FRAMU: Attention-Based Machine Unlearning Using Federated Reinforcement Learning-Reference-Cited by-同舟云学术

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FRAMU: Attention-Based Machine Unlearning Using Federated Reinforcement Learning

Published:2024-10 Issue:10 Volume:36 Page:5153-5167
ISSN:1041-4347
Container-title:IEEE Transactions on Knowledge and Data Engineering
language:
Short-container-title:IEEE Trans. Knowl. Data Eng.

Author:

Shaik Thanveer¹^ORCID,Tao Xiaohui¹^ORCID,Li Lin²^ORCID,Xie Haoran³^ORCID,Cai Taotao¹^ORCID,Zhu Xiaofeng⁴^ORCID,Li Qing⁵^ORCID

Affiliation:

1. School of Mathematics, Physics, and Computing, University of Southern Queensland, Darling Heights, QLD, Australia

2. School of Computer Science and Artificial Intelligence, Wuhan University of Technology, Wuhan, Hubei, China

3. Department of Computing and Decision Sciences, Lingnan University, Tuen Mun, Hong Kong

4. University of Electronic Science and Technology of China, Chengdu, Sichuan, China

5. Department of Computing, Hong Kong Polytechnic University, Hung Hom, Hong Kong

Funder

Lingnan University, Hong Kong

NSFC, China

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Link

http://xplorestaging.ieee.org/ielx7/69/10679113/10483278.pdf?arnumber=10483278

Reference60 articles.

1. TP2SF: A Trustworthy Privacy-Preserving Secured Framework for sustainable smart cities by leveraging blockchain and machine learning

2. A review On reinforcement learning: Introduction and applications in industrial process control

3. Federated Machine Learning: Survey, Multi-Level Classification, Desirable Criteria and Future Directions in Communication and Networking Systems

4. Privacy-Preserving Machine Learning: Threats and Solutions

5. Forgetting personal data and revoking consent under the GDPR: Challenges and proposed solutions

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