Top Down Induction of Decision Trees (TDIDT) is the most commonly used method of constructing a model from a dataset in the form of classification rules to classify previously unse...
To exploit increased instruction-level parallelism available in modern processors, we describe the formation and optimization of tracenets, an integrated approach to reducing the ...
Alexandre E. Eichenberger, Waleed Meleis, Suman Ma...
The nested data-parallel programming model supports the design and implementation of irregular parallel algorithms. This paper describes work in progress to incorporate nested data...
Brian Blount, Siddhartha Chatterjee, Michael Phili...
With the technology advance and the growth of Internet, the information that can be found in this net, as well as the number of users that access to look for specific data is big...
Recent years have seen growth in the number of algorithms designed to solve challenging simulation-based nonlinear optimization problems. One such algorithm is the Trust-Region Par...