The class imbalance problem (when one of the classes has much less samples than the others) is of great importance in machine learning, because it corresponds to many critical app...
Adaptation and personalization services of the information offered to the users in open e-learning environments are considered to be the turning point of recent research efforts. ...
Recent development of location technologies enables us to obtain the location history of users. This paper proposes a new method to infer users’ longterm properties from their r...
Co-training is a semi-supervised technique that allows classifiers to learn with fewer labelled documents by taking advantage of the more abundant unclassified documents. However, ...
We present a learning framework for structured support vector models in which boosting and bagging methods are used to construct ensemble models. We also propose a selection metho...