BACKGROUND: Defect predictors learned from static code measures can isolate code modules with a higher than usual probability of defects. AIMS: To improve those learners by focusi...
In this paper we consider the following scenario. A set of n jobs with different threads is being run concurrently. Each job has an associated weight, which gives the proportion ...
Micah Adler, Petra Berenbrink, Tom Friedetzky, Les...
One aim of Meta-learning techniques is to minimize the time needed for problem solving, and the effort of parameter hand-tuning, by automating algorithm selection. The predictive m...
Powering down SDRAMs at run-time reduces memory energy consumption significantly, but often at the cost of performance. If employed speculatively with real-time memory controller...
Classification fusion combines multiple classifications of data into a single classification solution of greater accuracy. Feature extraction aims to reduce the computational cost ...
Behrouz Minaei-Bidgoli, Gerd Kortemeyer, William F...