Revisiting Locally Supervised Learning: an Alternative to End-to-end Training

Yulin Wang, Zanlin Ni, Shiji Song +2

Due to the need to store the intermediate activations for back-propagation, end-to-end (E2E) training of deep networks usually suffers from high GPUs memory footprint. This paper a…