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NoProp: Training neural networks without back-propagation or forward-propagation

(arxiv.org)
161 points belleville | 1 comments | 14 Apr 25 00:03 UTC | HN request time: 0s | source
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DrFalkyn ◴[14 Apr 25 05:27 UTC] No.43678328[source]▶
If we could ever figure out what wet brains actually do (continuous feedback, ? enzyme release ? ) this might be possible
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friendzis ◴[14 Apr 25 11:04 UTC] No.43680009[source]▶
We know quite a lot. For example, we know that brains have various different nueromodulatory pathways. Take for example dopamine reward mechanism that is being talked about more openly these day. Dopamine is literally secreted by various different parts of the brain and affect different pathways.

I don't think it is anywhere feasible to emulate anything resembling this in a computational neural network with fixed input and output neurons.

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1. idiotsecant ◴[14 Apr 25 12:27 UTC] No.43680560[source]▶
Aren't we already emulating it? It's sort of a distributed and overlaid reward function, which we just undistributed