—With the exponential growth in the amount of data that is being generated in recent years, there is a pressing need for applying machine learning algorithms to large data sets. ...
In this research work a large set of the classical numerical functions were taken into account in order to understand both the search capability and the ability to escape from a lo...
Vincenzo Cutello, Giuseppe Nicosia, Mario Pavone, ...
Full-chip thermal monitoring is an important and challenging issue in today’s microprocessor design. In this paper, we propose a new information-theoretic framework to quantitat...
Huapeng Zhou, Xin Li, Chen-Yong Cher, Eren Kursun,...
We generalize the primal-dual hybrid gradient (PDHG) algorithm proposed by Zhu and Chan in [M. Zhu, and T. F. Chan, An Efficient Primal-Dual Hybrid Gradient Algorithm for Total Var...
We introduce a generic framework for the distributed execution of combinatorial optimization tasks. Instead of relying on custom hardware (like dedicated parallel machines or clus...