Lingjuan Lyu

According to our database, Lingjuan Lyu authored at least 177 papers between 2016 and 2024.

Collaborative distances:

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

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

ResFed: Communication0Efficient Federated Learning With Deep Compressed Residuals.

Rui Song, Liguo Zhou, Lingjuan Lyu, Andreas Festag, Alois Knoll

IEEE Internet Things J., March, 2024

${\sf FederBoost}$: Private Federated Learning for GBDT.

Zhihua Tian, Rui Zhang, Xiaoyang Hou, Lingjuan Lyu, Tianyi Zhang, Jian Liu, Kui Ren

IEEE Trans. Dependable Secur. Comput., 2024

FLoRA: Federated Fine-Tuning Large Language Models with Heterogeneous Low-Rank Adaptations.

Ziyao Wang, Zheyu Shen, Yexiao He, Guoheng Sun, Hongyi Wang, Lingjuan Lyu, Ang Li

CoRR, 2024

RLCP: A Reinforcement Learning-based Copyright Protection Method for Text-to-Image Diffusion Model.

Zhuan Shi, Jing Yan, Xiaoli Tang, Lingjuan Lyu, Boi Faltings

CoRR, 2024

CURE4Rec: A Benchmark for Recommendation Unlearning with Deeper Influence.

Chaochao Chen, Jiaming Zhang, Yizhao Zhang, Li Zhang, Lingjuan Lyu, Yuyuan Li, Biao Gong, Chenggang Yan

CoRR, 2024

FEDMEKI: A Benchmark for Scaling Medical Foundation Models via Federated Knowledge Injection.

Jiaqi Wang, Xiaochen Wang, Lingjuan Lyu, Jinghui Chen, Fenglong Ma

CoRR, 2024

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

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

CoRR, 2024

Detecting, Explaining, and Mitigating Memorization in Diffusion Models.

Yuxin Wen, Yuchen Liu, Chen Chen, Lingjuan Lyu

CoRR, 2024

Stretching Each Dollar: Diffusion Training from Scratch on a Micro-Budget.

Vikash Sehwag, Xianghao Kong, Jingtao Li, Michael Spranger, Lingjuan Lyu

CoRR, 2024

Six-CD: Benchmarking Concept Removals for Benign Text-to-image Diffusion Models.

Jie Ren, Kangrui Chen, Yingqian Cui, Shenglai Zeng, Hui Liu, 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

Towards Fundamentally Scalable Model Selection: Asymptotically Fast Update and Selection.

Wenxiao Wang, Weiming Zhuang, 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

Federated Learning under Partially Class-Disjoint Data via Manifold Reshaping.

Ziqing Fan, Jiangchao Yao, Ruipeng Zhang, Lingjuan Lyu, Ya Zhang, Yanfeng Wang

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

Minimum Topology Attacks for Graph Neural Networks.

Mengmei Zhang, Xiao Wang, Chuan Shi, Lingjuan Lyu, Tianchi Yang, Junping Du

CoRR, 2024

Unveiling the Secrets without Data: Can Graph Neural Networks Be Exploited through Data-Free Model Extraction Attacks?

Yuanxin Zhuang, Chuan Shi, Mengmei Zhang, Jinghui Chen, Lingjuan Lyu, Pan Zhou, Lichao Sun

Proceedings of the 33rd USENIX Security Symposium, 2024

Backdoor Attacks with Input-Unique Triggers in NLP.

Xukun Zhou, Jiwei Li, Tianwei Zhang, Lingjuan Lyu, Muqiao Yang, Jun He

Proceedings of the Machine Learning and Knowledge Discovery in Databases. Research Track, 2024

Defending Against Weight-Poisoning Backdoor Attacks for Parameter-Efficient Fine-Tuning.

Shuai Zhao, Leilei Gan, Anh Tuan Luu, Jie Fu, Lingjuan Lyu, Meihuizi Jia, Jinming Wen

Proceedings of the Findings of the Association for Computational Linguistics: NAACL 2024, 2024

FedSAC: Dynamic Submodel Allocation for Collaborative Fairness in Federated Learning.

Zihui Wang, Zheng Wang, Lingjuan Lyu, Zhaopeng Peng, Zhicheng Yang, Chenglu Wen, Rongshan Yu, Cheng Wang, Xiaoliang Fan

Proceedings of the 30th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, 2024

Protecting Split Learning by Potential Energy Loss.

Fei Zheng, Chaochao Chen, Lingjuan Lyu, Xinyi Fu, Xing Fu, Weiqiang Wang, Xiaolin Zheng, Jianwei Yin

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

PerceptAnon: Exploring the Human Perception of Image Anonymization Beyond Pseudonymization for GDPR.

Kartik Patwari, Chen-Nee Chuah, Lingjuan Lyu, Vivek Sharma

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

Bridging Model Heterogeneity in Federated Learning via Uncertainty-based Asymmetrical Reciprocity Learning.

Jiaqi Wang, Chenxu Zhao, Lingjuan Lyu, Quanzeng You, Mengdi Huai, Fenglong Ma

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

Effective Federated Graph Matching.

Yang Zhou, Zijie Zhang, Zeru Zhang, Lingjuan Lyu, Wei-Shinn Ku

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

FedWon: Triumphing Multi-domain Federated Learning Without Normalization.

Weiming Zhuang, Lingjuan Lyu

Proceedings of the Twelfth International Conference on Learning Representations, 2024

FedP3: Federated Personalized and Privacy-friendly Network Pruning under Model Heterogeneity.

Kai Yi, Nidham Gazagnadou, Peter Richtárik, Lingjuan Lyu

Proceedings of the Twelfth International Conference on Learning Representations, 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

Unveiling and Mitigating Memorization in Text-to-Image Diffusion Models Through Cross Attention.

Jie Ren, Yaxin Li, Shenglai Zeng, Han Xu, Lingjuan Lyu, Yue Xing, Jiliang Tang

Proceedings of the Computer Vision - ECCV 2024, 2024

Finding Needles in a Haystack: A Black-Box Approach to Invisible Watermark Detection.

Minzhou Pan, Zhenting Wang, Xin Dong, Vikash Sehwag, Lingjuan Lyu, Xue Lin

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

Haze Visibility Enhancement for Promoting Traffic Situational Awareness in Vision-Enabled Intelligent Transportation.

Yu Guo, Ryan Wen Liu, Yuxu Lu, Jiangtian Nie, Lingjuan Lyu, Zehui Xiong, Jiawen Kang, Han Yu, Dusit Niyato

IEEE Trans. Veh. Technol., December, 2023

Defending ChatGPT against jailbreak attack via self-reminders.

Yueqi Xie, Jingwei Yi, Jiawei Shao, Justin Curl, Lingjuan Lyu, Qifeng Chen, Xing Xie, Fangzhao Wu

Nat. Mac. Intell., December, 2023

InOR-Net: Incremental 3-D Object Recognition Network for Point Cloud Representation.

Jiahua Dong, Yang Cong, Gan Sun, Lixu Wang, Lingjuan Lyu, Jun Li, Ender Konukoglu

IEEE Trans. Neural Networks Learn. Syst., October, 2023

Traffic Anomaly Prediction Based on Joint Static-Dynamic Spatio-Temporal Evolutionary Learning.

Xiaoming Liu, Zhanwei Zhang, Lingjuan Lyu, Zhaohan Zhang, Shuai Xiao, Chao Shen, Philip S. Yu

IEEE Trans. Knowl. Data Eng., May, 2023

Federated Learning under Partially Disjoint Data via Manifold Reshaping.

Ziqing Fan, Jiangchao Yao, Ruipeng Zhang, Lingjuan Lyu, Yanfeng Wang, Ya Zhang

Trans. Mach. Learn. Res., 2023

Turning a Curse into a Blessing: Enabling In-Distribution-Data-Free Backdoor Removal via Stabilized Model Inversion.

Si Chen, Yi Zeng, Won Park, Jiachen T. Wang, Xun Chen, Lingjuan Lyu, Zhuoqing Mao, Ruoxi Jia

Trans. Mach. Learn. Res., 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

Correction to "Privacy-Preserving Blockchain-Based Federated Learning for IoT Devices".

Yang Zhao, Jun Zhao, Linshan Jiang, Rui Tan, Dusit Niyato, Zengxiang Li, Lingjuan Lyu, Yingbo Liu

IEEE Internet Things J., 2023

EdgeDis: Enabling Fast, Economical, and Reliable Data Dissemination for Mobile Edge Computing.

Bo Li, Qiang He, Feifei Chen, Lingjuan Lyu, Athman Bouguettaya, Yun Yang

CoRR, 2023

Privacy-preserving design of graph neural networks with applications to vertical federated learning.

Ruofan Wu, Mingyang Zhang, Lingjuan Lyu, Xiaolong Xu, Xiuquan Hao, Xinyi Fu, Tengfei Liu, Tianyi Zhang, Weiqiang Wang

CoRR, 2023

FROD: Robust Object Detection for Free.

Muhammad Awais, Weiming Zhuang, Lingjuan Lyu, Sung-Ho Bae

CoRR, 2023

Federated Learning over a Wireless Network: Distributed User Selection through Random Access.

Chen Sun, Shiyao Ma, Ce Zheng, Songtao Wu, Tao Cui, Lingjuan Lyu

CoRR, 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

Pushing the Limits of ChatGPT on NLP Tasks.

Xiaofei Sun, Linfeng Dong, Xiaoya Li, Zhen Wan, Shuhe Wang, Tianwei Zhang, Jiwei Li, Fei Cheng, Lingjuan Lyu, Fei Wu, Guoyin Wang

CoRR, 2023

Is Normalization Indispensable for Multi-domain Federated Learning?

Weiming Zhuang, 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

V2X-Boosted Federated Learning for Cooperative Intelligent Transportation Systems with Contextual Client Selection.

Rui Song, Lingjuan Lyu, Wei Jiang, Andreas Festag, Alois C. Knoll

CoRR, 2023

DADFNet: Dual Attention and Dual Frequency-Guided Dehazing Network for Video-Empowered Intelligent Transportation.

Yu Guo, Ryan Wen Liu, Jiangtian Nie, Lingjuan Lyu, Zehui Xiong, Jiawen Kang, Han Yu, Dusit Niyato

CoRR, 2023

A Pathway Towards Responsible AI Generated Content.

Chen Chen, Jie Fu, Lingjuan Lyu

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

InOR-Net: Incremental 3D Object Recognition Network for Point Cloud Representation.

Jiahua Dong, Yang Cong, Gan Sun, Lixu Wang, Lingjuan Lyu, Jun Li, Ender Konukoglu

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

SplitGNN: Splitting GNN for Node Classification with Heterogeneous Attention.

Xiaolong Xu, Lingjuan Lyu, Yihong Dong, Yicheng Lu, Weiqiang Wang, Hong Jin

CoRR, 2023

Differentially private locality sensitive hashing based federated recommender system.

Hongsheng Hu, Gillian Dobbie, Zoran Salcic, Meng Liu, Jianbing Zhang, Lingjuan Lyu, Xuyun Zhang

Concurr. Comput. Pract. Exp., 2023

Minimum Topology Attacks for Graph Neural Networks.

Mengmei Zhang, Xiao Wang, Chuan Shi, Lingjuan Lyu, Tianchi Yang, Junping Du

Proceedings of the ACM Web Conference 2023, 2023

Multiple-Agent Deep Reinforcement Learning for Avatar Migration in Vehicular Metaverses.

Junlong Chen, Jiangtian Nie, Minrui Xu, Lingjuan Lyu, Zehui Xiong, Jiawen Kang, Yongju Tong, Wenchao Jiang

Proceedings of the Companion Proceedings of the ACM Web Conference 2023, 2023

Meta-Sift: How to Sift Out a Clean Subset in the Presence of Data Poisoning?

Yi Zeng, Minzhou Pan, Himanshu Jahagirdar, Ming Jin, Lingjuan Lyu, Ruoxi Jia

Proceedings of the 32nd USENIX Security Symposium, 2023

ASSET: Robust Backdoor Data Detection Across a Multiplicity of Deep Learning Paradigms.

Minzhou Pan, Yi Zeng, Lingjuan Lyu, Xue Lin, Ruoxi Jia

Proceedings of the 32nd USENIX Security Symposium, 2023

Towards Personalized Federated Learning via Heterogeneous Model Reassembly.

Jiaqi Wang, Xingyi Yang, Suhan Cui, Liwei Che, Lingjuan Lyu, Dongkuan Xu, Fenglong Ma

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

Privacy Assessment on Reconstructed Images: Are Existing Evaluation Metrics Faithful to Human Perception?

Xiaoxiao Sun, Nidham Gazagnadou, Vivek Sharma, Lingjuan Lyu, Hongdong Li, Liang Zheng

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

UltraRE: Enhancing RecEraser for Recommendation Unlearning via Error Decomposition.

Yuyuan Li, Chaochao Chen, Yizhao Zhang, Weiming Liu, Lingjuan Lyu, Xiaolin Zheng, Dan Meng, Jun Wang

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

PrivateRec: Differentially Private Model Training and Online Serving for Federated News Recommendation.

Ruixuan Liu, Yang Cao, Yanlin Wang, Lingjuan Lyu, Yun Chen, Hong Chen

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

Reducing Communication for Split Learning by Randomized Top-k Sparsification.

Fei Zheng, Chaochao Chen, Lingjuan Lyu, Binhui Yao

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

FedSampling: A Better Sampling Strategy for Federated Learning.

Tao Qi, Fangzhao Wu, Lingjuan Lyu, Yongfeng Huang, Xing Xie

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

A Pathway Towards Responsible AI Generated Content.

Lingjuan Lyu

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

Reconstructive Neuron Pruning for Backdoor Defense.

Yige Li, Xixiang Lyu, Xingjun Ma, Nodens Koren, Lingjuan Lyu, Bo Li, Yu-Gang Jiang

Proceedings of the International Conference on Machine Learning, 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

Fast Federated Machine Unlearning with Nonlinear Functional Theory.

Tianshi Che, Yang Zhou, Zijie Zhang, Lingjuan Lyu, Ji Liu, Da Yan, Dejing Dou, Jun Huan

Proceedings of the International Conference on Machine Learning, 2023

Dimension-independent Certified Neural Network Watermarks via Mollifier Smoothing.

Jiaxiang Ren, Yang Zhou, Jiayin Jin, Lingjuan Lyu, Da Yan

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

Towards Robustness Certification Against Universal Perturbations.

Yi Zeng, Zhouxing Shi, Ming Jin, Feiyang Kang, Lingjuan Lyu, Cho-Jui Hsieh, Ruoxi Jia

Proceedings of the Eleventh International Conference on Learning Representations, 2023

Deja Vu: Continual Model Generalization for Unseen Domains.

Chenxi Liu, Lixu Wang, Lingjuan Lyu, Chen Sun, Xiao Wang, Qi Zhu

Proceedings of the Eleventh International Conference on Learning Representations, 2023

MocoSFL: enabling cross-client collaborative self-supervised learning.

Jingtao Li, Lingjuan Lyu, Daisuke Iso, Chaitali Chakrabarti, Michael Spranger

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

MAS: Towards Resource-Efficient Federated Multiple-Task Learning.

Weiming Zhuang, Yonggang Wen, Lingjuan Lyu, Shuai Zhang

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

The Perils of Learning From Unlabeled Data: Backdoor Attacks on Semi-supervised Learning.

Virat Shejwalkar, Lingjuan Lyu, Amir Houmansadr

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

Narcissus: A Practical Clean-Label Backdoor Attack with Limited Information.

Yi Zeng, Minzhou Pan, Hoang Anh Just, Lingjuan Lyu, Meikang Qiu, Ruoxi Jia

Proceedings of the 2023 ACM SIGSAC Conference on Computer and Communications Security, 2023

GNN-SL: Sequence Labeling Based on Nearest Examples via GNN.

Shuhe Wang, Yuxian Meng, Rongbin Ouyang, Jiwei Li, Tianwei Zhang, Lingjuan Lyu, Guoyin Wang

Proceedings of the Findings of the Association for Computational Linguistics: ACL 2023, 2023

Are You Copying My Model? Protecting the Copyright of Large Language Models for EaaS via Backdoor Watermark.

Wenjun Peng, Jingwei Yi, Fangzhao Wu, Shangxi Wu, Bin Zhu, Lingjuan Lyu, Binxing Jiao, Tong Xu, Guangzhong Sun, Xing Xie

Proceedings of the 61st Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), 2023

Defending against Backdoor Attacks in Natural Language Generation.

Xiaofei Sun, Xiaoya Li, Yuxian Meng, Xiang Ao, Lingjuan Lyu, Jiwei Li, Tianwei Zhang

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

Joint Stance and Rumor Detection in Hierarchical Heterogeneous Graph.

Chen Li, Hao Peng, Jianxin Li, Lichao Sun, Lingjuan Lyu, Lihong Wang, Philip S. Yu, Lifang He

IEEE Trans. Neural Networks Learn. Syst., 2022

FedCTR: Federated Native Ad CTR Prediction with Cross-platform User Behavior Data.

Chuhan Wu, Fangzhao Wu, Lingjuan Lyu, Yongfeng Huang, Xing Xie

ACM Trans. Intell. Syst. Technol., 2022

FedBERT: When Federated Learning Meets Pre-training.

Yuanyishu Tian, Yao Wan, Lingjuan Lyu, Dezhong Yao, Hai Jin, Lichao Sun

ACM Trans. Intell. Syst. Technol., 2022

Privacy-Preserving Anomaly Detection in Cloud Manufacturing Via Federated Transformer.

Shiyao Ma, Jiangtian Nie, Jiawen Kang, Lingjuan Lyu, Ryan Wen Liu, Ruihui Zhao, Ziyao Liu, Dusit Niyato

IEEE Trans. Ind. Informatics, 2022

FLEAM: A Federated Learning Empowered Architecture to Mitigate DDoS in Industrial IoT.

Jianhua Li, Lingjuan Lyu, Ximeng Liu, Xuyun Zhang, Xixiang Lyu

IEEE Trans. Ind. Informatics, 2022

How to Democratise and Protect AI: Fair and Differentially Private Decentralised Deep Learning.

Lingjuan Lyu, Yitong Li, Karthik Nandakumar, Jiangshan Yu, Xingjun Ma

IEEE Trans. Dependable Secur. Comput., 2022

Cloud-Based Privacy-Preserving Collaborative Consumption for Sharing Economy.

Lingjuan Lyu, Sid Chi-Kin Chau, Nan Wang, Yifeng Zheng

IEEE Trans. Cloud Comput., 2022

Data Poisoning Attacks on Federated Machine Learning.

Gan Sun, Yang Cong, Jiahua Dong, Qiang Wang, Lingjuan Lyu, Ji Liu

IEEE Internet Things J., 2022

ResFed: Communication Efficient Federated Learning by Transmitting Deep Compressed Residuals.

Rui Song, Liguo Zhou, Lingjuan Lyu, Andreas Festag, Alois C. Knoll

CoRR, 2022

How to Sift Out a Clean Data Subset in the Presence of Data Poisoning?

Yi Zeng, Minzhou Pan, Himanshu Jahagirdar, Ming Jin, Lingjuan Lyu, Ruoxi Jia

CoRR, 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

FairVFL: A Fair Vertical Federated Learning Framework with Contrastive Adversarial Learning.

Tao Qi, Fangzhao Wu, Chuhan Wu, Lingjuan Lyu, Tong Xu, Zhongliang Yang, Yongfeng Huang, Xing Xie

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

PrivateRec: Differentially Private Training and Serving for Federated News Recommendation.

Ruixuan Liu, Fangzhao Wu, Chuhan Wu, Yanlin Wang, Yang Cao, Lingjuan Lyu, Weike Pan, Yun Chen, Hong Chen, Xing Xie

CoRR, 2022

Exploiting Data Sparsity in Secure Cross-Platform Social Recommendation.

Jamie Cui, Chaochao Chen, Lingjuan Lyu, Carl Yang, Li Wang

CoRR, 2022

Threats to Pre-trained Language Models: Survey and Taxonomy.

Shangwei Guo, Chunlong Xie, Jiwei Li, Lingjuan Lyu, Tianwei Zhang

CoRR, 2022

Differential Private Knowledge Transfer for Privacy-Preserving Cross-Domain Recommendation.

Chaochao Chen, Huiwen Wu, Jiajie Su, Lingjuan Lyu, Xiaolin Zheng, Li Wang

Proceedings of the WWW '22: The ACM Web Conference 2022, Virtual Event, Lyon, France, April 25, 2022

Prompt Certified Machine Unlearning with Randomized Gradient Smoothing and Quantization.

Zijie Zhang, Yang Zhou, Xin Zhao, Tianshi Che, Lingjuan Lyu

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

FairVFL: A Fair Vertical Federated Learning Framework with Contrastive Adversarial Learning.

Tao Qi, Fangzhao Wu, Chuhan Wu, Lingjuan Lyu, Tong Xu, Hao Liao, Zhongliang Yang, Yongfeng Huang, Xing Xie

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

CATER: Intellectual Property Protection on Text Generation APIs via Conditional Watermarks.

Xuanli He, Qiongkai Xu, Yi Zeng, Lingjuan Lyu, Fangzhao Wu, Jiwei Li, Ruoxi Jia

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

No One Left Behind: Inclusive Federated Learning over Heterogeneous Devices.

Ruixuan Liu, Fangzhao Wu, Chuhan Wu, Yanlin Wang, Lingjuan Lyu, Hong Chen, Xing Xie

Proceedings of the KDD '22: The 28th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, Washington, DC, USA, August 14, 2022

EdgeWatch: Collaborative Investigation of Data Integrity at the Edge based on Blockchain.

Bo Li, Qiang He, Liang Yuan, Feifei Chen, Lingjuan Lyu, Yun Yang

Proceedings of the KDD '22: The 28th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, Washington, DC, USA, August 14, 2022

Data-Free Adversarial Knowledge Distillation for Graph Neural Networks.

Yuanxin Zhuang, Lingjuan Lyu, Chuan Shi, Carl Yang, Lichao Sun

Proceedings of the Thirty-First International Joint Conference on Artificial Intelligence, 2022

Vertically Federated Graph Neural Network for Privacy-Preserving Node Classification.

Chaochao Chen, Jun Zhou, Longfei Zheng, Huiwen Wu, Lingjuan Lyu, Jia Wu, Bingzhe Wu, Ziqi Liu, Li Wang, Xiaolin Zheng

Proceedings of the Thirty-First International Joint Conference on Artificial Intelligence, 2022

Accelerated Federated Learning with Decoupled Adaptive Optimization.

Jiayin Jin, Jiaxiang Ren, Yang Zhou, Lingjuan Lyu, Ji Liu, Dejing Dou

Proceedings of the International Conference on Machine Learning, 2022

Privacy for Free: How does Dataset Condensation Help Privacy?

Tian Dong, Bo Zhao, Lingjuan Lyu

Proceedings of the International Conference on Machine Learning, 2022

How to Inject Backdoors with Better Consistency: Logit Anchoring on Clean Data.

Zhiyuan Zhang, Lingjuan Lyu, Weiqiang Wang, Lichao Sun, Xu Sun

Proceedings of the Tenth International Conference on Learning Representations, 2022

FedSkip: Combatting Statistical Heterogeneity with Federated Skip Aggregation.

Ziqing Fan, Yanfeng Wang, Jiangchao Yao, Lingjuan Lyu, Ya Zhang, Qi Tian

Proceedings of the IEEE International Conference on Data Mining, 2022

Heterogeneous Graph Node Classification With Multi-Hops Relation Features.

Xiaolong Xu, Lingjuan Lyu, Hong Jin, Weiqiang Wang, Shuo Jia

Proceedings of the IEEE International Conference on Acoustics, 2022

Fine-mixing: Mitigating Backdoors in Fine-tuned Language Models.

Zhiyuan Zhang, Lingjuan Lyu, Xingjun Ma, Chenguang Wang, Xu Sun

Proceedings of the Findings of the Association for Computational Linguistics: EMNLP 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

Student Surpasses Teacher: Imitation Attack for Black-Box NLP APIs.

Qiongkai Xu, Xuanli He, Lingjuan Lyu, Lizhen Qu, Gholamreza Haffari

Proceedings of the 29th International Conference on Computational Linguistics, 2022

The 1st International Workshop on Federated Learning with Graph Data (FedGraph).

Carl Yang, Xiaoxiao Li, Nathalie Baracaldo, Neil Shah, Chaoyang He, Lingjuan Lyu, Lichao Sun, Salman Avestimehr

Proceedings of the 31st ACM International Conference on Information & Knowledge Management, 2022

Cross-Network Social User Embedding with Hybrid Differential Privacy Guarantees.

Jiaqian Ren, Lei Jiang, Hao Peng, Lingjuan Lyu, Zhiwei Liu, Chaochao Chen, Jia Wu, Xu Bai, Philip S. Yu

Proceedings of the 31st ACM International Conference on Information & Knowledge Management, 2022

Protecting Intellectual Property of Language Generation APIs with Lexical Watermark.

Xuanli He, Qiongkai Xu, Lingjuan Lyu, Fangzhao Wu, Chenguang Wang

Proceedings of the Thirty-Sixth AAAI Conference on Artificial Intelligence, 2022

2021

Clustering-based Efficient Privacy-preserving Face Recognition Scheme without Compromising Accuracy.

Meng Liu, Hongsheng Hu, Haolong Xiang, Chi Yang, Lingjuan Lyu, Xuyun Zhang

ACM Trans. Sens. Networks, 2021

Local Differential Privacy-Based Federated Learning for Internet of Things.

Yang Zhao, Jun Zhao, Mengmeng Yang, Teng Wang, Ning Wang, Lingjuan Lyu, Dusit Niyato, Kwok-Yan Lam

IEEE Internet Things J., 2021

Privacy-Preserving Blockchain-Based Federated Learning for IoT Devices.

Yang Zhao, Jun Zhao, Linshan Jiang, Rui Tan, Dusit Niyato, Zengxiang Li, Lingjuan Lyu, Yingbo Liu

IEEE Internet Things J., 2021

A fast and scalable authentication scheme in IOT for smart living.

Jianhua Li, Jiong Jin, Lingjuan Lyu, Dong Yuan, Yingying Yang, Longxiang Gao, Chao Shen

Future Gener. Comput. Syst., 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

Beyond Model Extraction: Imitation Attack for Black-Box NLP APIs.

Qiongkai Xu, Xuanli He, Lingjuan Lyu, Lizhen Qu, Gholamreza Haffari

CoRR, 2021

FedKD: Communication Efficient Federated Learning via Knowledge Distillation.

Chuhan Wu, Fangzhao Wu, Ruixuan Liu, Lingjuan Lyu, Yongfeng Huang, Xing Xie

CoRR, 2021

A Novel Attribute Reconstruction Attack in Federated Learning.

Lingjuan Lyu, Chen Chen

CoRR, 2021

A Vertical Federated Learning Framework for Graph Convolutional Network.

Xiang Ni, Xiaolong Xu, Lingjuan Lyu, Changhua Meng, Weiqiang Wang

CoRR, 2021

Killing Two Birds with One Stone: Stealing Model and Inferring Attribute from BERT-based APIs.

Lingjuan Lyu, Xuanli He, Fangzhao Wu, Lichao Sun

CoRR, 2021

DP-SIGNSGD: When Efficiency Meets Privacy and Robustness.

Lingjuan Lyu

CoRR, 2021

Robust Training Using Natural Transformation.

Shuo Wang, Lingjuan Lyu, Surya Nepal, Carsten Rudolph, Marthie Grobler, Kristen Moore

CoRR, 2021

Gradient Driven Rewards to Guarantee Fairness in Collaborative Machine Learning.

Xinyi Xu, Lingjuan Lyu, Xingjun Ma, Chenglin Miao, Chuan Sheng Foo, Bryan Kian Hsiang Low

Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

Anti-Backdoor Learning: Training Clean Models on Poisoned Data.

Yige Li, Xixiang Lyu, Nodens Koren, Lingjuan Lyu, Bo Li, Xingjun Ma

Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

Exploiting Data Sparsity in Secure Cross-Platform Social Recommendation.

Jinming Cui, Chaochao Chen, Lingjuan Lyu, Carl Yang, Li Wang

Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

Model Extraction and Adversarial Transferability, Your BERT is Vulnerable!

Xuanli He, Lingjuan Lyu, Lichao Sun, Qiongkai Xu

Proceedings of the 2021 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, 2021

Federated Model Distillation with Noise-Free Differential Privacy.

Lichao Sun, Lingjuan Lyu

Proceedings of the Thirtieth International Joint Conference on Artificial Intelligence, 2021

Neural Attention Distillation: Erasing Backdoor Triggers from Deep Neural Networks.

Yige Li, Xixiang Lyu, Nodens Koren, Lingjuan Lyu, Bo Li, Xingjun Ma

Proceedings of the 9th International Conference on Learning Representations, 2021

Privacy-Preserving Optimal Insulin Dosing Decision.

Zuobin Ying, Shuanglong Cao, Shengmin Xu, Ximeng Liu, Lingjuan Lyu, Cen Chen, Li Wang

Proceedings of the IEEE International Conference on Acoustics, 2021

Reliable and Privacy-Preserving Task Matching in Blockchain-Based Crowdsourcing.

Baolai Wang, Shaojing Fu, Xuyun Zhang, Tao Xie, Lingjuan Lyu, Yuchuan Luo

Proceedings of the CIKM '21: The 30th ACM International Conference on Information and Knowledge Management, Virtual Event, Queensland, Australia, November 1, 2021

2020

Collaborative Fairness in Federated Learning.

Lingjuan Lyu, Xinyi Xu, Qian Wang, Han Yu

Proceedings of the Federated Learning - Privacy and Incentive, 2020

Threats to Federated Learning.

Lingjuan Lyu, Han Yu, Jun Zhao, Qiang Yang

Proceedings of the Federated Learning - Privacy and Incentive, 2020

Towards Fair and Privacy-Preserving Federated Deep Models.

Lingjuan Lyu, Jiangshan Yu, Karthik Nandakumar, Yitong Li, Xingjun Ma, Jiong Jin, Han Yu, Kee Siong Ng

IEEE Trans. Parallel Distributed Syst., 2020

FORESEEN: Towards Differentially Private Deep Inference for Intelligent Internet of Things.

Lingjuan Lyu, James C. Bezdek, Jiong Jin, Yang Yang

IEEE J. Sel. Areas Commun., 2020

Privacy and Robustness in Federated Learning: Attacks and Defenses.

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

CoRR, 2020

Towards Building a Robust and Fair Federated Learning System.

Xinyi Xu, Lingjuan Lyu

CoRR, 2020

Collaborative Fairness in Federated Learning.

Lingjuan Lyu, Xinyi Xu, Qian Wang

CoRR, 2020

Local Differential Privacy and Its Applications: A Comprehensive Survey.

Mengmeng Yang, Lingjuan Lyu, Jun Zhao, Tianqing Zhu, Kwok-Yan Lam

CoRR, 2020

Threats to Federated Learning: A Survey.

Lingjuan Lyu, Han Yu, Qiang Yang

CoRR, 2020

An Unsupervised PM2.5 Estimation Method With Different Spatio-Temporal Resolutions Based on KIDW-TCGRU.

Canyang Guo, Genggeng Liu, Lingjuan Lyu, Chi-Hua Chen

IEEE Access, 2020

Contour Accentuation for Transfer Learning-Based Ship Recognition Method.

Chi-Hua Chen, Yizhuo Zhang, Wenzhong Guo, Mingyang Pan, Lingjuan Lyu, Chia-Yu Lin

Proceedings of the Companion of The 2020 Web Conference 2020, 2020

Privacy-Preserving Data Generation and Sharing Using Identification Sanitizer.

Shuo Wang, Lingjuan Lyu, Tianle Chen, Shangyu Chen, Surya Nepal, Carsten Rudolph, Marthie Grobler

Proceedings of the Web Information Systems Engineering - WISE 2020, 2020

Towards Distributed Privacy-Preserving Prediction.

Lingjuan Lyu, Yee Wei Law, Kee Siong Ng, Shibei Xue, Jun Zhao, Mengmeng Yang, Lei Liu

Proceedings of the 2020 IEEE International Conference on Systems, Man, and Cybernetics, 2020

Towards Differentially Private Text Representations.

Lingjuan Lyu, Yitong Li, Xuanli He, Tong Xiao

Proceedings of the 43rd International ACM SIGIR conference on research and development in Information Retrieval, 2020

Differentially Private Knowledge Distillation for Mobile Analytics.

Lingjuan Lyu, Chi-Hua Chen

Proceedings of the 43rd International ACM SIGIR conference on research and development in Information Retrieval, 2020

Lightweight Crypto-Assisted Distributed Differential Privacy for Privacy-Preserving Distributed Learning.

Lingjuan Lyu

Proceedings of the 2020 International Joint Conference on Neural Networks, 2020

Differentially Private Representation for NLP: Formal Guarantee and An Empirical Study on Privacy and Fairness.

Lingjuan Lyu, Xuanli He, Yitong Li

Proceedings of the Findings of the Association for Computational Linguistics: EMNLP 2020, 2020

2019

Fog-Embedded Deep Learning for the Internet of Things.

Lingjuan Lyu, James C. Bezdek, Xuanli He, Jiong Jin

IEEE Trans. Ind. Informatics, 2019

Distributed Privacy-Preserving Prediction.

Lingjuan Lyu, Yee Wei Law, Kee Siong Ng

CoRR, 2019

Towards Fair and Decentralized Privacy-Preserving Deep Learning with Blockchain.

Lingjuan Lyu, Jiangshan Yu, Karthik Nandakumar, Yitong Li, Xingjun Ma, Jiong Jin

CoRR, 2019

2018

PPFA: Privacy Preserving Fog-Enabled Aggregation in Smart Grid.

Lingjuan Lyu, Karthik Nandakumar, Benjamin I. P. Rubinstein, Jiong Jin, Justin Bedo, Marimuthu Palaniswami

IEEE Trans. Ind. Informatics, 2018

Privacy-preserving collaborative fuzzy clustering.

Lingjuan Lyu, James C. Bezdek, Yee Wei Law, Xuanli He, Marimuthu Palaniswami

Data Knowl. Eng., 2018

2017

Fog-Empowered Anomaly Detection in IoT Using Hyperellipsoidal Clustering.

Lingjuan Lyu, Jiong Jin, Sutharshan Rajasegarar, Xuanli He, Marimuthu Palaniswami

IEEE Internet Things J., 2017

Privacy-Preserving Aggregation of Smart Metering via Transformation and Encryption.

Lingjuan Lyu, Yee Wei Law, Jiong Jin, Marimuthu Palaniswami

Proceedings of the 2017 IEEE Trustcom/BigDataSE/ICESS, Sydney, Australia, August 1-4, 2017, 2017

Privacy-Preserving Collaborative Deep Learning with Application to Human Activity Recognition.

Lingjuan Lyu, Xuanli He, Yee Wei Law, Marimuthu Palaniswami

Proceedings of the 2017 ACM on Conference on Information and Knowledge Management, 2017

2016

An improved scheme for privacy-preserving collaborative anomaly detection.

Lingjuan Lyu, Yee Wei Law, Sarah M. Erfani, Christopher Leckie, Marimuthu Palaniswami

Proceedings of the 2016 IEEE International Conference on Pervasive Computing and Communication Workshops, 2016