Many learning algorithms form concept descriptions composed of clauses, each of which covers some proportion of the positive training data and a small to zero proportion of the ne...
In this paper, an easily implemented semi-supervised graph learning method is presented for dimensionality reduction and clustering, using the most of prior knowledge from limited...
Abstract. Learning in complex contexts often requires pure induction to be supported by various kinds of meta-information. Providing such information is a critical, difficult and ...
Stefano Ferilli, Floriana Esposito, Teresa Maria A...
Truly ubiquitous computing poses new and significant challenges. A huge number of heterogeneous devices will interact to perform complex distributed tasks. One of the key aspects...
Nicola Bicocchi, Marco Mamei, Andrea Prati, Rita C...
Literature on the use of machine learning (ML) algorithms for classifying IP traffic has relied on fullflows or the first few packets of flows. In contrast, many real-world scenar...