Can a handful of atoms outperform a much larger digital neural network on a real-world task? The answer may be yes. In a ...

Gartner predicted traditional search volume will drop 25% this year as users shift to AI-powered answer engines. Google’s AI Overviews now reach more than 2 billion monthly users, ChatGPT serves 800 ...

Abstract: Metaheuristic algorithms have demonstrated strong effectiveness in solving complex real-world optimization problems. This paper presents two discrete metaheuristic approaches for the ...

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, ...

Determining the least expensive path for a new subway line underneath a metropolis like New York City is a colossal planning challenge—involving thousands of potential routes through hundreds of city ...

In the field of multi-objective evolutionary optimization, prior studies have largely concentrated on the scalability of objective functions, with relatively less emphasis on the scalability of ...

Abstract: To achieve high-precision engineering design and improve the optimization efficiency of beam optical systems, this paper proposes a two-stage optimization method based on intelligent ...

The leading approach to the simplex method, a widely used technique for balancing complex logistical constraints, can’t get any better. In 1939, upon arriving late to his statistics course at the ...

This paper investigates the application of machine learning techniques to optimize complex spray-drying operations in manufacturing environments. Using a mixed-methods approach that combines ...

Researchers at the University of Illinois Urbana-Champaign and the University of Virginia have developed a new model architecture that could lead to more robust AI systems with more powerful reasoning ...