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As measured against absolutely atrocious backprop baselines in most cases.
Direct feedback alignment for training neural networks: https://arxiv.org/abs/1609.01596 - can train NNs with random projections of the error signal.
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That it works at all is interesting. How well it works is secondary, since this is not meant to be practical...
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is it same complexity as regular back prop?
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