—In this paper, we present an approach to nonlinear model reduction based on representing a nonlinear system with a piecewise-linear system and then reducing each of the pieces w...
This paper proposes a novel hierarchical learning strategy to deal with the data sparseness problem in relation extraction by modeling the commonality among related classes. For e...
Clustering stability is an increasingly popular family of methods for performing model selection in data clustering. The basic idea is that the chosen model should be stable under...
Embedded real-time systems must satisfy not only logical functional requirements but also para-functional properties such as timeliness, Quality of Service (QoS) and reliability. W...
The number of processors embedded on high performance computing platforms is continuously increasing to accommodate user desire to solve larger and more complex problems. However,...
Thara Angskun, George Bosilca, Graham E. Fagg, Jel...