Many techniques for association rule mining and feature selection require a suitable metric to capture the dependencies among variables in a data set. For example, metrics such as...
We use unsupervised probabilistic machine learning ideas to try to explain the kinds of learning observed in real neurons, the goal being to connect abstract principles of self-or...
Abstract—Customization of systems is costly, but it is necessary to better meet the needs of multi-various tasks and requirements in the fields such as medical care, education, ...
Sensitivity Analysis (SA) is a novel compiler technique that complements, and integrates with, static automatic parallelization analysis for the cases when relevant program behavi...
Silvius Rus, Maikel Pennings, Lawrence Rauchwerger
Abstract. The emergence of computing environments where smart devices are embedded pervasively in the physical world has made possible many interesting applications and has trigger...