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...
Scoring sentences in documents given abstract summaries created by humans is important in extractive multi-document summarization. In this paper, we formulate extractive summariza...