Abstract Dino Ienco and Rosa Meo Dipartimento di Informatica, Universit`a di Torino, Italy In this paper we propose and test the use of hierarchical clustering for feature selectio...
Recent advances in Multiple Kernel Learning (MKL) have positioned it as an attractive tool for tackling many supervised learning tasks. The development of efficient gradient desce...
Within the taxonomy of feature extraction methods, recently the Wrapper approaches lost some popularity due to the associated computational burden, compared to Embedded or Filter m...
Erik Schaffernicht, Volker Stephan, Horst-Michael ...
In this letter, we propose a clustering model that efficiently mitigates image and video under/over-segmentation by combining generalized Gaussian mixture modeling and feature sele...
A novel approach to combining clustering and feature selection is presented. It implements a wrapper strategy for feature selection, in the sense that the features are directly se...