In this study, we propose a novel evolutionary algorithm-based clustering method, named density-sensitive evolutionary clustering (DSEC). In DSEC, each individual is a sequence of ...
Decomposing a software system into smaller, more manageable clusters is a common approach to support the comprehension of large systems. In recent years, researchers have focused ...
Abstract. In this article we present the framework of Possibilistic Influence Diagrams (PID), which allow to model in a compact form problems of sequential decision making under un...
This paper1 explores the use of a Maximal Average Margin (MAM) optimality principle for the design of learning algorithms. It is shown that the application of this risk minimizati...
Kristiaan Pelckmans, Johan A. K. Suykens, Bart De ...
—The realistic performance of a multi-input multi-output (MIMO) communication system depends strongly on the spatial correlation properties introduced by clustering in the propag...