The purpose of this paper is three-fold. First, we formalize and study a problem of learning probabilistic concepts in the recently proposed KWIK framework. We give details of an ...
This work addresses the problem of finding the adjustable parameters of a learning algorithm using Genetic Algorithms. This problem is also known as the model selection problem. In...
Building blocks are a ubiquitous feature at all levels of human understanding, from perception through science and innovation. Genetic algorithms are designed to exploit this prev...
Word Sense Disambiguation in text is still a difficult problem as the best supervised methods require laborious and costly manual preparation of training data. Thus, this work focu...
Abstract. It has been shown that many kernel methods can be equivalently formulated as minimal-enclosing-ball (MEB) problems in certain feature space. Exploiting this reduction eff...
Emanuele Frandi, Maria Grazia Gasparo, Stefano Lod...