This paper presents multi-conditional learning (MCL), a training criterion based on a product of multiple conditional likelihoods. When combining the traditional conditional proba...
Andrew McCallum, Chris Pal, Gregory Druck, Xuerui ...
Abstract. Boosting methods are known to improve generalization performances of learning algorithms reducing both bias and variance or enlarging the margin of the resulting multi-cl...
Francesco Masulli, Matteo Pardo, Giorgio Sbervegli...
In this paper we provide a study about crime scenes and its features used in criminal investigations. We argue that the crime scene provides a large set of features that can be us...
Ricardo O. Abu Hana, Cinthia Obladen de Almendra F...
In this paper, we propose a new context-sensitive Bayesian learning algorithm. By modeling the distributions of data locations by a mixture of Gaussians, the new algorithm can uti...
A new scheme that classifies the Internet traffic according to their application types for scalable QoS provision is proposed in this work. The traditional port-based classific...