Modeling the Influence of Data Structure on Learning in Neural Networks: The Hidden Manifold Model
Understanding the reasons for the success of deep neural networks trained using stochastic gradient-based methods is a key open problem for the nascent theory of deep learning. The types of data where these networks are most successful, such as images or sequences of speech, are characterized by int...
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| Autores principales: | , , , |
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| Formato: | article |
| Lenguaje: | EN |
| Publicado: |
American Physical Society
2020
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| Materias: | |
| Acceso en línea: | https://doaj.org/article/1a23fabc856f4ecb8c6ed721b923a393 |
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