Entropy Guided Transformation Learning (ETL) is a new machine learning strategy that combines the advantages of decision trees (DT) and Transformation Based Learning (TBL). In thi...
This paper presents a communication-less multi-agent task allocation procedure that allows agents to use past experience to make non-greedy decisions about task assignments. Exper...
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...
Bayesian learning in undirected graphical models--computing posterior distributions over parameters and predictive quantities-is exceptionally difficult. We conjecture that for ge...
Work-integrated learning (WIL) poses unique challenges for user model design: on the one hand users’ knowledge levels need to be determined based on their work activities – tes...