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Learning Without Feedback: Fixed Random Learning Signals Allow for Feedforward Training of Deep Neural Networks
While the backpropagation of error algorithm enables deep neural network training, it implies (i) bidirectional synaptic weight transport and (ii) update locking until the forward and backward passes are completed. Not only do these constraints preclude biological plausibility, but they also hinder...
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| Veröffentlicht in: | Front Neurosci |
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| Hauptverfasser: | , , |
| Format: | Artigo |
| Sprache: | Inglês |
| Veröffentlicht: |
Frontiers Media S.A.
2021
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| Schlagworte: | |
| Online Zugang: | https://ncbi.nlm.nih.gov/pmc/articles/PMC7902857/ https://ncbi.nlm.nih.gov/pubmed/33642986 https://ncbi.nlm.nih.govhttp://dx.doi.org/10.3389/fnins.2021.629892 |
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