We are designing a computational architecture for a "learning economy" based on personal software agents who represent users in a virtual society and assist them in find...
Learning from data streams is a research area of increasing importance. Nowadays, several stream learning algorithms have been developed. Most of them learn decision models that c...
Learning software is not designed for data analysis and mining. Because usage data is not stored in a systematic way, its thorough analysis requires long and tedious preprocessing....
Active and semi-supervised learning are important techniques when labeled data are scarce. Recently a method was suggested for combining active learning with a semi-supervised lea...
Abstract a paradigm of modern Machine Learning (ML) which uses rewards and punishments to guide the learning process. One of the central ideas of RL is learning by “direct-online...