Fine-Grained Cycle Sharing (FGCS) systems aim at utilizing the large amount of idle computational resources available on the Internet. Such systems allow guest jobs to run on a ho...
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...
Learning the user’s semantics for CBIR involves two different sources of information: the similarity relations entailed by the content-based features, and the relevance relatio...
Abstract. Since testing is inherently incomplete, test selection is of vital importance. Coverage measures evaluate the quality of a test suite and help the tester select test case...
Typical conversational recommender systems support interactive strategies that are hard-coded in advance and followed rigidly during a recommendation session. In fact, Reinforceme...