Learning deep kernels in the space of monotone conjunctive polynomials

Ivano Lauriola, Mirko Polato, Fabio Aiolli

Abstract: Highlights•The monotone Conjunctive Polynomial feature space is here presented.•Homogeneous polynomial kernels can be decomposed as a combination of monotone conjunctive kernels.•The optimal monotone Conjunctive Polynomial kernel can be learned via Multiple Kernel Learning.•The proposed approach proved to be robust to overfitting.•The monotone Conjunctive Polynomial kernel has a deep structure.