Is Aggregation the Only Choice? Federated Learning via Layer-wise Model Recombination-Reference-Cited by-同舟云学术

Is Aggregation the Only Choice? Federated Learning via Layer-wise Model Recombination

Published:2024-08-24 Issue: Volume:34 Page:1096-1107
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Container-title:Proceedings of the 30th ACM SIGKDD Conference on Knowledge Discovery and Data Mining
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Author:

Hu Ming¹^ORCID,Yue Zhihao²^ORCID,Xie Xiaofei¹^ORCID,Chen Cheng²^ORCID,Huang Yihao³^ORCID,Wei Xian⁴^ORCID,Lian Xiang⁵^ORCID,Liu Yang³^ORCID,Chen Mingsong²^ORCID

Affiliation:

1. Singapore Management University, Singapore, Singapore

2. East China Normal University, Shanghai, China

3. Nanyang Technological University, Singapore, Singapore

4. Chinese Academy of Sciences, Shanghai, China

5. Kent State University, Kent, OH, USA

Funder

?Digital Silk Road? Shanghai International Joint Lab of Trustworthy Intelligent Software

the National Research Foundation, Singapore, and DSO National Laboratories under the AI Singapore Programme

National Natural Science Foundation of China

Natural Science Foundation

Natural Science Foundation of China

the National Research Foundation, Singapore, and the Cyber Security Agency under its National Cybersecurity R\&D Programme

Publisher

ACM

Link

https://dl.acm.org/doi/pdf/10.1145/3637528.3671722

Reference48 articles.

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2. Mohammed Adnan, Shivam Kalra, Jesse C Cresswell, Graham W Taylor, and Hamid R Tizhoosh. 2022. Federated learning and differential privacy for medical image analysis. Scientific reports, Vol. 12, 1 (2022), 1953.

3. The skellam mechanism for differentially private federated learning;Agarwal Naman;Advances in Neural Information Processing Systems,2021

4. Samiul Alam, Luyang Liu, Ming Yan, and Mi Zhang. 2022. Fedrolex: Model-heterogeneous federated learning with rolling sub-model extraction. Advances in neural information processing systems, Vol. 35 (2022), 29677--29690.