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 ...

Review re-maps multi-view learning into four supervised scenarios and three granular sub-tiers, delivering the first unified ...

Scientific knowledge advances through the interplay of empiricism and theory. Empirical observations of environmental ...

Researchers from Peking University have conducted a comprehensive systematic review on the integration of machine learning into statistical methods for disease risk prediction models, shedding light ...

On October 3-4, 2025,The Federal Reserve Bank of Philadelphia and the Center for Applied AI at the University of Chicago Booth School of Business are co-hosting a conference on Frontiers in Machine ...

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 ...

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 ...

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, ...

Artificial intelligence is no longer a future idea. It is already part of daily life. Students use it when they search online ...

Researchers are applying artificial intelligence and other techniques in the quest to forecast quakes in time to help people find safety. In September 2017, about two minutes before a magnitude 8.2 ...