Differentially Private Federated Learning for Multitask Objective Recognition-Reference-Cited by-同舟云学术

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Differentially Private Federated Learning for Multitask Objective Recognition

Published:2024-05 Issue:5 Volume:20 Page:7269-7281
ISSN:1551-3203
Container-title:IEEE Transactions on Industrial Informatics
language:
Short-container-title:IEEE Trans. Ind. Inf.

Author:

Xie Renyou¹^ORCID,Li Chaojie¹^ORCID,Zhou Xiaojun²^ORCID,Chen Hongyang³^ORCID,Dong Zhaoyang⁴^ORCID

Affiliation:

1. School of Electrical Engineering and Telecommunications, University of New South Wales, Sydney, NSW, Australia

2. School of Automation, Central South University, Changsha, China

3. Research Center for Graph Computing, Zhejiang Lab, Hangzhou, China

4. School of Electrical and Electronic Engineering, Nanyang Technological University, Singapore

Funder

Australian Research Council

National Key R&D Program of China

National Natural Science Foundation of China

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Link

http://xplorestaging.ieee.org/ielx7/9424/10521545/10429819.pdf?arnumber=10429819

Reference38 articles.

1. Hierarchical Progressive Network for Multimodal Medical Image Fusion in Healthcare Systems

2. A Survey of the Usages of Deep Learning for Natural Language Processing

3. Multi-timescale Forecast of Solar Irradiance Based on Multi-task Learning and Echo State Network Approaches

4. A brief review on multi-task learning

5. Multi-task learning as multi-objective optimization;Sener,2019

Cited by 1 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Differential Private Federated Learning in Geographically Distributed Public Administration Processes;Future Internet;2024-06-23

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