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Learning the Connections in Direct Feedback Alignment
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
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