A Multifaceted Survey on Federated Learning: Fundamentals, Paradigm Shifts, Practical Issues, Recent Developments, Partnerships, Trade-Offs, Trustworthiness, and Ways Forward

Federated learning (FL) is considered a de facto standard for privacy preservation in AI environments because it does not require data to be aggregated in some central place to train an AI model. Preserving data on the client side and sharing only the model’s parameters with a central server...

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Автори:	Abdul Majeed, Seong Oun Hwang
Формат:	Artigo
Мова:	Inglês
Опубліковано:	IEEE 2024-01-01
Серія:	IEEE Access
Предмети:	Federated learning AI models poisoning attacks privacy preservation training data
Онлайн доступ:	https://ieeexplore.ieee.org/document/10555253/
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