Learning from imbalanced datasets presents a convoluted problem both from the modeling and cost standpoints. In particular, when a class is of great interest but occurs relatively...
Nitesh V. Chawla, David A. Cieslak, Lawrence O. Ha...
The contribution of this paper is to compare paradigms coming from the classes of parametric, and non-parametric techniques to solve the decision fusion problem encountered in the...
— Metaheuristics such as Estimation of Distribution Algorithms and the Cross-Entropy method use probabilistic modelling and inference to generate candidate solutions in optimizat...
Marcus Gallagher, Ian Wood, Jonathan M. Keith, Geo...
The volume of spam e-mails has grown rapidly in the last two years resulting in increasing costs to users, network operators, and e-mail service providers (ESPs). E-mail users dem...
—In this paper, we present a distributed algorithm to dynamically allocate the available resources of a service-oriented network to delay sensitive network services. We use a uti...
Michael G. Kallitsis, Robert D. Callaway, Michael ...