We present a framework for the reduction of dimensionality of a data set via manifold learning. Using the building blocks of local hyperplanes we show how a global manifold can be...
Fault injections constitute a major threat to the security of embedded systems. The errors in the cryptographic algorithms have been shown to be extremely dangerous, since powerful...
The ability of Compressive Sensing (CS) to recover sparse signals from limited measurements has been recently exploited in computational imaging to acquire high-speed periodic and...
M. Salman Asif, Dikpal Reddy, Petros Boufounos, As...
Detailed knowledge about implemented concerns in the source code is crucial for the cost-effective maintenance and successful evolution of large systems. Concern mining techniques...
Many high-performance tools, applications and infrastructures, such as Paradyn, STAT, TAU, Ganglia, SuperMon, Astrolabe, Borealis, and MRNet, use data aggregation to synthesize lar...