The microarchitectural design space of a new processor is too large for an architect to evaluate in its entirety. Even with the use of statistical simulation, evaluation of a sing...
Christophe Dubach, Timothy M. Jones, Michael F. P....
We developed a machine learning system for determining gene functions from heterogeneous sources of data sets using a Weighted Naive Bayesian Network (WNB). The knowledge of gene ...
Energy-efficient microprocessor designs are one of the major concerns in both high performance and embedded processor domains. Furthermore, as process technology advances toward d...
The Support Vector Machine (SVM) of Vapnik [9] has become widely established as one of the leading approaches to pattern recognition and machine learning. It expresses predictions...
Background: The identification of groups of co-regulated genes and their transcription factors, called transcriptional modules, has been a focus of many studies about biological s...
Ho-Joon Lee, Thomas Manke, Ricardo Bringas, Martin...