Multi-instance (MI) learning is a variant of supervised learning where labeled examples consist of bags (i.e. multi-sets) of feature vectors instead of just a single feature vecto...
Naive Bayes models have been widely used for clustering and classification. However, they are seldom used for general probabilistic learning and inference (i.e., for estimating an...
E-Learning is a fast, just-in-time, and non-linear learning process, which is now widely applied in distributed and dynamic environments such as on the World Wide Web. However, it...
Collaborative learning is question-driven and open-ended by nature. Many of the techniques developed for intelligent tutoring are applicable only in more structured settings, but f...
Abstract. Nowadays, there is a big discussion about two different topics: how distance learning and the old fashioned learning can be improved using the new technologies. In both ...