Vishwanathan, S; Smola, Alexander; Vidal, Rene
We propose a family of kernels based on the Binet-Cauchy theorem, and its extension to Fredholm operators. Our derivation provides a unifying framework for all kernels on dynamical systems currently used in machine learning, including kernels derived from the behavioral framework, diffusion processes, marginalized kernels, kernels on graphs, and the kernels on sets arising from the subspace angle approach. In the case of linear time-invariant systems, we derive explicit formulae for computing...[Show more]
Items in Open Research are protected by copyright, with all rights reserved, unless otherwise indicated.