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High-dimensional dynamics of generalization error in neural networks
We perform an analysis of the average generalization dynamics of large neural networks trained using gradient descent. We study the practically-relevant “high-dimensional” regime where the number of free parameters in the network is on the order of or even larger than the number of examples in the d...
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| Publicado no: | Neural Netw |
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| Main Authors: | , , |
| Formato: | Artigo |
| Idioma: | Inglês |
| Publicado em: |
Pergamon Press
2020
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| Assuntos: | |
| Acesso em linha: | https://ncbi.nlm.nih.gov/pmc/articles/PMC7685244/ https://ncbi.nlm.nih.gov/pubmed/33022471 https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1016/j.neunet.2020.08.022 |
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