In many real world applications, active selection of training examples can significantly reduce the number of labelled training examples to learn a classification function. Differ...
This paper presents my participation to the second Morpho Challenge. Results have been obtained with the algorithm already presented at Morpho Challenge 2005. The system takes a p...
We consider the problem of learning a record matching package (classifier) in an active learning setting. In active learning, the learning algorithm picks the set of examples to ...
Multiple-instance learning is a variation on supervised learning, where the task is to learn a concept given positive and negative bags of instances. Each bag may contain many ins...
Traditional spectral classification has been proved to be effective in dealing with both labeled and unlabeled data when these data are from the same domain. In many real world ap...