In this paper, we introduce a domain-independent classification framework based on both k-nearest neighbor and Naïve Bayesian classification algorithms. The architecture of our s...
Abstract. Outlier detection has been used for centuries to detect and, where appropriate, remove anomalous observations from data. Outliers arise due to mechanical faults, changes ...
Abstract. This paper proposes a global escape mechanism which can handle unexpected or unwanted conditions changing the default execution of distributed communicational flows, pres...
Two distinct learning mechanisms are considered for a population of agents who engage in decentralized search for the common optimum. An agent may choose to learn via innovation (...
As cloud computing environments become explosively popular, dealing with unpredictable changes, uncertainties, and disturbances in both systems and environments turns out to be on...