Kernel methods represent a cornerstone in modern machine learning, enabling algorithms to efficiently derive non-linear patterns by implicitly mapping data into high‐dimensional feature spaces. At the ...

Jessica Lin and Zhenqi (Pete) Shi from Genentech describe a novel machine learning approach to predicting retention times for ...

As data privacy collides with AI’s rapid expansion, the Berkeley-trained technologist explains how a new generation of models ...

MIT researchers have developed a method that generates more accurate uncertainty measures for certain types of estimation.

AI (Artificial Intelligence) is a broad concept and its goal is to create intelligent systems whereas Machine Learning is a ...

A scientist in Sweden has developed a new hybrid local features-based method using thermographs to identify faulty solar panels. A researcher from Sweden’s Jönköping University has proposed a machine ...

Harvard University presents its eight-week online course through edX, which imparts to students essential knowledge of ...

This study leverages advanced genomics and machine learning to refine the understanding of key fruit quality traits in ...

No audio available for this content. High-precision GNSS applications, such as real-time displacement monitoring and vehicle navigation, rely heavily on resolving carrier-phase ambiguities. However, ...

Jordan Awan receives funding from the National Science Foundation and the National Institute of Health. He also serves as a privacy consultant for the federal non-profit, MITRE. In statistics and ...

Experts are increasingly turning to machine learning to predict antibiotic resistance in pathogens. With its help, resistance ...