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 ...
Overview: Master deep learning with these 10 essential books blending math, code, and real-world AI applications for lasting ...
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, ...
The built environment faces increasing pressures from climate change, resource limitations, and rapid urbanisation.
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 ...
Scientific knowledge advances through the interplay of empiricism and theory. Empirical observations of environmental ...
Background Annually, 4% of the global population undergoes non-cardiac surgery, with 30% of those patients having at least ...
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