Meta-learning is an efficient approach in the field of machine learning, which involves multiple classifiers. In this paper, a meta-learning framework consisting of stacking meta-...
This paper analyzes the potential advantages and theoretical challenges of “active learning” algorithms. Active learning involves sequential sampling procedures that use infor...
Online learning and kernel learning are two active research topics in machine learning. Although each of them has been studied extensively, there is a limited effort in addressing ...
This paper presents how a new teaching method in the way that a queuing theory and systems modeling or simulation course can be done, was evaluated by the teachers and the student...
Athanasios Perdos, Alexander Chatzigeorgiou, Georg...
Abstract. This paper presents a strategy of dynamic user modeling for sketchbased user interface. A user model is defined as an incremental decision tree for a specific user. A dra...