Vertical Federated Knowledge Transfer via Representation Distillation for Healthcare Collaboration Networks

Author:

Huang Chung-ju1ORCID,Wang Leye1ORCID,Han Xiao2ORCID

Affiliation:

1. School of Computer Science, Peking University, China

2. School of Information Management and Engineering, Shanghai University of Finance and Economics, China

Funder

NSFC

Publisher

ACM

Reference56 articles.

1. Federated Learning for Healthcare: Systematic Review and Architecture Proposal

2. Donald  A Barr . 2019. Health Disparities in the United States: Social Class , Race, Ethnicity, and the Social Determinants of Health . JHU Press . Donald A Barr. 2019. Health Disparities in the United States: Social Class, Race, Ethnicity, and the Social Determinants of Health. JHU Press.

3. Practical Lossless Federated Singular Vector Decomposition over Billion-Scale Data

4. XGBoost

5. Weijing Chen , Guoqiang Ma , Tao Fan , Yan Kang , Qian Xu , and Qiang Yang . 2021. SecureBoost+ : A High Performance Gradient Boosting Tree Framework for Large Scale Vertical Federated Learning. CoRR abs/2110.10927 ( 2021 ). arXiv:2110.10927https://arxiv.org/abs/2110.10927 Weijing Chen, Guoqiang Ma, Tao Fan, Yan Kang, Qian Xu, and Qiang Yang. 2021. SecureBoost+ : A High Performance Gradient Boosting Tree Framework for Large Scale Vertical Federated Learning. CoRR abs/2110.10927 (2021). arXiv:2110.10927https://arxiv.org/abs/2110.10927

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1. Federated semi-supervised representation augmentation with cross-institutional knowledge transfer for healthcare collaboration;Knowledge-Based Systems;2024-09

2. Vertical Federated Learning: Concepts, Advances, and Challenges;IEEE Transactions on Knowledge and Data Engineering;2024-07

3. A Data Reconstruction Attack Against Vertical Federated Learning Based on Knowledge Transfer;IEEE INFOCOM 2024 - IEEE Conference on Computer Communications Workshops (INFOCOM WKSHPS);2024-05-20

4. FedMix: Boosting with Data Mixture for Vertical Federated Learning;2024 IEEE 40th International Conference on Data Engineering (ICDE);2024-05-13

5. Towards Heterogeneous Federated Learning: Analysis, Solutions, and Future Directions;Lecture Notes in Computer Science;2024

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