The kernel embedding of distributions comprises a class of nonparametric methods in which a probability distribution is represented as an element of a reproducing kernel Hilbert space A. Smola, A. Gretton, L. Song, B. Schölkopf.
The kernel embedding of distributions comprises a class of nonparametric methods in which a probability distribution is represented as an element of a reproducing kernel Hilbert space. For example, numerous kernels have been proposed for the following spaces: vector spaces, strings, A. Smola, A. Gretton, L. Song, B. Schölkopf.