Modularizing Deep Learning via Pairwise Learning With Kernels

Shiyu Duan, Shujian Yu, Jose Principe

By redefining the conventional notions of layers, we present an alternative view on finitely wide, fully trainable deep neural networks as stacked linear models in feature spaces,…