Genomic surveillance—the process of monitoring and sequencing pathogens—is one of the most important tools for detecting ...

XL, dynamic interest modeling, and distributed stream computing to analyze large-scale e-commerce user behavior. By improving long-sequence prediction, real-time processing, and behavioral clustering, ...

Understanding how firms build their capabilities, such as managerial skills, technology adoption and innovation capacity, is ...

Few people have invented an algorithm with the potential to spark a worldwide crisis, so why is quantum computing pioneer ...

Researchers at Russia's FEFU and China unveil a new algorithm to enhance earthquake forecasting accuracy using less computing ...

New Iterative Block Particle Filter algorithm makes genomic surveillance faster, cheaper and more scalable, improving early ...

Huawei's HZU Algorithm Aims for 90:1 Compression in New OceanProtect Backup Systems ...

Abstract: As one type of efficient unsupervised learning methods, clustering algorithms have been widely used in data mining and knowledge discovery with noticeable advantages. However, clustering ...

Abstract: Feature selection is a technique commonly used in Data Mining and Machine Learning. Traditional feature selection methods, when applied to large datasets, generate a large number of feature ...

A deep-learning algorithm applied to 15 years of seismic recordings beneath Yellowstone has identified 86,276 earthquakes ...

Single-cell RNA-seq AI analysis has become the default way to make sense of the millions of expression measurements a single experiment can now generate. Turning raw sequencing counts into ...