| Data-free knowledge distillation for heterogeneous federated learning Z Zhu, J Hong, J Zhou International conference on machine learning, 12878-12889, 2021 | 454 | 2021 |
| Federated adversarial debiasing for fair and transferable representations J Hong, Z Zhu, S Yu, Z Wang, HH Dodge, J Zhou Proceedings of the 27th ACM SIGKDD Conference on Knowledge Discovery & Data …, 2021 | 44 | 2021 |
| Efficient Split-Mix Federated Learning for On-Demand and In-Situ Customization J Hong, H Wang, Z Wang, J Zhou International Conference on Learning Representations, 2022 | 40 | 2022 |
| Federated robustness propagation: sharing adversarial robustness in heterogeneous federated learning J Hong, H Wang, Z Wang, J Zhou Proceedings of the AAAI Conference on Artificial Intelligence 37 (7), 7893-7901, 2023 | 35* | 2023 |
| MECTA: Memory-Economic Continual Test-Time Model Adaptation J Hong, L Lyu, J Zhou, M Spranger International Conference on Learning Representations, 2023 | 25 | 2023 |
| Resilient and communication efficient learning for heterogeneous federated systems Z Zhu, J Hong, S Drew, J Zhou Proceedings of Thirty-ninth International Conference on Machine Learning …, 2022 | 20 | 2022 |
| Variant grassmann manifolds: A representation augmentation method for action recognition J Hong, Y Li, H Chen ACM Transactions on Knowledge Discovery from Data (TKDD) 13 (2), 1-23, 2019 | 14 | 2019 |
| Short sequence classification through discriminable linear dynamical system Y Li, J Hong, H Chen IEEE Transactions on neural networks and learning systems 30 (11), 3396-3408, 2019 | 12 | 2019 |
| Learning model-based privacy protection under budget constraints J Hong, H Wang, Z Wang, J Zhou Proceedings of the AAAI Conference on Artificial Intelligence 35 (9), 7702-7710, 2021 | 10 | 2021 |
| Disturbance Grassmann kernels for subspace-based learning J Hong, H Chen, F Lin Proceedings of the 24th ACM SIGKDD international conference on knowledge …, 2018 | 9 | 2018 |
| DP-OPT: Make Large Language Model Your Privacy-Preserving Prompt Engineer J Hong, JT Wang, C Zhang, Z Li, B Li, Z Wang ICLR 2024, 2023 | 8 | 2023 |
| A privacy-preserving hybrid federated learning framework for financial crime detection H Zhang, J Hong, F Dong, S Drew, L Xue, J Zhou KDD International Workshop on Federated Learning for Distributed Data Mining, 2023 | 8 | 2023 |
| Trap and Replace: Defending Backdoor Attacks by Trapping Them into an Easy-to-Replace Subnetwork H Wang, J Hong, A Zhang, J Zhou, Z Wang NeurIPS 2022, 2022 | 8 | 2022 |
| Dynamic Privacy Budget Allocation Improves Data Efficiency of Differentially Private Gradient Descent J Hong, Z Wang, J Zhou ACM Conference on Fairness, Accountability, and Transparency, 11-35, 2022 | 8 | 2022 |
| Turning the Curse of Heterogeneity in Federated Learning into a Blessing for Out-of-Distribution Detection S Yu, J Hong, H Wang, Z Wang, J Zhou International Conference on Learning Representations, 2023 | 7 | 2023 |
| How robust is your fairness? evaluating and sustaining fairness under unseen distribution shifts H Wang, J Hong, J Zhou, Z Wang Transactions on machine learning research 2023, 2023 | 7 | 2023 |
| Outsourcing Training without Uploading Data via Efficient Collaborative Open-Source Sampling J Hong, L Lyu, J Zhou, M Spranger Advances in Neural Information Processing Systems, 2022 | 7 | 2022 |
| Sequential data classification in the space of liquid state machines Y Li, J Hong, H Chen Joint European Conference on Machine Learning and Knowledge Discovery in …, 2016 | 7 | 2016 |
| International Workshop on Federated Learning for Distributed Data Mining J Hong, Z Zhu, L Lyu, Y Zhou, VN Boddeti, J Zhou Proceedings of the 29th ACM SIGKDD Conference on Knowledge Discovery and …, 2023 | 3 | 2023 |
| Detecting MCI using real-time, ecologically valid data capture methodology: How to improve scientific rigor in digital biomarker analyses J Hong, J Kaye, HH Dodge, J Zhou, ORCATECH Alzheimer's & Dementia 16, e044371, 2020 | 3 | 2020 |
Jiayu ZhouMichigan State UniversityVerified email at cse.msu.edu
