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A Kernel Theory of Modern Data Augmentation
Data augmentation, a technique in which a training set is expanded with class-preserving transformations, is ubiquitous in modern machine learning pipelines. In this paper, we seek to establish a theoretical framework for understanding data augmentation. We approach this from two directions: First,...
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| Publicado no: | Proc Mach Learn Res |
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| Main Authors: | , , , , , |
| Formato: | Artigo |
| Idioma: | Inglês |
| Publicado em: |
2019
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| Assuntos: | |
| Acesso em linha: | https://ncbi.nlm.nih.gov/pmc/articles/PMC6879382/ https://ncbi.nlm.nih.gov/pubmed/31777848 |
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