Imagine trying to design a key for a lock that is constantly changing its shape. That is the exact challenge we face in ...
Quantum computers—devices that process information using quantum mechanical effects—have long been expected to outperform ...
Low-rank data analysis has emerged as a powerful paradigm across applied mathematics, statistics, and data science. With the rapid growth of modern datasets in size, dimensionality, and complexity, ...
Long sales cycles, low conversion volume, and multi-stage purchase journeys make measurement and attribution harder, creating real obstacles to campaign optimization. For B2Bs and brands selling ...
Researchers at Google Cloud and UCLA have proposed a new reinforcement learning framework that significantly improves the ability of language models to learn very challenging multi-step reasoning ...
Ising machines demonstrate significant potential to tackle computationally complex challenges, including combinatorial optimization problems related to logistics, manufacturing, finance, and AI. The ...
Aqarios' platform Luna v1.0 marks a major milestone in quantum optimization. This release significantly improves usability, performance, and real-world applicability by introducing FlexQAOA, a hybrid ...
A new algorithm helps topology optimizers skip unnecessary iterations, making optimization and design faster, more stable and more useful. PROVIDENCE, R.I. [Brown University] — With the rise of 3D ...
Abstract: This paper introduces a new discrete StarFish Optimization Algorithm (D-SFOA) to solve a complex discrete Symmetric Travelling Salesman Problem (STSP). The discrete SFOA algorithm is ...
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