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Hardware-Efficient On-line Learning through Pipelined Truncated-Error Backpropagation in Binary-State Networks
Artificial neural networks (ANNs) trained using backpropagation are powerful learning architectures that have achieved state-of-the-art performance in various benchmarks. Significant effort has been devoted to developing custom silicon devices to accelerate inference in ANNs. Accelerating the traini...
| Autores principales: | , , , |
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| Formato: | Online Artículo Texto |
| Lenguaje: | English |
| Publicado: |
Frontiers Media S.A.
2017
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| Materias: | |
| Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5592276/ https://www.ncbi.nlm.nih.gov/pubmed/28932180 http://dx.doi.org/10.3389/fnins.2017.00496 |