MiS Preprint Repository

A central component of the analysis of panel clustering techniques forthe approximation of integral operators is the so-called $\eta$-admissibility condition $$min\{diam(\tau ),diam(\sigma )\}\le 2\eta dist(\tau ,\sigma )$$ that ensures that the kernel function is approximated only on those parts of the domain that are far from the singularity.

Typical techniques based on a Taylor expansion of the kernel function require the distance of such a subdomain to be "far enough" from the singularity such that the parameter $\eta$ has to be smaller than a given constant depending on properties of the kernel function.

In this paper, we demonstrate that any $\eta$ is sufficient if interpolation instead of Taylor expansion is used for the kernel approximation, which paves the way for grey-box panel clustering algorithms.