Knowledge-based planning methods offer benefits over classical techniques, but they are time consuming and costly to construct. There has been research on learning plan knowledge ...
In this paper, we review the paradigm of inductive process modeling, which uses background knowledge about possible component processes to construct quantitative models of dynamic...
Will Bridewell, Narges Bani Asadi, Pat Langley, Lj...
This paper discusses issues related to Bayesian network model learning for unbalanced binary classification tasks. In general, the primary focus of current research on Bayesian ne...
Efforts for software evolution supersede any other part of the software life cycle. Technological decisions have a major impact on the maintainability, but are not well reflected ...
While we have previously reported on multiscale segmentation of single-figure anatomic objects from medical images by deformable m-rep models, here we report on a method of segmen...
P. Thomas Fletcher, Stephen M. Pizer, A. Graham Ga...