Feature selection is often applied to highdimensional data prior to classification learning. Using the same training dataset in both selection and learning can result in socalled ...
This paper looks at the problem of data prioritization, commonly found in mobile ad-hoc networks. The proposed general solution uses a machine learning approach in order to learn ...
: The aim of all education is to apply what we learn in different contexts and to recognise and extend this learning to new situations. Virtual learning environments can used to bu...
We propose a new neural network architecture, called Simple Recurrent Temporal-Difference Networks (SR-TDNs), that learns to predict future observations in partially observable en...
Educational media mining is the process of converting raw media data from educational systems to useful information that can be used to design learning systems, answer research qu...