Rethinking Personalized Federated Learning with Clustering-Based Dynamic Graph Propagation

Author:

Wang Jiaqi,Chen Yuzhong,Wu Yuhang,Das Mahashweta,Yang Hao,Ma Fenglong

Publisher

Springer Nature Singapore

Reference32 articles.

1. Arivazhagan, M.G., Aggarwal, V., Singh, A.K., Choudhary, S.: Federated learning with personalization layers. arXiv preprint arXiv:1912.00818 (2019)

2. Briggs, C., Fan, Z., Andras, P.: Federated learning with hierarchical clustering of local updates to improve training on non-IID data. In: 2020 International Joint Conference on Neural Networks, pp. 1–9. IEEE (2020)

3. Chen, F., Long, G., Wu, Z., Zhou, T., Jiang, J.: Personalized federated learning with graph. arXiv preprint arXiv:2203.00829 (2022)

4. Fallah, A., Mokhtari, A., Ozdaglar, A.: Personalized federated learning with theoretical guarantees: a model-agnostic meta-learning approach. In: Advances in Neural Information Processing Systems, vol. 33, pp. 3557–3568 (2020)

5. Ghosh, A., Chung, J., Yin, D., Ramchandran, K.: An efficient framework for clustered federated learning. In: Advances in Neural Information Processing Systems, vol. 33, pp. 19586–19597 (2020)

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