Naive Bayes is an effective and efficient learning algorithm in classification. In many applications, however, an accurate ranking of instances based on the class probability is m...
In many application domains there is a large amount of unlabeled data but only a very limited amount of labeled training data. One general approach that has been explored for util...
Avrim Blum, John D. Lafferty, Mugizi Robert Rweban...
Inductive learning of first-order theory based on examples has serious bottleneck in the enormous hypothesis search space needed, making existing learning approaches perform poorl...
The design and implementation of the reconstruction system in medical X-ray imaging is a challenging issue due to its immense computational demands. In order to ensure an efficien...
Holger Scherl, Stefan Hoppe, Markus Kowarschik, Jo...
Separation of concerns is one of the overarching goals of exception handling in order to keep separate normal and exceptional behaviour of a software system. In the context of a s...
Ivo Augusto Bertoncello, Marcelo Oliveira Dias, Pa...