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Unsupervised Learning in an Ensemble of Spiking Neural Networks Mediated by ITDP
We propose a biologically plausible architecture for unsupervised ensemble learning in a population of spiking neural network classifiers. A mixture of experts type organisation is shown to be effective, with the individual classifier outputs combined via a gating network whose operation is driven b...
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| Pubblicato in: | PLoS Comput Biol |
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| Autori principali: | , , , |
| Natura: | Artigo |
| Lingua: | Inglês |
| Pubblicazione: |
Public Library of Science
2016
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| Soggetti: | |
| Accesso online: | https://ncbi.nlm.nih.gov/pmc/articles/PMC5070787/ https://ncbi.nlm.nih.gov/pubmed/27760125 https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1371/journal.pcbi.1005137 |
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