Research in Hilbert space operators and Berezin numbers constitutes a fertile arena in modern mathematical analysis, bridging abstract operator theory with practical applications in spectral theory ...

For an arbitrary Hilbert space 𝓔, the Segal–Bargmann space 𝓗(𝓔) is the reproducing kernel Hilbert space associated with the kernel K(x, y) = exp(〈x, y〉) for x, y in 𝓔. If φ : 𝓔₁ → 𝓔₂ is a ...

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 ...