The kernel regularized least squares (KRLS) method uses the kernel trick to perform non-linear regression estimation. Its performance depends on proper selection of both a kernel function and a regularization parameter. ...

The modeling of real-world problems as graphs along with the problem of non-linear distributions comes up with the idea of applying kernel functions in feature spaces. Roughly speaking, the idea is to seek for well-behaved ...

Research in modern data-driven dynamical systems is typically focused on the three key challenges of high dimensionality, unknown dynamics and nonlinearity. The dynamic mode decomposition (DMD) has emerged as a cornerstone ...