Chen Chen

According to our database, Chen Chen authored at least 43 papers between 2019 and 2024.

Collaborative distances:

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

2024

Practical Attribute Reconstruction Attack Against Federated Learning.

Chen Chen, Lingjuan Lyu, Han Yu, Gang Chen

IEEE Trans. Big Data, December, 2024

Privacy and Robustness in Federated Learning: Attacks and Defenses.

Lingjuan Lyu, Han Yu, Xingjun Ma, Chen Chen, Lichao Sun, Jun Zhao, Qiang Yang, Philip S. Yu

IEEE Trans. Neural Networks Learn. Syst., July, 2024

Dual Low-Rank Adaptation for Continual Learning with Pre-Trained Models.

Huancheng Chen, Jingtao Li, Nidham Gazagnadou, Weiming Zhuang, Chen Chen, Lingjuan Lyu

CoRR, 2024

Self-Comparison for Dataset-Level Membership Inference in Large (Vision-)Language Models.

Jie Ren, Kangrui Chen, Chen Chen, Vikash Sehwag, Yue Xing, Jiliang Tang, Lingjuan Lyu

CoRR, 2024

EnTruth: Enhancing the Traceability of Unauthorized Dataset Usage in Text-to-image Diffusion Models with Minimal and Robust Alterations.

Jie Ren, Yingqian Cui, Chen Chen, Vikash Sehwag, Yue Xing, Jiliang Tang, Lingjuan Lyu

CoRR, 2024

Evaluating and Mitigating IP Infringement in Visual Generative AI.

Zhenting Wang, Chen Chen, Vikash Sehwag, Minzhou Pan, Lingjuan Lyu

CoRR, 2024

Is Synthetic Image Useful for Transfer Learning? An Investigation into Data Generation, Volume, and Utilization.

Yuhang Li, Xin Dong, Chen Chen, Jingtao Li, Yuxin Wen, Michael Spranger, Lingjuan Lyu

CoRR, 2024

COALA: A Practical and Vision-Centric Federated Learning Platform.

Weiming Zhuang, Jian Xu, Chen Chen, Jingtao Li, Lingjuan Lyu

Proceedings of the Forty-first International Conference on Machine Learning, 2024

How to Trace Latent Generative Model Generated Images without Artificial Watermark?

Zhenting Wang, Vikash Sehwag, Chen Chen, Lingjuan Lyu, Dimitris N. Metaxas, Shiqing Ma

Proceedings of the Forty-first International Conference on Machine Learning, 2024

Detecting, Explaining, and Mitigating Memorization in Diffusion Models.

Yuxin Wen, Yuchen Liu, Chen Chen, Lingjuan Lyu

Proceedings of the Twelfth International Conference on Learning Representations, 2024

DIAGNOSIS: Detecting Unauthorized Data Usages in Text-to-image Diffusion Models.

Zhenting Wang, Chen Chen, Lingjuan Lyu, Dimitris N. Metaxas, Shiqing Ma

Proceedings of the Twelfth International Conference on Learning Representations, 2024

A Simple Background Augmentation Method for Object Detection with Diffusion Model.

Yuhang Li, Xin Dong, Chen Chen, Weiming Zhuang, Lingjuan Lyu

Proceedings of the Computer Vision - ECCV 2024, 2024

FedMef: Towards Memory-Efficient Federated Dynamic Pruning.

Hong Huang, Weiming Zhuang, Chen Chen, Lingjuan Lyu

Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2024

2023

Decision Boundary-Aware Data Augmentation for Adversarial Training.

Chen Chen, Jingfeng Zhang, Xilie Xu, Lingjuan Lyu, Chaochao Chen, Tianlei Hu, Gang Chen

IEEE Trans. Dependable Secur. Comput., 2023

How to Detect Unauthorized Data Usages in Text-to-image Diffusion Models.

Zhenting Wang, Chen Chen, Yuchen Liu, Lingjuan Lyu, Dimitris N. Metaxas, Shiqing Ma

CoRR, 2023

When Foundation Model Meets Federated Learning: Motivations, Challenges, and Future Directions.

Weiming Zhuang, Chen Chen, Lingjuan Lyu

CoRR, 2023

Alteration-free and Model-agnostic Origin Attribution of Generated Images.

Zhenting Wang, Chen Chen, Yi Zeng, Lingjuan Lyu, Shiqing Ma

CoRR, 2023

Addressing Catastrophic Forgetting in Federated Class-Continual Learning.

Jie Zhang, Chen Chen, Weiming Zhuang, LingJuan Lv

CoRR, 2023

A Pathway Towards Responsible AI Generated Content.

Chen Chen, Jie Fu, Lingjuan Lyu

CoRR, 2023

GAIN: Enhancing Byzantine Robustness in Federated Learning with Gradient Decomposition.

Yuchen Liu, Chen Chen, Lingjuan Lyu, Fangzhao Wu, Sai Wu, Gang Chen

CoRR, 2023

Where Did I Come From? Origin Attribution of AI-Generated Images.

Zhenting Wang, Chen Chen, Yi Zeng, Lingjuan Lyu, Shiqing Ma

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

Is Heterogeneity Notorious? Taming Heterogeneity to Handle Test-Time Shift in Federated Learning.

Yue Tan, Chen Chen, Weiming Zhuang, Xin Dong, Lingjuan Lyu, Guodong Long

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

RAIN: RegulArization on Input and Network for Black-Box Domain Adaptation.

Qucheng Peng, Zhengming Ding, Lingjuan Lyu, Lichao Sun, Chen Chen

Proceedings of the Thirty-Second International Joint Conference on Artificial Intelligence, 2023

Byzantine-Robust Learning on Heterogeneous Data via Gradient Splitting.

Yuchen Liu, Chen Chen, Lingjuan Lyu, Fangzhao Wu, Sai Wu, Gang Chen

Proceedings of the International Conference on Machine Learning, 2023

IDEAL: Query-Efficient Data-Free Learning from Black-Box Models.

Jie Zhang, Chen Chen, Lingjuan Lyu

Proceedings of the Eleventh International Conference on Learning Representations, 2023

TARGET: Federated Class-Continual Learning via Exemplar-Free Distillation.

Jie Zhang, Chen Chen, Weiming Zhuang, Lingjuan Lyu

Proceedings of the IEEE/CVF International Conference on Computer Vision, 2023

Towards Adversarially Robust Continual Learning.

Tao Bai, Chen Chen, Lingjuan Lyu, Jun Zhao, Bihan Wen

Proceedings of the IEEE International Conference on Acoustics, 2023

Delving into the Adversarial Robustness of Federated Learning.

Jie Zhang, Bo Li, Chen Chen, Lingjuan Lyu, Shuang Wu, Shouhong Ding, Chao Wu

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

2022

Toward Better Target Representation for Source-Free and Black-Box Domain Adaptation.

Qucheng Peng, Zhengming Ding, Lingjuan Lyu, Lichao Sun, Chen Chen

CoRR, 2022

QEKD: Query-Efficient and Data-Free Knowledge Distillation from Black-box Models.

Jie Zhang, Chen Chen, Jiahua Dong, Ruoxi Jia, Lingjuan Lyu

CoRR, 2022

CalFAT: Calibrated Federated Adversarial Training with Label Skewness.

Chen Chen, Yuchen Liu, Xingjun Ma, Lingjuan Lyu

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

DENSE: Data-Free One-Shot Federated Learning.

Jie Zhang, Chen Chen, Bo Li, Lingjuan Lyu, Shuang Wu, Shouhong Ding, Chunhua Shen, Chao Wu

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

Extracted BERT Model Leaks More Information than You Think!

Xuanli He, Lingjuan Lyu, Chen Chen, Qiongkai Xu

Proceedings of the 2022 Conference on Empirical Methods in Natural Language Processing, 2022

2021

A Practical Data-Free Approach to One-shot Federated Learning with Heterogeneity.

Jie Zhang, Chen Chen, Bo Li, Lingjuan Lyu, Shuang Wu, Jianghe Xu, Shouhong Ding, Chao Wu

CoRR, 2021

A Novel Attribute Reconstruction Attack in Federated Learning.

Lingjuan Lyu, Chen Chen

CoRR, 2021

Guided Interpolation for Adversarial Training.

Chen Chen, Jingfeng Zhang, Xilie Xu, Tianlei Hu, Gang Niu, Gang Chen, Masashi Sugiyama

CoRR, 2021

2020

HAM: a deep collaborative ranking method incorporating textual information.

Chengwei Wang, Tengfei Zhou, Chen Chen, Tianlei Hu, Gang Chen

Frontiers Inf. Technol. Electron. Eng., 2020

Robust Federated Recommendation System.

Chen Chen, Jingfeng Zhang, Anthony K. H. Tung, Mohan S. Kankanhalli, Gang Chen

CoRR, 2020

Online Partial Label Learning.

Haobo Wang, Yuzhou Qiang, Chen Chen, Weiwei Liu, Tianlei Hu, Zhao Li, Gang Chen

Proceedings of the Machine Learning and Knowledge Discovery in Databases, 2020

Off-Policy Recommendation System Without Exploration.

Chengwei Wang, Tengfei Zhou, Chen Chen, Tianlei Hu, Gang Chen

Proceedings of the Advances in Knowledge Discovery and Data Mining, 2020

Incorporating Label Embedding and Feature Augmentation for Multi-Dimensional Classification.

Haobo Wang, Chen Chen, Weiwei Liu, Ke Chen, Tianlei Hu, Gang Chen

Proceedings of the Thirty-Fourth AAAI Conference on Artificial Intelligence, 2020

2019

CAMO: A Collaborative Ranking Method for Content Based Recommendation.

Chengwei Wang, Tengfei Zhou, Chen Chen, Tianlei Hu, Gang Chen

Proceedings of the Thirty-Third AAAI Conference on Artificial Intelligence, 2019

Two-Stage Label Embedding via Neural Factorization Machine for Multi-Label Classification.

Chen Chen, Haobo Wang, Weiwei Liu, Xingyuan Zhao, Tianlei Hu, Gang Chen

Proceedings of the Thirty-Third AAAI Conference on Artificial Intelligence, 2019