In this paper we extend a previous definition of gradual dependence as a special kind of (crisp) association rule, in order to measure not only the existence of a tendency, but i...
The main objective of this paper is to provide an efficient tool for delineating brain tumors in three-dimensional magnetic resonance images. To achieve this goal, we use basically...
Variational methods for approximate inference in machine learning often adapt a parametric probability distribution to optimize a given objective function. This view is especially ...
Antti Honkela, Matti Tornio, Tapani Raiko, Juha Ka...
In this paper we propose novel optimization models for the planning of Wireless Mesh Networks whose objective is to minimize the network installation cost, while providing full cov...
Edoardo Amaldi, Antonio Capone, Matteo Cesana, Fed...
Humanoid robots are fascinating from two points of view, firstly their construction and secondly because they lend life to inanimate objects. The combination of biology and robots ...
Ivo Boblan, Rudolf Bannasch, Hartmut Schwenk, Fran...