In this paper we propose a novel method for demographic classification and present an image retrieval system that can retrieve facial images by demographic information that includ...
Truly ubiquitous computing poses new and significant challenges. A huge number of heterogeneous devices will interact to perform complex distributed tasks. One of the key aspects...
Nicola Bicocchi, Marco Mamei, Andrea Prati, Rita C...
Statistical learning theory chiefly studies restricted hypothesis classes, particularly those with finite Vapnik-Chervonenkis (VC) dimension. The fundamental quantity of interest i...
In machine learning, ensemble classifiers have been introduced for more accurate pattern classification than single classifiers. We propose a new ensemble learning method that emp...
The aim of this paper is to compare Bayesian network classifiers to the k-NN classifier based on a subset of features. This subset is established by means of sequential feature se...