Abstract: This article presents a novel proximal gradient neurodynamic network (PGNN) for solving composite optimization problems (COPs). The proposed PGNN with time-varying coefficients can be ...

Cheng, R. , Liu, J. , Hao, L. and Wu, D. (2026) On the Application of the Infinitesimal Method to Two Categories of Problems in College Physics. Open Journal of Social Sciences, 14, 378-389. doi: ...

When you purchase through links on our site, we may earn an affiliate commission. Here’s how it works. In October 2024, news broke that Facebook parent company Meta had cracked an "impossible" problem ...

We walk through an optimization problem step by step, clearly explaining how to identify variables, set up the correct function, apply derivatives, and find maximum or minimum values. Each step is ...

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 ...

Abstract: Several real-world applications introduce derivativefree optimization problems, called variable dimension problems, where the problem's dimension is not known in advance. Despite their ...

ORLANDO, Florida, Aug 27 (Reuters) - There is legitimate debate about the actual independence of modern-day central banks, but almost everyone agrees that overt politicization of monetary policy – as ...

A line of engineering research seeks to develop computers that can tackle a class of challenges called combinatorial optimization problems. These are common in real-world applications such as ...

KARLSRUHE, Germany and COLLEGE PARK, Md.– Kipu Quantum and IonQ (NYSE: IONQ) announced what they said is a record achievement: the successful solution of “the most complex known protein folding ...

Annealing processors (APs) are gaining popularity for solving complex optimization problems. Fully-coupled Ising model APs are especially valued for their flexibility, but balancing capacity (number ...

It’s been difficult to find important questions that quantum computers can answer faster than classical machines, but a new algorithm appears to do it for some critical optimization tasks. For ...