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POPri: Private Federated Learning using Preference-Optimized Synthetic Data

Fuente: arXiv

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Détails bibliographiques
Auteurs principaux:	Hou, Charlie, Wang, Mei-Yu, Zhu, Yige, Lazar, Daniel, Fanti, Giulia
Format:	Preprint
Publié:	2025
Sujets:	Machine Learning Artificial Intelligence Cryptography and Security Distributed, Parallel, and Cluster Computing
Accès en ligne:	Acceder al recurso
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