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Application of Meta-Heuristic Algorithms for Training Neural Networks and Deep Learning Architectures: A Comprehensive Review
The learning process and hyper-parameter optimization of artificial neural networks (ANNs) and deep learning (DL) architectures is considered one of the most challenging machine learning problems. Several past studies have used gradient-based back propagation methods to train DL architectures. Howev...
| Autores principales: | , |
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| Formato: | Online Artículo Texto |
| Lenguaje: | English |
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Springer US
2022
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| Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9628382/ https://www.ncbi.nlm.nih.gov/pubmed/36339645 http://dx.doi.org/10.1007/s11063-022-11055-6 |