Zobrazeno 1 - 6
of 6
pro vyhledávání: '"differentiated differential privacy"'
Autor:
Li, Yong1,2,3 (AUTHOR) liyong@ccut.edu.cn, Du, Wei1 (AUTHOR) 2202103022@stu.ccut.edu.cn, Han, Liquan1 (AUTHOR) 2202103042@stu.ccut.edu.cn, Zhang, Zhenjian1 (AUTHOR) 2202103086@stu.ccut.edu.cn, Liu, Tongtong1 (AUTHOR)
Publikováno v:
Sensors (14248220). Dec2023, Vol. 23 Issue 23, p9305. 21p.
Publikováno v:
Sensors, Vol 23, Iss 23, p 9305 (2023)
There are several unsolved problems in federated learning, such as the security concerns and communication costs associated with it. Differential privacy (DP) offers effective privacy protection by introducing noise to parameters based on rigorous pr
Externí odkaz:
https://doaj.org/article/91fbbf4a8ee74b0c9c2deb4e9b26c58f
Publikováno v:
Journal of Computer Engineering & Applications; Oct2024, Vol. 60 Issue 19, p278-287, 10p
Publikováno v:
International Journal of Advanced Computer Science & Applications; Jul2024, Vol. 15 Issue 7, p220-230, 11p
Publikováno v:
Proceedings of SPIE; 9/1/2023, Vol. 12641, p1264103-1264103, 1p
Autor:
Shuihua Wang
This book constitutes the refereed proceedings of the Third EAI International Conference on IoT and Big Data Technologies for Health Care, IotCARE 2022, which took place virtually during December 12-13, 2022.The 23 papers included in this volume were
