Nyström Kernel Mean Embeddings

Antoine Chatalic, Nicolas Schreuder, Lorenzo Rosasco, Alessandro Rudi

Abstract: Kernel mean embeddings are a powerful tool to represent probability distributions over arbitrary spaces as single points in a Hilbert space. Yet, the cost of computing and storing such embeddings p...