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 ...

Researchers have successfully demonstrated quantum speedup in kernel-based machine learning. When you purchase through links on our site, we may earn an affiliate commission. Here’s how it works.

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

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, ...

Objective This study reviewed the current state of machine learning (ML) research for the prediction of sports-related injuries. It aimed to chart the various approaches used and assess their efficacy ...

Gas sensing material screening faces challenges due to costly trial-and-error methods and the complexity of multi-parameter ...