This paper provides algorithms that use an information-theoretic analysis to learn Bayesian network structures from data. Based on our three-phase learning framework, we develop e...
Jie Cheng, Russell Greiner, Jonathan Kelly, David ...
Mesh generation is a critical step in high fidelity computational simulations. High-quality and high-density meshes are required to accurately capture the complex physical phenome...
Yasushi Ito, Alan M. Shih, Anil K. Erukala, Bharat...
Accurate knowledge of the effect of parameter uncertainty on process design and operation is essential for optimal and feasible operation of a process plant. Existing approaches de...
The emerging standards for the specification of Web Services support the publication of the static interfaces of the operations they may execute. However, little attention is paid...
Despite the advances reached along the last 20 years, anomaly detection in network behavior is still an immature technology, and the shortage of commercial tools thus corroborates...