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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...

Whakaahuatanga katoa

I tiakina i:
Ngā taipitopito rārangi puna kōrero
Ngā kaituhi matua: Jamie Heredge, Niraj Kumar, Dylan Herman, Shouvanik Chakrabarti, Romina Yalovetzky, Shree Hari Sureshbabu, Changhao Li, Marco Pistoia
Hōputu: Artigo
Reo:Inglês
I whakaputaina: Nature Portfolio 2025-05-01
Rangatū:npj Quantum Information
Urunga tuihono:https://doi.org/10.1038/s41534-025-01022-z
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