arXiv Preprints

- 2024 -

1. L. Yi, H. Yu, C. Ren, G. Wang, X. Liu & X. Li, "Federated Model Heterogeneous Matryoshka Representation Learning," arXiv preprint arXiv:2406.00488, 2024.

2. L. Yi, H. Yu, C. Ren, H. Zhang, G. Wang, X. Liu & X. Li, "pFedAFM: Adaptive Feature Mixture for Batch-Level Personalization in Heterogeneous Federated Learning," arXiv preprint arXiv:2404.17847, 2024.

3. C. Ren, H. Yu, H. Peng, X. Tang, A. Li, Y. Gao, A. Z. Tan, B. Zhao, X. Li, Z. Li & Q. Yang, "Advances and Open Challenges in Federated Learning with Foundation Models," arXiv preprint arXiv:2404.15381, 2024.

4. L. Yi, H. Yu, C. Ren, H. Zhang, G. Wang, X. Liu & X. Li, "pFedMoE: Data-Level Personalization with Mixture of Experts for Model-Heterogeneous Personalized Federated Learning," arXiv preprint arXiv:2402.01350, 2024.

- 2023 -

5. L. Yi, H. Yu, Z. Shi, G. Wang, X. Liu, L. Cui & X. Li, "FedSSA: Semantic Similarity-based Aggregation for Efficient Model-Heterogeneous Personalized Federated Learning," arXiv preprint arXiv:2311.06879, 2023.

6. X. Tang & H. Yu, "Multi-Session Budget Optimization for Forward Auction-based Federated Learning," arXiv preprint arXiv:2311.12548, 2023.

7. L. Yi, H. Yu, G. Wang & X. Liu, "pFedES: Model Heterogeneous Personalized Federated Learning with Feature Extractor Sharing," arXiv preprint arXiv:2311.06879, 2023.

8. L. Yi, H. Yu, G. Wang, X. Liu & X. Li, "pFedLoRA: Model-Heterogeneous Personalized Federated Learning with LoRA Tuning," arXiv preprint arXiv:2310.13283, 2023.

9. X. Tan & H. Yu, "Hire When You Need to: Gradual Participant Recruitment for Auction-based Federated Learning," arXiv preprint arXiv:2310.02651, 2023.

10. Z. Xiong, Y. Zhang, Z. Shen, P. Ren & H. Yu, "Image Aesthetics Assessment via Learnable Queries," arXiv preprint arXiv:2309.02861, 2023.

11. P. Xing, S. Lu & H. Yu, "FedLogic: Interpretable Federated Multi-Domain Chain-of-Thought Prompt Selection for Large Language Models," arXiv preprint arXiv:2308.15324, 2023.

12. Y. Zhang & H. Yu, "LR-XFL: Logical Reasoning-based Explainable Federated Learning," arXiv preprint arXiv:2308.12681, 2023.

13. R. Liu, Y. Chen, A. Li, Y. Ding, H. Yu & C. Guan, "Aggregating Intrinsic Information to Enhance BCI Performance through Federated Learning," arXiv preprint arXiv:2308.11636, 2023.

14. Y. Gao, H. Sun, Z. Li & H. Yu, "The Prospect of Enhancing Large-Scale Heterogeneous Federated Learning with Transformers," arXiv preprint arXiv:2308.03945, 2023.

15. C. Ren, H. Yu, R. Yan, M. Xu, Y. Shen, H. Zhu, D. Niyato, Z. Y. Dong & L. C. Kwek, "Towards Quantum Federated Learning," arXiv preprint arXiv:2306.09912, 2023.

16. Z. Chen, J. Chen, Y. Chen, H. Yu, A. Singh & M. Sra, "LMExplainer: A Knowledge-Enhanced Explainer for Language Models," arXiv preprint arXiv:2303.16537, 2023.

17. L. Yi, G. Wang, X. Liu, Z. Shi & H. Yu, "FedGH: Heterogeneous Federated Learning with Generalized Global Header," arXiv preprint arXiv:2303.13137, 2023.

18. A. Li, R. Liu, M. Hu, L. A. Tuan & H. Yu, "Towards Interpretable Federated Learning," arXiv preprint arXiv:2302.13473, 2023.

- 2022 -

19. W. Lu, J. Wang, H. Yu, L. Huang, X. Zhang, Y. Chen & X. Xie, "FIXED: Frustratingly Easy Domain Generalization with Mixup," arXiv preprint arXiv:2211.05228, 2022.

20. X. Guo & H. Yu, "On the Domain Adaptation and Generalization of Pretrained Language Models: A Survey," arXiv preprint arXiv:2211.03154, 2022.

21. X. Tang & H. Yu, "Towards Trustworthy AI-Empowered Real-Time Bidding for Online Advertisement Auctioning," arXiv preprint arXiv:2210.07770, 2022.

22. Y. Zhang & H. Yu, "Towards Verifiable Federated Learning," arXiv preprint arXiv:2202.08310, 2022.

23. R. Liu, P. Xing, Z. Deng, A. Li, C. Guan & H. Yu, "Federated Graph Neural Networks: Overview, Techniques and Challenges," arXiv preprint arXiv:2202.07256, 2022.

- 2021 -

24. C. Liu & H. Yu, "AI-Empowered Persuasive Video Generation: A Survey," arXiv preprint arXiv:2112.09401, 2021.

25. Y. Shi, H. Yu & C. Leung, "Towards Fairness-Aware Federated Learning," arXiv preprint arXiv:2111.01872, 2021.

26. X. Wu & H. Yu, "MarS-FL: Enabling Competitors to Collaborate in Federated Learning," arXiv preprint arXiv:2110.13464, 2021.

27. Y.-A. Xie, J. Kang, D. Niyato, N. T. T. Van, N. C. Luong, Z. Liu & H. Yu, "Securing Federated Learning: A Covert Communication-based Approach," arXiv preprint arXiv:2110.02221, 2021.

28. Z. Liu, Y. Chen, H. Yu, Y. Liu & L. Cui, "GTG-Shapley: Efficient and Accurate Participant Contribution Evaluation in Federated Learning," arXiv preprint arXiv:2109.02053, 2021.

29. S. K. Pye & H. Yu, "Personalised Federated Learning: A Combinational Approach," arXiv preprint arXiv:2108.09618, 2021.

30. A. Z. Tan, H. Yu, L. Cui & Q. Yang, "Towards Personalized Federated Learning," arXiv preprint arXiv:2103.00710, 2021.

- 2020 -

31. L. Lyu, H. Yu, X. Ma, L. Sun, J. Zhao, Q. Yang & P. S. Yu, "Privacy and Robustness in Federated Learning: Attacks and Defenses," arXiv preprint arXiv:2012.06337, 2020.

32. L. Wang, H. Yu & X. Han, "Federated Crowdsourcing: Framework and Challenges," arXiv preprint arXiv:2011.03208, 2020.

33. G. Li, C. Liu, H. Yu, Y. Fan, L. Zhang, Z. Wang & M. Wang, "SCNet: A Neural Network for Automated Side-Channel Attack," arXiv preprint arXiv:2008.00476, 2020. 

34. M. Cong, X. Weng, H. Yu, J. Qu & S. M. Yiu, "Optimal Procurement Auction for Cooperative Production of Virtual Products: Vickrey-Clarke-Groves Meet Cremer-McLean," arXiv preprint arXiv:2007.14780, 2020. 

35. C. Ju, R. Zhao, J. Sun, X. Wei, B. Zhao, Y. Liu, H. Li, T. Chen, X. Zhang, D. Gao, B. Tan, H. Yu & Y. Jin, "Privacy-Preserving Technology to Help Millions of People: Federated Prediction Model for Stroke Prevention," arXiv preprint arXiv:2006.10517, 2020.

36. L. Lyu, H. Yu & Q. Yang, "Threats to Federated Learning: A Survey," CoRR, arXiv:2003.02133, 2020.

37. Y. Liu, S. Sun, Z. Ai, S. Zhang, Z. Liu & H. Yu, "FedCoin: A Peer-to-Peer Payment System for Federated Learning," arXiv preprint arXiv:2002.11711, 2020.

38. S. Feng & H. Yu, "Multi-Participant Multi-Class Vertical Federated Learning," arXiv preprint arXiv:2001.11154, 2020.

39. Y. Chen, X. Yang, X. Qin, H. Yu, B. Chen & Z. Shen, "FOCUS: Dealing with Label Quality Disparity in Federated Learning," arXiv preprint arXiv:2001.11359, 2020.

- 2019 -

40. P. Kairouz, H. B. McMahan, B. Avent, A. Bellet, M. Bennis, A. N. Bhagoji, K. Bonawitz, Z. Charles, G. Cormode, R. Cummings, R. G. L. D'Oliveira, S. E. Rouayheb, D. Evans, J. Gardner, Z. Garrett, A. Gascón, B. Ghazi, P. B. Gibbons, M. Gruteser, Z. Harchaoui, C. He, L. He, Z. Huo, B. Hutchinson, J. Hsu, M. Jaggi, T. Javidi, G. Joshi, M. Khodak, J. Konečný, A. Korolova, F. Koushanfar, S. Koyejo, T. Lepoint, Y. Liu, P. Mittal, M. Mohri, R. Nock, A. Özgür, R. Pagh, M. Raykova, H. Qi, D. Ramage, R. Raskar, D. Song, W. Song, S. U. Stich, Z. Sun, A. T. Suresh, F. Tramèr, P. Vepakomma, J. Wang, L. Xiong, Z. Xu, Q. Yang, F. X. Yu, H. Yu & S. Zhao, "Advances and Open Problems in Federated Learning," arXiv preprint arXiv:1912.04977, 2019. (zhuanzhi.ai report)

41. J. Zhao, T. Wang, T. Bai, K.-Y. Lam, Z. Xu, S. Shi, X. Ren, X. Yang, Y. Liu & H. Yu, "Reviewing and Improving the Gaussian Mechanism for Differential Privacy," arXiv preprint arXiv:1911.12060, 2019.

- 2016 -

42. S. Fauvel & H. Yu, "A Survey on Artificial Intelligence and Data Mining for MOOCs," arXiv preprint arXiv:1601.06862, 2016.

- 2014 -

43. H. Yu, Z. Shen, Q. Wu & C. Miao, "Designing Socially Intelligent Virtual Companions," arXiv preprint arXiv:1411.7090, 2014.

44. J. Lin, H. Yu & Z. Shen, "An Empirical Analysis of Task Allocation in Scrum-based Agile Programming,"arXiv preprint arXiv:1411.6201, 2014.

45. J. Lin, H. Yu & Z. Shen, "Identifying Talented Software Engineering Students through Data-driven Skill Assessment," arXiv preprint arXiv:1411.6197, 2014.