Recurrent neural networks are theoretically capable of learning complex temporal sequences, but training them through gradient-descent is too slow and unstable for practical use i...
Customer preferences for products are drifting over time. Product perception and popularity are constantly changing as new selection emerges. Similarly, customer inclinations are ...
In the paper we propose a new evolutionary algorithm for induction of univariate regression trees that associate leaves with simple linear regression models. In contrast to typical...
Abstract With the ongoing shift from off-line to on-line business processes, the Web has become an important business platform, and for most companies it is crucial to have an on-...
—The discovery of evolving communities in dynamic networks is an important research topic that poses challenging tasks. Previous evolutionary based clustering methods try to maxi...