Automata models of learning systems introduced in the 1960s were popularized as learning automata (LA) in a survey paper in 1974 [1]. Since then, there have been many fundamental a...
When applied to real-world problems, the powerful optimization tool of Evolutionary Algorithms frequently turns out to be too time-consuming due to elaborate fitness calculations t...
The algebraic hierarchical decomposition of finite state automata can be applied wherever a finite system should be `understood' using a hierarchical coordinate system. Here ...
New applications from the areas of analytical data processing and data integration require powerful features to condense and reconcile available data. Object-relational and other d...
The group Lasso is an extension of the Lasso for feature selection on (predefined) non-overlapping groups of features. The non-overlapping group structure limits its applicability...