This paper proposes a logic-oriented framework for institutional agents specification and analysis. Within this framework institutional agents are seen as artificial agents that a...
Abstract. A crucial problem in machine learning is to choose an appropriate representation of data, in a way that emphasizes the relations we are interested in. In many cases this ...
This paper presents a new approach to text processing, based on textemes. These are atomic text units generalising the concepts of character and glyph by merging them in a common ...
In recent years subdivision methods have been one of the most successful techniques applied to the multi-resolution representation and visualization of surface meshes. Extension t...
We investigate the use of linear and nonlinear principal manifolds for learning low-dimensional representations for visual recognition. Several leading techniques: Principal Compo...