Compressed Imaging is the theory that studies the problem of image recovery from an under-determined system of linear measurements. One of the most popular methods in this field i...
Serge L. Shishkin, Hongcheng Wang, Gregory S. Hage...
Thermal hot spots and temperature gradients on the die need to be minimized to manufacture reliable systems while meeting energy and performance constraints. In this work, we solve...
Abstract— Today’s embedded systems are typically distributed and more often confronted with timevarying demands. Existing methodologies that optimize the partitioning of comput...
In the last 15 years periodic timetable problems have found much interest in the combinatorial optimization community. We will focus on the optimisation task to minimise a weighted...
Abstract. Accurate selectivity estimations are essential for query optimization decisions where they are typically derived from various kinds of histograms which condense value dis...