Abstract--This paper presents a dynamic predictiveoptimization framework of a nonlinear temporal process. Datamining (DM) and evolutionary strategy algorithms are integrated in the...
Abstract. This paper proposes a generic extension to propositional rule learners to handle multiple-instance data. In a multiple-instance representation, each learning example is r...
Abstract. Inspired by the recent advances in evolutionary biology, we have developed a self-organising, self-adaptable cellular system for multitask learning. The main aim of our p...
Abstract. Interactively learning from a small sample of unlabeled examples is an enormously challenging task. Relevance feedback and more recently active learning are two standard ...
Charlie K. Dagli, ShyamSundar Rajaram, Thomas S. H...
Abstract. The paper describes a complex e-learning experiment that has involved over 700 students that attended the Human-Computer Interaction course at the "Politehnica"...
Stefan Trausan-Matu, Vlad Posea, Traian Rebedea, C...