Because many real-world problems can be represented and solved as constraint satisfaction problems, the development of effective, efficient constraint solvers is important. A solv...
The importance of learning distance functions is gradually being acknowledged by the machine learning community, and different techniques are suggested that can successfully learn ...
Online learning algorithms have recently risen to prominence due to their strong theoretical guarantees and an increasing number of practical applications for large-scale data ana...
—Cross-domain learning methods have shown promising results by leveraging labeled patterns from the auxiliary domain to learn a robust classifier for the target domain which has ...
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...