In text management tasks, the dimensionality reduction becomes necessary to computation and interpretability of the results generated by machine learning algorithms. This paper de...
Kernel methods have been applied successfully in many data mining tasks. Subspace kernel learning was recently proposed to discover an effective low-dimensional subspace of a kern...
Jianhui Chen, Shuiwang Ji, Betul Ceran, Qi Li, Min...
This paper shows that a detailed, although non-emotional, description of event or an action can be a reliable source for learning opinions. Empirical results show the practical uti...
—In this paper, we study how a humanoid robot can learn affordance relations in his environment through its own interactions in an unsupervised way. Specifically, we developed a...
Baris Akgun, Nilgun Dag, Tahir Bilal, Ilkay Atil, ...
Abstract. The paper proposes a learning approach to support medical researchers in the context of in-vivo cancer imaging, and specifically in the analysis of Dynamic Contrast-Enhan...
Alessandro Daducci, Umberto Castellani, Marco Cris...