Abstract. The key for providing a robust context for personalized information retrieval is to build a library which gathers the long term and the short term user’s interests and ...
Abstract. We describe an ensemble of classifiers based algorithm for incremental learning in nonstationary environments. In this formulation, we assume that the learner is presente...
Abstract. There has been growing interest in practice in using unlabeled data together with labeled data in machine learning, and a number of different approaches have been develo...
Abstract. In this paper we describe a methodology for harvesting information from large distributed repositories (e.g. large Web sites) with minimum user intervention. The methodol...
Fabio Ciravegna, Sam Chapman, Alexiei Dingli, Yori...
Abstract. Most of multi-agent reinforcement learning algorithms aim to converge to a Nash equilibrium, but a Nash equilibrium does not necessarily mean a desirable result. On the o...