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Towards Fairness-Aware Federated Learning.
Shi Y, Yu H, Leung C. Shi Y, et al. Among authors: yu h. IEEE Trans Neural Netw Learn Syst. 2023 Apr 10;PP. doi: 10.1109/TNNLS.2023.3263594. Online ahead of print. IEEE Trans Neural Netw Learn Syst. 2023. PMID: 37037249
Towards Personalized Federated Learning.
Tan AZ, Yu H, Cui L, Yang Q. Tan AZ, et al. Among authors: yu h. IEEE Trans Neural Netw Learn Syst. 2023 Dec;34(12):9587-9603. doi: 10.1109/TNNLS.2022.3160699. Epub 2023 Nov 30. IEEE Trans Neural Netw Learn Syst. 2023. PMID: 35344498
Privacy and Robustness in Federated Learning: Attacks and Defenses.
Lyu L, Yu H, Ma X, Chen C, Sun L, Zhao J, Yang Q, Yu PS. Lyu L, et al. Among authors: yu ps, yu h. IEEE Trans Neural Netw Learn Syst. 2022 Nov 10;PP. doi: 10.1109/TNNLS.2022.3216981. Online ahead of print. IEEE Trans Neural Netw Learn Syst. 2022. PMID: 36355741
Multicomponent Adversarial Domain Adaptation: A General Framework.
Yi C, Chen H, Xu Y, Chen H, Liu Y, Tan H, Yan Y, Yu H. Yi C, et al. Among authors: yu h. IEEE Trans Neural Netw Learn Syst. 2023 Oct;34(10):6824-6838. doi: 10.1109/TNNLS.2023.3270359. Epub 2023 Oct 6. IEEE Trans Neural Netw Learn Syst. 2023. PMID: 37224350
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