Gaussian processes (GPs) have attracted considerable attention in assisting evolutionary algorithms (EAs) to solve computationally expensive optimization problems (EOPs) because they can directly ...

An artificial-intelligence algorithm that discovers its own way to learn achieves state-of-the-art performance, including on some tasks it had never encountered before. Joel Lehman is at Lila Sciences ...

On a scorching July afternoon in Shanghai, dozens of Chinese students hunch over tablet screens, engrossed in English, math and physics lessons. Algorithms track every keystroke, and the seconds spent ...

ABSTRACT: Lung cancer stands as the preeminent cause of cancer-related mortality globally. Prompt and precise diagnosis, coupled with effective treatment, is imperative to reduce the fatality rates ...

ABSTRACT: Egg loss is one of the major problems in the egg hatching industry. This study aims to support farmers in optimizing their egg hatch through the development of a prediction model. This is to ...

What would you like to Propose? I propose adding flowcharts for selected algorithms to make it easier for beginners to understand the logic visually. Flowcharts will complement the existing code ...

Patent applications on artificial intelligence and machine learning have soared in recent years, yet legal guidance on the patentability of AI and machine learning algorithms remains scarce. The US ...

When it comes to teaching math, a debate has persisted for decades: How, and to what degree, should algorithms be a focus of learning math? The step-by-step procedures are among the most debated ...

SAVANA uses a machine learning algorithm to identify cancer-specific structural variations and copy number aberrations in long-read DNA sequencing data. The complex structure of cancer genomes means ...

Discovering faster algorithms for matrix multiplication remains a key pursuit in computer science and numerical linear algebra. Since the pioneering contributions of Strassen and Winograd in the late ...