Multi-modal optimization refers to locating not only one optimum but a set of locally optimal solutions. Niching is an important technique to solve multi-modal optimization problem...
This paper proposes selective update and cooperation strategies for parameter estimation in distributed adaptive sensor networks. A setmembership filtering approach is employed t...
Stefan Werner, Yih-Fang Huang, Marcello L. R. de C...
In this paper we discuss multiperiod portfolio selection problems related to a speci…c provisioning problem. Our results are an extension of Dhaene et al. (2005), where optimal ...
Classification in imbalanced domains is a recent challenge in machine learning. We refer to imbalanced classification when data presents many examples from one class and few from ...
When disseminating data involving human subjects, researchers have to weigh in the requirements of privacy of the individuals involved in the data. A model widely used for enhancin...