Crowdsourced federated learning architecture with personalized privacy preservation

In crowdsourced federated learning, differential privacy is commonly used to prevent the aggregation server from recovering training data from the models uploaded by clients to achieve privacy preservation. However, improper privacy budget settings and perturbation methods will severely impact model...

詳細記述

書誌詳細

主要な著者:	Yunfan Xu, Xuesong Qiu, Fan Zhang, Jiakai Hao
フォーマット:	Artigo
言語:	Inglês
出版事項:	Tsinghua University Press 2024-09-01
シリーズ:	Intelligent and Converged Networks
主題:	crowdsourced federated learning differential privacy privacy preservation two-stage game
オンライン･アクセス:	https://www.sciopen.com/article/10.23919/ICN.2024.0014
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