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Confidential machine learning on untrusted platforms: a survey
With the ever-growing data and the need for developing powerful machine learning models, data owners increasingly depend on various untrusted platforms (e.g., public clouds, edges, and machine learning service providers) for scalable processing or collaborative learning. Thus, sensitive data and mod...
| Autores principales: | , |
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| Formato: | Online Artículo Texto |
| Lenguaje: | English |
| Publicado: |
Springer Singapore
2021
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| Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8591683/ https://www.ncbi.nlm.nih.gov/pubmed/34805760 http://dx.doi.org/10.1186/s42400-021-00092-8 |