Deep learning has been successfully applied to perform non-linear embedding. In this paper, we present supervised embedding techniques that use a deep network to collapse classes....
Martin Renqiang Min, Laurens van der Maaten, Zinen...
In this paper, we analyze restrictions of traditional communication performance models affecting the accuracy of analytical prediction of the execution time of collective communic...
Alexey L. Lastovetsky, Vladimir Rychkov, Maureen O...
Embedded processors have become increasingly complex, resulting in variable execution behavior and reduced timing predictability. On such processors, safe timing specifications e...
Jin Ouyang, Raghuveer Raghavendra, Sibin Mohan, Ta...
Key challenges in distributed real-time embedded (DRE) system developments include safe composition of system components and mapping the functional specifications onto the target...
Flash memory has become virtually indispensable in most mobile devices. In order for mobile devices to successfully provide services to users, it is essential that flash memory b...