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 ...
Join our daily and weekly newsletters for the latest updates and exclusive content on industry-leading AI coverage. Learn More It’s widely known that quantum computers are well suited for solving ...
where \(\mathsf{G}(\cdot)\) is some convex operator and \(\mathcal{F}\) is as set of feasible input distributions. Examples of such an optimization problem include finding capacity in information ...
LONDON--(BUSINESS WIRE)--SpendEdge, a leading provider of supply chain optimization solutions, has announced the completion of the latest presentation on the top supply chain optimization problems ...
Conventional quantum algorithms are not feasible for solving combinatorial optimization problems (COPs) with constraints in the operation time of quantum computers. To address this issue, researchers ...
This paper deals with the packing problem of circles and non-convex polygons, which can be both translated and rotated into a strip with prohibited regions. Using the Ф-function technique, a ...
Profile-guided optimization, introduced as a preview in Go 1.20 in February, graduates from preview status in the new version. PGO enables the compiler toolchain to do workload-specific and ...
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