Multi-scale kernels for Nyström based extension schemes

In this work we propose multi-scale kernels, which are constructed as combinations of Gaussian kernels, to be used for kernel-based extension schemes. We review the kernels' spectral properties and show that their first few modes capture more information compared to the standard Gaussian kernel. Their application is demonstrated on a synthetic data-set and also applied to a real-life example that models daily electricity profiles and predicts the average day-ahead behavior.