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Junyuan (Jason) Hong
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Year
Data-free knowledge distillation for heterogeneous federated learning
Z Zhu, J Hong, J Zhou
International conference on machine learning, 12878-12889, 2021
6972021
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
542022
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
532021
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
48*2023
MECTA: Memory-Economic Continual Test-Time Model Adaptation
J Hong, L Lyu, J Zhou, M Spranger
International Conference on Learning Representations, 2023
362023
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
31*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
312022
Revisiting Zeroth-Order Optimization for Memory-Efficient LLM Fine-Tuning: A Benchmark
Y Zhang, P Li, J Hong, J Li, Y Zhang, W Zheng, PY Chen, JD Lee, W Yin, ...
ICML, 2024
242024
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
202023
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
142019
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
132023
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
132022
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
132022
Shake to Leak: Fine-tuning Diffusion Models Can Amplify the Generative Privacy Risk
Z Li, J Hong, B Li, Z Wang
2nd IEEE Conference on Secure and Trustworthy Machine Learning, 2024
122024
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
122023
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
122021
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
122019
Decoding Compressed Trust: Scrutinizing the Trustworthiness of Efficient LLMs Under Compression
J Hong, J Duan, C Zhang, Z Li, C Xie, K Lieberman, J Diffenderfer, ...
ICML, 2024
112024
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
92022
Disturbance Grassmann kernels for subspace-based learning
J Hong, H Chen, F Lin
Proceedings of the 24th ACM SIGKDD international conference on knowledge …, 2018
92018
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