Junyuan Hong

According to our database, Junyuan Hong authored at least 30 papers between 2016 and 2024.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2024

Decoding Compressed Trust: Scrutinizing the Trustworthiness of Efficient LLMs Under Compression.

Junyuan Hong, Jinhao Duan, Chenhui Zhang, Zhangheng Li, Chulin Xie, Kelsey Lieberman, James Diffenderfer, Brian R. Bartoldson, Ajay Jaiswal, Kaidi Xu, Bhavya Kailkhura, Dan Hendrycks, Dawn Song, Zhangyang Wang, Bo Li

CoRR, 2024

Shake to Leak: Fine-tuning Diffusion Models Can Amplify the Generative Privacy Risk.

Zhangheng Li, Junyuan Hong, Bo Li, Zhangyang Wang

CoRR, 2024

On the Generalization Ability of Unsupervised Pretraining.

Yuyang Deng, Junyuan Hong, Jiayu Zhou, Mehrdad Mahdavi

CoRR, 2024

Revisiting Zeroth-Order Optimization for Memory-Efficient LLM Fine-Tuning: A Benchmark.

Yihua Zhang, Pingzhi Li, Junyuan Hong, Jiaxiang Li, Yimeng Zhang, Wenqing Zheng, Pin-Yu Chen, Jason D. Lee, Wotao Yin, Mingyi Hong, Zhangyang Wang, Sijia Liu, Tianlong Chen

CoRR, 2024

2023

How Robust is Your Fairness? Evaluating and Sustaining Fairness under Unseen Distribution Shifts.

Haotao Wang, Junyuan Hong, Jiayu Zhou, Zhangyang Wang

Trans. Mach. Learn. Res., 2023

DP-OPT: Make Large Language Model Your Privacy-Preserving Prompt Engineer.

Junyuan Hong, Jiachen T. Wang, Chenhui Zhang, Zhangheng Li, Bo Li, Zhangyang Wang

CoRR, 2023

Who Leaked the Model? Tracking IP Infringers in Accountable Federated Learning.

Shuyang Yu, Junyuan Hong, Yi Zeng, Fei Wang, Ruoxi Jia, Jiayu Zhou

CoRR, 2023

Safe and Robust Watermark Injection with a Single OoD Image.

Shuyang Yu, Junyuan Hong, Haobo Zhang, Haotao Wang, Zhangyang Wang, Jiayu Zhou

CoRR, 2023

FedNoisy: Federated Noisy Label Learning Benchmark.

Siqi Liang, Jintao Huang, Dun Zeng, Junyuan Hong, Jiayu Zhou, Zenglin Xu

CoRR, 2023

On the Hardness of Robustness Transfer: A Perspective from Rademacher Complexity over Symmetric Difference Hypothesis Space.

Yuyang Deng, Nidham Gazagnadou, Junyuan Hong, Mehrdad Mahdavi, Lingjuan Lyu

CoRR, 2023

Understanding Deep Gradient Leakage via Inversion Influence Functions.

Haobo Zhang, Junyuan Hong, Yuyang Deng, Mehrdad Mahdavi, Jiayu Zhou

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

International Workshop on Federated Learning for Distributed Data Mining.

Junyuan Hong, Zhuangdi Zhu, Lingjuan Lyu, Yang Zhou, Vishnu Naresh Boddeti, Jiayu Zhou

Proceedings of the 29th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, 2023

Revisiting Data-Free Knowledge Distillation with Poisoned Teachers.

Junyuan Hong, Yi Zeng, Shuyang Yu, Lingjuan Lyu, Ruoxi Jia, Jiayu Zhou

Proceedings of the International Conference on Machine Learning, 2023

Turning the Curse of Heterogeneity in Federated Learning into a Blessing for Out-of-Distribution Detection.

Shuyang Yu, Junyuan Hong, Haotao Wang, Zhangyang Wang, Jiayu Zhou

Proceedings of the Eleventh International Conference on Learning Representations, 2023

MECTA: Memory-Economic Continual Test-Time Model Adaptation.

Junyuan Hong, Lingjuan Lyu, Jiayu Zhou, Michael Spranger

Proceedings of the Eleventh International Conference on Learning Representations, 2023

Federated Robustness Propagation: Sharing Adversarial Robustness in Heterogeneous Federated Learning.

Junyuan Hong, Haotao Wang, Zhangyang Wang, Jiayu Zhou

Proceedings of the Thirty-Seventh AAAI Conference on Artificial Intelligence, 2023

2022

Trap and Replace: Defending Backdoor Attacks by Trapping Them into an Easy-to-Replace Subnetwork.

Haotao Wang, Junyuan Hong, Aston Zhang, Jiayu Zhou, Zhangyang Wang

Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

Outsourcing Training without Uploading Data via Efficient Collaborative Open-Source Sampling.

Junyuan Hong, Lingjuan Lyu, Jiayu Zhou, Michael Spranger

Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

Resilient and Communication Efficient Learning for Heterogeneous Federated Systems.

Zhuangdi Zhu, Junyuan Hong, Steve Drew, Jiayu Zhou

Proceedings of the International Conference on Machine Learning, 2022

Efficient Split-Mix Federated Learning for On-Demand and In-Situ Customization.

Junyuan Hong, Haotao Wang, Zhangyang Wang, Jiayu Zhou

Proceedings of the Tenth International Conference on Learning Representations, 2022

Dynamic Privacy Budget Allocation Improves Data Efficiency of Differentially Private Gradient Descent.

Junyuan Hong, Zhangyang Wang, Jiayu Zhou

Proceedings of the FAccT '22: 2022 ACM Conference on Fairness, Accountability, and Transparency, Seoul, Republic of Korea, June 21, 2022

2021

Federated Robustness Propagation: Sharing Adversarial Robustness in Federated Learning.

Junyuan Hong, Haotao Wang, Zhangyang Wang, Jiayu Zhou

CoRR, 2021

On Dynamic Noise Influence in Differentially Private Learning.

Junyuan Hong, Zhangyang Wang, Jiayu Zhou

CoRR, 2021

Federated Adversarial Debiasing for Fair and Transferable Representations.

Junyuan Hong, Zhuangdi Zhu, Shuyang Yu, Zhangyang Wang, Hiroko H. Dodge, Jiayu Zhou

Proceedings of the KDD '21: The 27th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, 2021

Data-Free Knowledge Distillation for Heterogeneous Federated Learning.

Zhuangdi Zhu, Junyuan Hong, Jiayu Zhou

Proceedings of the 38th International Conference on Machine Learning, 2021

Learning Model-Based Privacy Protection under Budget Constraints.

Junyuan Hong, Haotao Wang, Zhangyang Wang, Jiayu Zhou

Proceedings of the Thirty-Fifth AAAI Conference on Artificial Intelligence, 2021

2019

Short Sequence Classification Through Discriminable Linear Dynamical System.

Yang Li, Junyuan Hong, Huanhuan Chen

IEEE Trans. Neural Networks Learn. Syst., 2019

Variant Grassmann Manifolds: A Representation Augmentation Method for Action Recognition.

Junyuan Hong, Yang Li, Huanhuan Chen

ACM Trans. Knowl. Discov. Data, 2019

2018

Disturbance Grassmann Kernels for Subspace-Based Learning.

Junyuan Hong, Huanhuan Chen, Feng Lin

Proceedings of the 24th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining, 2018

2016

Sequential Data Classification in the Space of Liquid State Machines.

Yang Li, Junyuan Hong, Huanhuan Chen

Proceedings of the Machine Learning and Knowledge Discovery in Databases, 2016