Abstract. Greedy machine learning algorithms suffer from shortsightedness, potentially returning suboptimal models due to limited exploration of the search space. Greedy search mis...
Abstract. We have developed a learning platform to simplify and improve teaching and practice of Computer Graphics for beginners and advanced students. Our goal is to offer a set o...
Abstract. In a recent work we have carried out CarpeDiem, a novel algorithm for the fast evaluation of Supervised Sequential Learning (SSL) classifiers. In this paper we point out...
Abstract. Virtual training systems are increasingly used for the training of complex, dynamic tasks. To give trainees the opportunity to train autonomously, intelligent agents are ...
Abstract. This paper explores how to predict query difficulty for contextual image retrieval. We reformulate the problem as the task of predicting how difficult to represent a quer...