—A major assumption in many machine learning and data mining algorithms is that the training and future data must be in the same feature space and have the same distribution. How...
Much has been made of the need for academic planning research to orient towards real-world applications. In this paper, we relate our experience in adapting domain-independent pla...
Abstract. Conditional Random Fields (CRFs) provide a powerful instrument for labeling sequences. So far, however, CRFs have only been considered for labeling sequences over flat al...
Bias/variance analysis is a useful tool for investigating the performance of machine learning algorithms. Conventional analysis decomposes loss into errors due to aspects of the le...
Machine Learning systems are often distinguished according to the kind of representation they use, which can be either propositional or first-order logic. The framework working wi...
Teresa Maria Altomare Basile, Floriana Esposito, N...