Missing data caused by boundary specification has a detrimental effect on the analysis of network structures, and designing optimal sampling methods is crucial for conducting network investigations.

Quantum annealing (QA) has the potential to significantly improve solution quality and reduce time complexity in solving combinatorial optimization problems compared to classical optimization methods.

Research paper by Bjørnar Luteberget and Giorgio Sartor wins 2024 FICO® Xpress Best Paper Award; the algorithm is now in FICO® Xpress Solver “When solving a very large computational problem, ...

The rise of AI, graphic processing, combinatorial optimization and other data-intensive applications has resulted in data-processing bottlenecks, as ever greater amounts of data must be shuttled back ...

A quantum computer can solve optimization problems faster than classical supercomputers, a process known as "quantum advantage" and demonstrated by a USC researcher in a paper recently published in ...