Data mining evolved as a collection of applicative problems and efficient solution algorithms relative to rather peculiar problems, all focused on the discovery of relevant infor...
Abstract. Innovations such as optimistic exploration, function approximation, and hierarchical decomposition have helped scale reinforcement learning to more complex environments, ...
Abstract. In order to increase precision in searching for web pages or web documents, taking the temporal dimension into account is gaining increased interest. A particular problem...
We propose adaptive nonlinear auto-associative modeling (ANAM) based on Locally Linear Embedding algorithm (LLE) for learning intrinsic principal features of each concept separatel...
Data on individuals and entities are being collected widely. These data can contain information that explicitly identifies the individual (e.g., social security number). Data can ...