Toward Neuromic Computing: Neurons as Autoencoders
Fuente:
arXiv
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| Format: | Preprint |
| Published: |
2024
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| _version_ | 1866910422610739200 |
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| author | Bull, Larry |
| author_facet | Bull, Larry |
| contents | This short paper presents the idea that neural backpropagation is using dendritic processing to enable individual neurons to perform autoencoding. Using a very simple connection weight search heuristic and artificial neural network model, the effects of interleaving autoencoding for each neuron in a hidden layer of a feedforward network are explored. This is contrasted to the standard layered approach to autoencoding. It is shown that such individualised processing is not detrimental and can improve network learning. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2403_02331 |
| institution | arXiv |
| publishDate | 2024 |
| record_format | arxiv |
| spellingShingle | Toward Neuromic Computing: Neurons as Autoencoders Bull, Larry Neural and Evolutionary Computing This short paper presents the idea that neural backpropagation is using dendritic processing to enable individual neurons to perform autoencoding. Using a very simple connection weight search heuristic and artificial neural network model, the effects of interleaving autoencoding for each neuron in a hidden layer of a feedforward network are explored. This is contrasted to the standard layered approach to autoencoding. It is shown that such individualised processing is not detrimental and can improve network learning. |
| title | Toward Neuromic Computing: Neurons as Autoencoders |
| topic | Neural and Evolutionary Computing |
| url | https://arxiv.org/abs/2403.02331 |