In this paper we describe an online/incremental linear binary classifier based on an interesting approach to estimate the Fisher subspace. The proposed method allows to deal with ...
Alessandro Rozza, Gabriele Lombardi, Marco Rosa, E...
Associative classification is a rule-based approach to classify data relying on association rule mining by discovering associations between a set of features and a class label. Su...
The newly emerging field of Network Science deals with the tasks of modelling, comparing and summarizing large data sets that describe complex interactions. Because pairwise affin...
The idea behind Aspect-Oriented Modeling (AOM) is to apply aspect-oriented techniques to (software) models with the aim of modularizing crosscutting concerns. This can be done with...
We present a scalable medium bit-rate wide-band audio coding technique based on frequency domain linear prediction (FDLP). FDLP is an efficient method for representing the long-ter...