The use of higher-order local autocorrelations as features for pattern recognition has been acknowledged since many years, but their applicability was restricted to relatively low...
In this paper we focus on high dimensional data sets for which the number of dimensions is an order of magnitude higher than the number of objects. From a classifier design standp...
In this paper, we extend the recently proposed Core Vector Machine algorithm to the regression setting by generalizing the underlying minimum enclosing ball problem. The resultant...
Background. Recent studies have shown that Support Vector Regression (SVR) has an interesting potential in the field of effort estimation. However applying SVR requires to careful...
Anna Corazza, Sergio Di Martino, Filomena Ferrucci...
This paper proposes Twin Vector Machine (TVM), a constant space and sublinear time Support Vector Machine (SVM) algorithm for online learning. TVM achieves its favorable scaling b...