Most work on preference learning has focused on pairwise preferences or rankings over individual items. In this paper, we present a method for learning preferences over sets of it...
Abstract. There has been growing interest in practice in using unlabeled data together with labeled data in machine learning, and a number of different approaches have been develo...
In this paper, we present our research results about a UML-based modeling language dedicated to Problem-Based Learning design. The CPM (Cooperative Problem-Based learning Metamode...
We study Vector Addition Systems with States (VASS) extended in such a way that one of the manipulated integer variables can be tested to zero. For this class of system, it has bee...
We recapitulate regular one-shot learning from membership and equivalence queries, positive and negative finite data. We present a meta-algorithm that generalizes over as many sett...