Bridging deep and kernel methods

Abstract

There has been some exciting major progress in recent years in data analysis methods, including a variety of deep learning architectures, as well as further advances in kernel-based learning methods, which have demonstrated predictive superiority. In this paper we provide a brief motivated survey of recent proposals to explicitly or implicitly combine kernel methods with the notion of deep learning networks.