This paper proposes a technique for identifying program properties that indicate errors. The technique generates machine learning models of program properties known to result from...
When using machine learning for in silico modeling, the goal is normally to obtain highly accurate predictive models. Often, however, models should also bring insights into intere...
Before applying learning algorithms to datasets, practitioners often globally discretize any numeric attributes. If the algorithm cannot handle numeric attributes directly, prior ...
— Previous works studied the effect of many system parameters on spectrum sharing opportunities where secondary users access the spectrum of primary users. However, a parameter t...
With smart-phones becoming increasingly commonplace, there has been a subsequent surge in applications that continuously track the location of users. However, serious privacy conc...