This paper develops a scalable online optimization framework for the autonomic performance management of distributed computing systems operating in a dynamic environment to satisf...
Gaussian mixture models (GMMs) are a convenient and essential tool for the estimation of probability density functions. Although GMMs are used in many research domains from image ...
This paper examines the use of a hierarchical coevolutionary genetic algorithm under different partnering strategies. Cascading clusters of sub-populations are built from the bott...
Text representation is a central task for any approach to automatic learning from texts. It requires a format which allows to interrelate texts even if they do not share content w...
—Motivated by the fact that most of the existing QoS service composition solutions have limited scalability, we develop a hierarchical-based solution framework to achieve scalabi...
Jingwen Jin, Jin Liang, Jingyi Jin, Klara Nahrsted...