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 ...

Machine learning is reshaping the way portfolios are built, monitored, and adjusted. Investors are no longer limited to ...

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

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 ...

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, ...

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

Discover how a new machine learning method can help scientists predict which MOF structures are good candidates for advanced ...

A new research paper shows the approach performs significantly better than the random-walk forecasting method.