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stat.ML updates on arXiv.org

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Are skip connections necessary for biologically plausible learning rules?
Daniel Jiwoong Im, Rutuja Patil, Kristin Branson · 2019-12-05 · via stat.ML updates on arXiv.org

Backpropagation is the workhorse of deep learning, however, several other biologically-motivated learning rules have been introduced, such as random feedback alignment and difference target propagation. None of these methods have produced a competitive performance against backpropagation. In this paper, we show that biologically-motivated learning rules with skip connections between intermediate layers can perform as well as backpropagation on the MNIST dataset and are robust to various sets of hyper-parameters.

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