In this paper, we focus on the adaptation problem that has a large labeled data in the source domain and a large but unlabeled data in the target domain. Our aim is to learn relia...
Learning styles, as well as the best ways of responding with corresponding instructional strategies, have been intensively studied in the classical educational (classroom) setting...
The focus of my thesis is on the development of a multi-method framework for the validation of formal models (domain model, user model, and teaching model) for adaptive work-integr...
A number of algorithms have been proposed aimed at tackling the problem of learning "Gene Linkage" within the context of genetic optimisation, that is to say, the problem...
In this paper, we consider the multi-task sparse learning problem under the assumption that the dimensionality diverges with the sample size. The traditional l1/l2 multi-task lass...
Xi Chen, Jingrui He, Rick Lawrence, Jaime G. Carbo...