A method is introduced to learn and represent similarity with linear operators in kernel induced Hilbert spaces. Transferring error bounds for vector valued large-margin classifie...
We investigate the problem of learning optimal descriptors for a given classification task. Many hand-crafted descriptors have been proposed in the literature for measuring visua...
Clustering algorithms are a useful tool to explore data structures and have been employed in many disciplines. The focus of this paper is the partitioning clustering problem with ...
Maurizio Filippone, Francesco Camastra, Francesco ...
Abstract. We present a generic framework for the automatic and modular inference of sound class invariants for class-based object oriented languages. The idea is to derive a sound ...
Abstract. In this paper a novel framework for brain classification is proposed in the context of mental health research. A learning by example method is introduced by combining loc...
Umberto Castellani, E. Rossato, Vittorio Murino, M...