Short-and-Long-Term Impact of Initialization Functions in NeuroEvolution

Author:

Evangelista Lucas Gabriel Coimbra,Giusti RafaelORCID

Publisher

Springer International Publishing

Reference25 articles.

1. Ma, Y., Xie, Y.: Evolutionary neural networks for deep learning: a review. Int. J. Mach. Learn. Cybern. (2022). https://doi.org/10.1007/s13042-022-01578-8

2. Kumar, S. K.: On weight initialization in deep neural networks. In: arXiv preprint arXiv:1704.08863 (2017)

3. Initializing neural networks. https://www.deeplearning.ai/ai-notes/initialization/. Accessed 12 June 2022

4. Goodfellow, I.J., Bengio, Y., Courville, A.: Deep Learning, 1st edn. Cambridge (2016)

5. Glorot, X., Bengio, Y.: Understanding the difficulty of training deep feedforward neural networks. In: Proceedings of the Thirteenth International Conference on Artificial Intelligence and Statistics, pp. 249–256. JMLR Workshop and Conference Proceedings, Sardinia (2010)

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