The large amount of information now available on the Web can play a prominent role in building a cooperative intelligent distance learning environment. We propose a system to prov...
Mohammed Abdel Razek, Claude Frasson, Marc Kaltenb...
Recently, there has been increasing interest in the issues of cost-sensitive learning and decision making in a variety of applications of data mining. A number of approaches have ...
We present a probabilistic model-based framework for distributed learning that takes into account privacy restrictions and is applicable to scenarios where the different sites ha...
Abstract. Multiple-instance learning (MIL) allows for training classifiers from ambiguously labeled data. In computer vision, this learning paradigm has been recently used in many ...
The paper introduces a new framework for feature learning in classification motivated by information theory. We first systematically study the information structure and present a n...