This paper raises the question of collective decision making under possibilistic uncertainty; We study four egalitarian decision rules and show that in the context of a possibilis...
Increased interest in web-based education has spurred the proliferation of online learning environments. However, these platforms suffer from high dropout rates due to lack of su...
Sparse learning has been proven to be a powerful technique in supervised feature selection, which allows to embed feature selection into the classification (or regression) proble...
When scheduling tasks for field-deployable systems, our solutions must be robust to the uncertainty inherent in the real world. Although human intuition is trusted to balance rew...
Module extraction—the task of computing a (preferably small) fragment M of an ontology T that preserves entailments over a signature Σ—has found many applications in recent y...
Ana Armas Romero, Mark Kaminski, Bernardo Cuenca G...