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Exploring deep neural networks via layer-peeled model: Minority collapse in imbalanced training
In this paper, we introduce the Layer-Peeled Model, a nonconvex, yet analytically tractable, optimization program, in a quest to better understand deep neural networks that are trained for a sufficiently long time. As the name suggests, this model is derived by isolating the topmost layer from the r...
| Autores principales: | , , , |
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| Formato: | Online Artículo Texto |
| Lenguaje: | English |
| Publicado: |
National Academy of Sciences
2021
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| Materias: | |
| Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8639364/ https://www.ncbi.nlm.nih.gov/pubmed/34675075 http://dx.doi.org/10.1073/pnas.2103091118 |