In this paper we present a novel framework for evolving ART-based classification models, which we refer to as MOME-ART. The new training framework aims to evolve populations of ART...
Rong Li, Timothy R. Mersch, Oriana X. Wen, Assem K...
The use of Bayesian networks for classification problems has received significant recent attention. Although computationally efficient, the standard maximum likelihood learning me...
As network attacks have increased in number and severity over the past few years, intrusion detection system (IDS) is increasingly becoming a critical component to secure the netwo...
: The software industry is faced with the fast growing complexity of IT infrastructures. This makes manual administration increasingly difficult and appears to be the limiting fact...
In this paper we present a unsupervised learning based approach for sub-pixel motion estimation. The novelty of this work is the learning based method itself which tries to learn ...
Mithun Das Gupta, Nemanja Petrovic, ShyamSundar Ra...