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Bayesian interpolation with deep linear networks
Characterizing how neural network depth, width, and dataset size jointly impact model quality is a central problem in deep learning theory. We give here a complete solution in the special case of linear networks with output dimension one trained using zero noise Bayesian inference with Gaussian weig...
| Autores principales: | , |
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| Formato: | Online Artículo Texto |
| Lenguaje: | English |
| Publicado: |
National Academy of Sciences
2023
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| Materias: | |
| Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10266010/ https://www.ncbi.nlm.nih.gov/pubmed/37252994 http://dx.doi.org/10.1073/pnas.2301345120 |