Introduction to Fusion of Machine Learning Paradigms

In the recent years, Machine Learning research has been exploring integrated or hybrid learning methodologies, i.e. methodologies that fuse together two or more Machine Learning approaches and promise to achieve higher performance and better efficiency when compared to those of their constituent components. The book at hand, consisting of this editorial note and an additional eight chapters, aims at updating the relevant computer science-related research communities, including professors, researchers, scientists, engineers and students, as well as the general reader from other disciplines, on the most recent advances in applications of methods based on Fusing Machine Learning Paradigms.