Sparse Spectrum Warped Input Measures for Nonstationary Kernel Learning Anthony Tompkins 1, Rafael Oliveira 1, 2, Fabio Ramos 1,3 1 School of Computer Science, the University of Sydney, Australia 2

Simpler phenomena that do not exhibit such variation may be called stationary . The typical kernel based learner canonically relies on a stationary kernel function, a measure of "similarity", to define the prior beliefs over the function space.