no code implementations • 1 Jan 2021 • Matthew Bailey Webster, Jonghyun Choi, changwook Ahn
We propose to learn the backward weight matrices in DFA, adopting the methodology of Kolen-Pollack learning, to improve training and inference accuracy in deep convolutional neural networks by updating the direct feedback connections such that they come to estimate the forward path.
Ranked #177 on Image Classification on CIFAR-100