A novel method for estimating prediction uncertainty using machine learning techniques is presented. Uncertainty is expressed in the form of the two quantiles (constituting the pr...
We present predictive performance models of two of the petascale applications, S3D and GTC, from the DOE Office of Science workload. We outline the development of these models and...
We provide a novel view of learning an approximate model of a partially observable environment from data and present a simple implemenf the idea. The learned model abstracts away ...
The analysis phase constitutes an essential step in the development of information systems. Nevertheless, learning materials design activities currently have reduced the analysis ...
State-of-the-art Machine Translation (MT) systems are still far from being perfect. An alternative is the so-called Interactive Machine Translation (IMT) framework. In this framew...