibit smoothness along a graph over labeled and unlabeled samples. In pr...
An important problem in the area of homeland security is to identify abnormal or suspicious entities in large datasets. Although there are methods from data mining and social netwo...
— 1 Taking advantage of the independent fading channel conditions among multiple wireless users, opportunistic transmissions schedule the user with the instantaneously best condi...
This paper improves our previous research effort [1] by providing an efficient method for kernel loop unrolling minimisation in the case of already scheduled loops, where circular...