This paper studies efficient learning with respect to mind changes. Our starting point is the idea that a learner that is efficient with respect to mind changes minimizes mind cha...
Supervised learning is difficult with high dimensional input spaces and very small training sets, but accurate classification may be possible if the data lie on a low-dimensional ...
Ad-hoc sensor networks provide a cheap and scalable technology for constructing pervasive learning assessment systems that are embedded in physical environments. This paper propos...
Imran A. Zualkernan, Ahmed Wasfy, Imad Zabalawi, M...
Since the approval of IEEE LOM Draft Standard and the advance of network-driven learning technology, a large number of resource database constructors, content developers and learn...
While most theoretical work in machine learning has focused on the complexity of learning, recently there has been increasing interest in formally studying the complexity of teach...