We introduce a method of feature selection for Support Vector Machines. The method is based upon finding those features which minimize bounds on the leave-one-out error. This sear...
Jason Weston, Sayan Mukherjee, Olivier Chapelle, M...
This paper uses Support Vector Machines (SVM) to fuse multiple classifiers for an offline signature system. From the signature images, global and local features are extracted and ...
This paper investigates statistical performances of Support Vector Machines (SVM) and considers the problem of adaptation to the margin parameter and to complexity. In particular ...
In an attempt to overcome problems associated with articulatory limitations and generative models, this work considers the use of phonological features in discriminative models fo...
In this work is presented a novel approach for the classification of audio concepts in broadcast soccer videos using deep belief network (DBN), a probabilistic neural network with...
Lamberto Ballan, Alessio Bazzica, Marco Bertini, A...