Characterizing privacy in quantum machine learning
Abstract Ensuring data privacy in machine learning models is critical, especially in distributed settings where model gradients are shared among multiple parties for collaborative learning. Motivated by the increasing success of recovering input data from the gradients of classical models, this stud...
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| Principais autores: | , , , , , , , |
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| Formato: | Artigo |
| Idioma: | Inglês |
| Publicado em: |
Nature Portfolio
2025-05-01
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| Colecção: | npj Quantum Information |
| Acesso em linha: | https://doi.org/10.1038/s41534-025-01022-z |
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