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2020 – today
- 2024
[j31]Rui Song
, Liguo Zhou, Lingjuan Lyu, Andreas Festag, Alois Knoll:
ResFed: Communication0Efficient Federated Learning With Deep Compressed Residuals. IEEE Internet Things J. 11(6): 9458-9472 (2024)- [j30]Zhihua Tian, Rui Zhang, Xiaoyang Hou, Lingjuan Lyu, Tianyi Zhang, Jian Liu, Kui Ren:
${\sf FederBoost}$: Private Federated Learning for GBDT. IEEE Trans. Dependable Secur. Comput. 21(3): 1274-1285 (2024) - [j29]Lingjuan Lyu, Han Yu, Xingjun Ma, Chen Chen, Lichao Sun, Jun Zhao, Qiang Yang, Philip S. Yu:
Privacy and Robustness in Federated Learning: Attacks and Defenses. IEEE Trans. Neural Networks Learn. Syst. 35(7): 8726-8746 (2024) - [c90]Hong Huang, Weiming Zhuang, Chen Chen, Lingjuan Lyu:
FedMef: Towards Memory-Efficient Federated Dynamic Pruning. CVPR 2024: 27538-27547 - [c89]Minzhou Pan, Zhenting Wang, Xin Dong, Vikash Sehwag, Lingjuan Lyu, Xue Lin:
Finding Needles in a Haystack: A Black-Box Approach to Invisible Watermark Detection. ECCV (33) 2024: 253-270 - [c88]Zhenting Wang, Chen Chen, Lingjuan Lyu, Dimitris N. Metaxas, Shiqing Ma:
DIAGNOSIS: Detecting Unauthorized Data Usages in Text-to-image Diffusion Models. ICLR 2024 - [c87]Yuxin Wen, Yuchen Liu, Chen Chen, Lingjuan Lyu:
Detecting, Explaining, and Mitigating Memorization in Diffusion Models. ICLR 2024 - [c86]Kai Yi, Nidham Gazagnadou, Peter Richtárik, Lingjuan Lyu:
FedP3: Federated Personalized and Privacy-friendly Network Pruning under Model Heterogeneity. ICLR 2024 - [c85]Weiming Zhuang, Lingjuan Lyu:
FedWon: Triumphing Multi-domain Federated Learning Without Normalization. ICLR 2024 - [c84]Yang Zhou, Zijie Zhang, Zeru Zhang, Lingjuan Lyu, Wei-Shinn Ku:
Effective Federated Graph Matching. ICML 2024 - [c83]Jiaqi Wang, Chenxu Zhao, Lingjuan Lyu, Quanzeng You, Mengdi Huai, Fenglong Ma:
Bridging Model Heterogeneity in Federated Learning via Uncertainty-based Asymmetrical Reciprocity Learning. ICML 2024 - [c82]Kartik Patwari, Chen-Nee Chuah, Lingjuan Lyu, Vivek Sharma:
PerceptAnon: Exploring the Human Perception of Image Anonymization Beyond Pseudonymization for GDPR. ICML 2024 - [c81]Zhenting Wang, Vikash Sehwag, Chen Chen, Lingjuan Lyu, Dimitris N. Metaxas, Shiqing Ma:
How to Trace Latent Generative Model Generated Images without Artificial Watermark? ICML 2024 - [c80]Weiming Zhuang, Jian Xu, Chen Chen, Jingtao Li, Lingjuan Lyu:
COALA: A Practical and Vision-Centric Federated Learning Platform. ICML 2024 - [c79]Fei Zheng, Chaochao Chen, Lingjuan Lyu, Xinyi Fu, Xing Fu, Weiqiang Wang, Xiaolin Zheng, Jianwei Yin:
Protecting Split Learning by Potential Energy Loss. IJCAI 2024: 5590-5598 - [c78]Zihui Wang, Zheng Wang, Lingjuan Lyu, Zhaopeng Peng, Zhicheng Yang, Chenglu Wen, Rongshan Yu, Cheng Wang, Xiaoliang Fan:
FedSAC: Dynamic Submodel Allocation for Collaborative Fairness in Federated Learning. KDD 2024: 3299-3310 - [c77]Shuai Zhao, Leilei Gan, Anh Tuan Luu, Jie Fu, Lingjuan Lyu, Meihuizi Jia, Jinming Wen:
Defending Against Weight-Poisoning Backdoor Attacks for Parameter-Efficient Fine-Tuning. NAACL-HLT (Findings) 2024: 3421-3438 - [c76]Xukun Zhou, Jiwei Li, Tianwei Zhang, Lingjuan Lyu, Muqiao Yang, Jun He:
Backdoor Attacks with Input-Unique Triggers in NLP. ECML/PKDD (1) 2024: 296-312 - [c75]Yuanxin Zhuang, Chuan Shi, Mengmei Zhang, Jinghui Chen, Lingjuan Lyu, Pan Zhou, Lichao Sun:
Unveiling the Secrets without Data: Can Graph Neural Networks Be Exploited through Data-Free Model Extraction Attacks? USENIX Security Symposium 2024 - [i104]Shuai Zhao, Leilei Gan, Luu Anh Tuan, Jie Fu, Lingjuan Lyu, Meihuizi Jia, Jinming Wen:
Defending Against Weight-Poisoning Backdoor Attacks for Parameter-Efficient Fine-Tuning. CoRR abs/2402.12168 (2024) - [i103]Mengmei Zhang, Xiao Wang, Chuan Shi, Lingjuan Lyu, Tianchi Yang, Junping Du:
Minimum Topology Attacks for Graph Neural Networks. CoRR abs/2403.02723 (2024) - [i102]Jie Ren, Yaxin Li, Shenglai Zeng, Han Xu, Lingjuan Lyu, Yue Xing, Jiliang Tang:
Unveiling and Mitigating Memorization in Text-to-image Diffusion Models through Cross Attention. CoRR abs/2403.11052 (2024) - [i101]Hong Huang, Weiming Zhuang, Chen Chen, Lingjuan Lyu:
FedMef: Towards Memory-efficient Federated Dynamic Pruning. CoRR abs/2403.14737 (2024) - [i100]Minzhou Pan, Zhenting Wang, Xin Dong, Vikash Sehwag, Lingjuan Lyu, Xue Lin:
Finding needles in a haystack: A Black-Box Approach to Invisible Watermark Detection. CoRR abs/2403.15955 (2024) - [i99]Yuhang Li, Xin Dong, Chen Chen, Jingtao Li, Yuxin Wen, Michael Spranger, Lingjuan Lyu:
Is Synthetic Image Useful for Transfer Learning? An Investigation into Data Generation, Volume, and Utilization. CoRR abs/2403.19866 (2024) - [i98]Kai Yi, Nidham Gazagnadou, Peter Richtárik, Lingjuan Lyu:
FedP3: Federated Personalized and Privacy-friendly Network Pruning under Model Heterogeneity. CoRR abs/2404.09816 (2024) - [i97]Zhenting Wang, Vikash Sehwag, Chen Chen, Lingjuan Lyu, Dimitris N. Metaxas, Shiqing Ma:
How to Trace Latent Generative Model Generated Images without Artificial Watermark? CoRR abs/2405.13360 (2024) - [i96]Zihui Wang, Zheng Wang, Lingjuan Lyu, Zhaopeng Peng, Zhicheng Yang, Chenglu Wen, Rongshan Yu, Cheng Wang, Xiaoliang Fan:
FedSAC: Dynamic Submodel Allocation for Collaborative Fairness in Federated Learning. CoRR abs/2405.18291 (2024) - [i95]Ziqing Fan, Jiangchao Yao, Ruipeng Zhang, Lingjuan Lyu, Ya Zhang, Yanfeng Wang:
Federated Learning under Partially Class-Disjoint Data via Manifold Reshaping. CoRR abs/2405.18983 (2024) - [i94]Zhenting Wang, Chen Chen, Vikash Sehwag, Minzhou Pan, Lingjuan Lyu:
Evaluating and Mitigating IP Infringement in Visual Generative AI. CoRR abs/2406.04662 (2024) - [i93]Wenxiao Wang, Weiming Zhuang, Lingjuan Lyu:
Towards Fundamentally Scalable Model Selection: Asymptotically Fast Update and Selection. CoRR abs/2406.07536 (2024) - [i92]Jie Ren, Yingqian Cui, Chen Chen, Vikash Sehwag, Yue Xing, Jiliang Tang, Lingjuan Lyu:
EnTruth: Enhancing the Traceability of Unauthorized Dataset Usage in Text-to-image Diffusion Models with Minimal and Robust Alterations. CoRR abs/2406.13933 (2024) - [i91]Jie Ren, Kangrui Chen, Yingqian Cui, Shenglai Zeng, Hui Liu, Yue Xing, Jiliang Tang, Lingjuan Lyu:
Six-CD: Benchmarking Concept Removals for Benign Text-to-image Diffusion Models. CoRR abs/2406.14855 (2024) - [i90]Jiaqi Wang, Chenxu Zhao, Lingjuan Lyu, Quanzeng You, Mengdi Huai, Fenglong Ma:
Bridging Model Heterogeneity in Federated Learning via Uncertainty-based Asymmetrical Reciprocity Learning. CoRR abs/2407.03247 (2024) - [i89]Vikash Sehwag, Xianghao Kong, Jingtao Li, Michael Spranger, Lingjuan Lyu:
Stretching Each Dollar: Diffusion Training from Scratch on a Micro-Budget. CoRR abs/2407.15811 (2024) - [i88]Weiming Zhuang, Jian Xu, Chen Chen, Jingtao Li, Lingjuan Lyu:
COALA: A Practical and Vision-Centric Federated Learning Platform. CoRR abs/2407.16560 (2024) - [i87]Yuxin Wen, Yuchen Liu, Chen Chen, Lingjuan Lyu:
Detecting, Explaining, and Mitigating Memorization in Diffusion Models. CoRR abs/2407.21720 (2024) - [i86]Yuhang Li, Xin Dong, Chen Chen, Weiming Zhuang, Lingjuan Lyu:
A Simple Background Augmentation Method for Object Detection with Diffusion Model. CoRR abs/2408.00350 (2024) - [i85]Jiaqi Wang, Xiaochen Wang, Lingjuan Lyu, Jinghui Chen, Fenglong Ma:
FEDMEKI: A Benchmark for Scaling Medical Foundation Models via Federated Knowledge Injection. CoRR abs/2408.09227 (2024) - [i84]Chaochao Chen, Jiaming Zhang, Yizhao Zhang, Li Zhang, Lingjuan Lyu, Yuyuan Li, Biao Gong, Chenggang Yan:
CURE4Rec: A Benchmark for Recommendation Unlearning with Deeper Influence. CoRR abs/2408.14393 (2024) - [i83]Zhuan Shi, Jing Yan, Xiaoli Tang, Lingjuan Lyu, Boi Faltings:
RLCP: A Reinforcement Learning-based Copyright Protection Method for Text-to-Image Diffusion Model. CoRR abs/2408.16634 (2024) - [i82]Ziyao Wang, Zheyu Shen, Yexiao He, Guoheng Sun, Hongyi Wang, Lingjuan Lyu, Ang Li:
FLoRA: Federated Fine-Tuning Large Language Models with Heterogeneous Low-Rank Adaptations. CoRR abs/2409.05976 (2024) - 2023
- [j28]Hongsheng Hu, Gillian Dobbie, Zoran Salcic, Meng Liu, Jianbing Zhang, Lingjuan Lyu, Xuyun Zhang:
Differentially private locality sensitive hashing based federated recommender system. Concurr. Comput. Pract. Exp. 35(14) (2023) - [j27]Yang Zhao, Jun Zhao, Linshan Jiang, Rui Tan, Dusit Niyato, Zengxiang Li, Lingjuan Lyu, Yingbo Liu:
Correction to "Privacy-Preserving Blockchain-Based Federated Learning for IoT Devices". IEEE Internet Things J. 10(1): 973 (2023) - [j26]Yueqi Xie, Jingwei Yi, Jiawei Shao, Justin Curl, Lingjuan Lyu, Qifeng Chen, Xing Xie, Fangzhao Wu:
Defending ChatGPT against jailbreak attack via self-reminders. Nat. Mac. Intell. 5(12): 1486-1496 (2023) - [j25]Chen Chen, Jingfeng Zhang, Xilie Xu, Lingjuan Lyu, Chaochao Chen, Tianlei Hu, Gang Chen:
Decision Boundary-Aware Data Augmentation for Adversarial Training. IEEE Trans. Dependable Secur. Comput. 20(3): 1882-1894 (2023) - [j24]Xiaoming Liu, Zhanwei Zhang, Lingjuan Lyu, Zhaohan Zhang, Shuai Xiao, Chao Shen, Philip S. Yu:
Traffic Anomaly Prediction Based on Joint Static-Dynamic Spatio-Temporal Evolutionary Learning. IEEE Trans. Knowl. Data Eng. 35(5): 5356-5370 (2023) - [j23]Si Chen, Yi Zeng, Won Park, Jiachen T. Wang, Xun Chen, Lingjuan Lyu, Zhuoqing Mao, Ruoxi Jia:
Turning a Curse into a Blessing: Enabling In-Distribution-Data-Free Backdoor Removal via Stabilized Model Inversion. Trans. Mach. Learn. Res. 2023 (2023) - [j22]Ziqing Fan, Jiangchao Yao, Ruipeng Zhang, Lingjuan Lyu, Yanfeng Wang, Ya Zhang:
Federated Learning under Partially Disjoint Data via Manifold Reshaping. Trans. Mach. Learn. Res. 2023 (2023) - [j21]Jiahua Dong, Yang Cong, Gan Sun, Lixu Wang, Lingjuan Lyu, Jun Li, Ender Konukoglu:
InOR-Net: Incremental 3-D Object Recognition Network for Point Cloud Representation. IEEE Trans. Neural Networks Learn. Syst. 34(10): 6955-6967 (2023) - [j20]Yu Guo, Ryan Wen Liu, Yuxu Lu, Jiangtian Nie, Lingjuan Lyu, Zehui Xiong, Jiawen Kang, Han Yu, Dusit Niyato:
Haze Visibility Enhancement for Promoting Traffic Situational Awareness in Vision-Enabled Intelligent Transportation. IEEE Trans. Veh. Technol. 72(12): 15421-15435 (2023) - [c74]Xiaofei Sun, Xiaoya Li, Yuxian Meng, Xiang Ao, Lingjuan Lyu, Jiwei Li, Tianwei Zhang:
Defending against Backdoor Attacks in Natural Language Generation. AAAI 2023: 5257-5265 - [c73]Jie Zhang, Bo Li, Chen Chen, Lingjuan Lyu, Shuang Wu, Shouhong Ding, Chao Wu:
Delving into the Adversarial Robustness of Federated Learning. AAAI 2023: 11245-11253 - [c72]Wenjun Peng, Jingwei Yi, Fangzhao Wu, Shangxi Wu, Bin Zhu, Lingjuan Lyu, Binxing Jiao, Tong Xu, Guangzhong Sun, Xing Xie:
Are You Copying My Model? Protecting the Copyright of Large Language Models for EaaS via Backdoor Watermark. ACL (1) 2023: 7653-7668 - [c71]Shuhe Wang, Yuxian Meng, Rongbin Ouyang, Jiwei Li, Tianwei Zhang, Lingjuan Lyu, Guoyin Wang:
GNN-SL: Sequence Labeling Based on Nearest Examples via GNN. ACL (Findings) 2023: 12679-12692 - [c70]Yi Zeng, Minzhou Pan, Hoang Anh Just, Lingjuan Lyu, Meikang Qiu, Ruoxi Jia:
Narcissus: A Practical Clean-Label Backdoor Attack with Limited Information. CCS 2023: 771-785 - [c69]Tao Bai, Chen Chen, Lingjuan Lyu, Jun Zhao, Bihan Wen:
Towards Adversarially Robust Continual Learning. ICASSP 2023: 1-5 - [c68]Virat Shejwalkar, Lingjuan Lyu, Amir Houmansadr:
The Perils of Learning From Unlabeled Data: Backdoor Attacks on Semi-supervised Learning. ICCV 2023: 4707-4717 - [c67]Jie Zhang, Chen Chen, Weiming Zhuang, Lingjuan Lyu:
TARGET: Federated Class-Continual Learning via Exemplar-Free Distillation. ICCV 2023: 4759-4770 - [c66]Weiming Zhuang, Yonggang Wen, Lingjuan Lyu, Shuai Zhang:
MAS: Towards Resource-Efficient Federated Multiple-Task Learning. ICCV 2023: 23357-23367 - [c65]Junyuan Hong, Lingjuan Lyu, Jiayu Zhou, Michael Spranger:
MECTA: Memory-Economic Continual Test-Time Model Adaptation. ICLR 2023 - [c64]Jingtao Li, Lingjuan Lyu, Daisuke Iso, Chaitali Chakrabarti, Michael Spranger:
MocoSFL: enabling cross-client collaborative self-supervised learning. ICLR 2023 - [c63]Chenxi Liu, Lixu Wang, Lingjuan Lyu, Chen Sun, Xiao Wang, Qi Zhu:
Deja Vu: Continual Model Generalization for Unseen Domains. ICLR 2023 - [c62]Yi Zeng, Zhouxing Shi, Ming Jin, Feiyang Kang, Lingjuan Lyu, Cho-Jui Hsieh, Ruoxi Jia:
Towards Robustness Certification Against Universal Perturbations. ICLR 2023 - [c61]Jie Zhang, Chen Chen, Lingjuan Lyu:
IDEAL: Query-Efficient Data-Free Learning from Black-Box Models. ICLR 2023 - [c60]Tianshi Che, Yang Zhou, Zijie Zhang, Lingjuan Lyu, Ji Liu, Da Yan, Dejing Dou, Jun Huan:
Fast Federated Machine Unlearning with Nonlinear Functional Theory. ICML 2023: 4241-4268 - [c59]Junyuan Hong, Yi Zeng, Shuyang Yu, Lingjuan Lyu, Ruoxi Jia, Jiayu Zhou:
Revisiting Data-Free Knowledge Distillation with Poisoned Teachers. ICML 2023: 13199-13212 - [c58]Yige Li, Xixiang Lyu, Xingjun Ma, Nodens Koren, Lingjuan Lyu, Bo Li, Yu-Gang Jiang:
Reconstructive Neuron Pruning for Backdoor Defense. ICML 2023: 19837-19854 - [c57]Yuchen Liu, Chen Chen, Lingjuan Lyu, Fangzhao Wu, Sai Wu, Gang Chen:
Byzantine-Robust Learning on Heterogeneous Data via Gradient Splitting. ICML 2023: 21404-21425 - [c56]Jiaxiang Ren, Yang Zhou, Jiayin Jin, Lingjuan Lyu, Da Yan:
Dimension-independent Certified Neural Network Watermarks via Mollifier Smoothing. ICML 2023: 28976-29008 - [c55]Qucheng Peng, Zhengming Ding, Lingjuan Lyu, Lichao Sun, Chen Chen:
RAIN: RegulArization on Input and Network for Black-Box Domain Adaptation. IJCAI 2023: 4118-4126 - [c54]Tao Qi, Fangzhao Wu, Lingjuan Lyu, Yongfeng Huang, Xing Xie:
FedSampling: A Better Sampling Strategy for Federated Learning. IJCAI 2023: 4154-4162 - [c53]Fei Zheng, Chaochao Chen, Lingjuan Lyu, Binhui Yao:
Reducing Communication for Split Learning by Randomized Top-k Sparsification. IJCAI 2023: 4665-4673 - [c52]Lingjuan Lyu:
A Pathway Towards Responsible AI Generated Content. IJCAI 2023: 7033-7038 - [c51]Ruixuan Liu, Yang Cao, Yanlin Wang, Lingjuan Lyu, Yun Chen, Hong Chen:
PrivateRec: Differentially Private Model Training and Online Serving for Federated News Recommendation. KDD 2023: 4539-4548 - [c50]Junyuan Hong, Zhuangdi Zhu, Lingjuan Lyu, Yang Zhou, Vishnu Naresh Boddeti, Jiayu Zhou:
International Workshop on Federated Learning for Distributed Data Mining. KDD 2023: 5861-5862 - [c49]Yuyuan Li, Chaochao Chen, Yizhao Zhang, Weiming Liu, Lingjuan Lyu, Xiaolin Zheng, Dan Meng, Jun Wang:
UltraRE: Enhancing RecEraser for Recommendation Unlearning via Error Decomposition. NeurIPS 2023 - [c48]Xiaoxiao Sun, Nidham Gazagnadou, Vivek Sharma, Lingjuan Lyu, Hongdong Li, Liang Zheng:
Privacy Assessment on Reconstructed Images: Are Existing Evaluation Metrics Faithful to Human Perception? NeurIPS 2023 - [c47]Yue Tan, Chen Chen, Weiming Zhuang, Xin Dong, Lingjuan Lyu, Guodong Long:
Is Heterogeneity Notorious? Taming Heterogeneity to Handle Test-Time Shift in Federated Learning. NeurIPS 2023 - [c46]Zhenting Wang, Chen Chen, Yi Zeng, Lingjuan Lyu, Shiqing Ma:
Where Did I Come From? Origin Attribution of AI-Generated Images. NeurIPS 2023 - [c45]Jiaqi Wang, Xingyi Yang, Suhan Cui, Liwei Che, Lingjuan Lyu, Dongkuan Xu, Fenglong Ma:
Towards Personalized Federated Learning via Heterogeneous Model Reassembly. NeurIPS 2023 - [c44]Yi Zeng, Minzhou Pan, Himanshu Jahagirdar, Ming Jin, Lingjuan Lyu, Ruoxi Jia:
Meta-Sift: How to Sift Out a Clean Subset in the Presence of Data Poisoning? USENIX Security Symposium 2023: 1667-1684 - [c43]Minzhou Pan, Yi Zeng, Lingjuan Lyu, Xue Lin, Ruoxi Jia:
ASSET: Robust Backdoor Data Detection Across a Multiplicity of Deep Learning Paradigms. USENIX Security Symposium 2023: 2725-2742 - [c42]Mengmei Zhang, Xiao Wang, Chuan Shi, Lingjuan Lyu, Tianchi Yang, Junping Du:
Minimum Topology Attacks for Graph Neural Networks. WWW 2023: 630-640 - [c41]Junlong Chen, Jiangtian Nie, Minrui Xu, Lingjuan Lyu, Zehui Xiong, Jiawen Kang, Yongju Tong, Wenchao Jiang:
Multiple-Agent Deep Reinforcement Learning for Avatar Migration in Vehicular Metaverses. WWW (Companion Volume) 2023: 1258-1265 - [i81]Chenxi Liu, Lixu Wang, Lingjuan Lyu, Chen Sun, Xiao Wang, Qi Zhu:
DEJA VU: Continual Model Generalization For Unseen Domains. CoRR abs/2301.10418 (2023) - [i80]Xiaolong Xu, Lingjuan Lyu, Yihong Dong, Yicheng Lu, Weiqiang Wang, Hong Jin:
SplitGNN: Splitting GNN for Node Classification with Heterogeneous Attention. CoRR abs/2301.12885 (2023) - [i79]Yuchen Liu, Chen Chen, Lingjuan Lyu, Fangzhao Wu, Sai Wu, Gang Chen:
GAIN: Enhancing Byzantine Robustness in Federated Learning with Gradient Decomposition. CoRR abs/2302.06079 (2023) - [i78]Jie Zhang, Bo Li, Chen Chen, Lingjuan Lyu, Shuang Wu, Shouhong Ding, Chao Wu:
Delving into the Adversarial Robustness of Federated Learning. CoRR abs/2302.09479 (2023) - [i77]Jiahua Dong, Yang Cong, Gan Sun, Lixu Wang, Lingjuan Lyu, Jun Li, Ender Konukoglu:
InOR-Net: Incremental 3D Object Recognition Network for Point Cloud Representation. CoRR abs/2302.09886 (2023) - [i76]Minzhou Pan, Yi Zeng, Lingjuan Lyu, Xue Lin, Ruoxi Jia:
ASSET: Robust Backdoor Data Detection Across a Multiplicity of Deep Learning Paradigms. CoRR abs/2302.11408 (2023) - [i75]Yuyang Deng, Nidham Gazagnadou, Junyuan Hong, Mehrdad Mahdavi, Lingjuan Lyu:
On the Hardness of Robustness Transfer: A Perspective from Rademacher Complexity over Symmetric Difference Hypothesis Space. CoRR abs/2302.12351 (2023) - [i74]Chen Chen, Jie Fu, Lingjuan Lyu:
A Pathway Towards Responsible AI Generated Content. CoRR abs/2303.01325 (2023) - [i73]Xukun Zhou, Jiwei Li, Tianwei Zhang, Lingjuan Lyu, Muqiao Yang, Jun He:
Backdoor Attacks with Input-unique Triggers in NLP. CoRR abs/2303.14325 (2023) - [i72]Tao Bai, Chen Chen, Lingjuan Lyu, Jun Zhao, Bihan Wen:
Towards Adversarially Robust Continual Learning. CoRR abs/2303.17764 (2023) - [i71]Yu Guo, Ryan Wen Liu, Jiangtian Nie, Lingjuan Lyu, Zehui Xiong, Jiawen Kang, Han Yu, Dusit Niyato:
DADFNet: Dual Attention and Dual Frequency-Guided Dehazing Network for Video-Empowered Intelligent Transportation. CoRR abs/2304.09588 (2023) - [i70]Wenjun Peng, Jingwei Yi, Fangzhao Wu, Shangxi Wu, Bin Zhu, Lingjuan Lyu, Binxing Jiao, Tong Xu, Guangzhong Sun, Xing Xie:
Are You Copying My Model? Protecting the Copyright of Large Language Models for EaaS via Backdoor Watermark. CoRR abs/2305.10036 (2023) - [i69]Rui Song, Lingjuan Lyu, Wei Jiang, Andreas Festag, Alois C. Knoll:
V2X-Boosted Federated Learning for Cooperative Intelligent Transportation Systems with Contextual Client Selection. CoRR abs/2305.11654 (2023) - [i68]Yige Li, Xixiang Lyu, Xingjun Ma, Nodens Koren, Lingjuan Lyu, Bo Li, Yu-Gang Jiang:
Reconstructive Neuron Pruning for Backdoor Defense. CoRR abs/2305.14876 (2023) - [i67]Zhenting Wang, Chen Chen, Yi Zeng, Lingjuan Lyu, Shiqing Ma:
Alteration-free and Model-agnostic Origin Attribution of Generated Images. CoRR abs/2305.18439 (2023) - [i66]Fei Zheng, Chaochao Chen, Lingjuan Lyu, Binhui Yao:
Reducing Communication for Split Learning by Randomized Top-k Sparsification. CoRR abs/2305.18469 (2023) - [i65]Junyuan Hong, Yi Zeng, Shuyang Yu, Lingjuan Lyu, Ruoxi Jia, Jiayu Zhou:
Revisiting Data-Free Knowledge Distillation with Poisoned Teachers. CoRR abs/2306.02368 (2023) - [i64]Weiming Zhuang, Lingjuan Lyu:
Is Normalization Indispensable for Multi-domain Federated Learning? CoRR abs/2306.05879 (2023) - [i63]Xiaofei Sun, Linfeng Dong, Xiaoya Li, Zhen Wan, Shuhe Wang, Tianwei Zhang, Jiwei Li, Fei Cheng, Lingjuan Lyu, Fei Wu, Guoyin Wang:
Pushing the Limits of ChatGPT on NLP Tasks. CoRR abs/2306.09719 (2023) - [i62]Tao Qi, Fangzhao Wu, Lingjuan Lyu, Yongfeng Huang, Xing Xie:
FedSampling: A Better Sampling Strategy for Federated Learning. CoRR abs/2306.14245 (2023) - [i61]Weiming Zhuang, Chen Chen, Lingjuan Lyu:
When Foundation Model Meets Federated Learning: Motivations, Challenges, and Future Directions. CoRR abs/2306.15546 (2023) - [i60]Zhenting Wang, Chen Chen, Yuchen Liu, Lingjuan Lyu, Dimitris N. Metaxas, Shiqing Ma:
How to Detect Unauthorized Data Usages in Text-to-image Diffusion Models. CoRR abs/2307.03108 (2023) - [i59]Chen Sun, Shiyao Ma, Ce Zheng, Songtao Wu, Tao Cui, Lingjuan Lyu:
Federated Learning over a Wireless Network: Distributed User Selection through Random Access. CoRR abs/2307.03758 (2023) - [i58]Weiming Zhuang, Yonggang Wen, Lingjuan Lyu, Shuai Zhang:
MAS: Towards Resource-Efficient Federated Multiple-Task Learning. CoRR abs/2307.11285 (2023) - [i57]Muhammad Awais, Weiming Zhuang, Lingjuan Lyu, Sung-Ho Bae:
FROD: Robust Object Detection for Free. CoRR abs/2308.01888 (2023) - [i56]Jiaqi Wang, Xingyi Yang, Suhan Cui, Liwei Che, Lingjuan Lyu, Dongkuan Xu, Fenglong Ma:
Towards Personalized Federated Learning via Heterogeneous Model Reassembly. CoRR abs/2308.08643 (2023) - [i55]Xiaoxiao Sun, Nidham Gazagnadou, Vivek Sharma, Lingjuan Lyu, Hongdong Li, Liang Zheng:
Privacy Assessment on Reconstructed Images: Are Existing Evaluation Metrics Faithful to Human Perception? CoRR abs/2309.13038 (2023) - [i54]Ruofan Wu, Mingyang Zhang, Lingjuan Lyu, Xiaolong Xu, Xiuquan Hao, Xinyi Fu, Tengfei Liu, Tianyi Zhang, Weiqiang Wang:
Privacy-preserving design of graph neural networks with applications to vertical federated learning. CoRR abs/2310.20552 (2023) - [i53]Bo Li, Qiang He, Feifei Chen, Lingjuan Lyu, Athman Bouguettaya, Yun Yang:
EdgeDis: Enabling Fast, Economical, and Reliable Data Dissemination for Mobile Edge Computing. CoRR abs/2311.00271 (2023) - 2022
- [j19]Gan Sun, Yang Cong, Jiahua Dong, Qiang Wang, Lingjuan Lyu, Ji Liu:
Data Poisoning Attacks on Federated Machine Learning. IEEE Internet Things J. 9(13): 11365-11375 (2022) - [j18]Lingjuan Lyu, Sid Chi-Kin Chau, Nan Wang, Yifeng Zheng:
Cloud-Based Privacy-Preserving Collaborative Consumption for Sharing Economy. IEEE Trans. Cloud Comput. 10(3): 1647-1660 (2022) - [j17]Lingjuan Lyu, Yitong Li, Karthik Nandakumar, Jiangshan Yu, Xingjun Ma:
How to Democratise and Protect AI: Fair and Differentially Private Decentralised Deep Learning. IEEE Trans. Dependable Secur. Comput. 19(2): 1003-1017 (2022) - [j16]Jianhua Li, Lingjuan Lyu, Ximeng Liu, Xuyun Zhang, Xixiang Lyu:
FLEAM: A Federated Learning Empowered Architecture to Mitigate DDoS in Industrial IoT. IEEE Trans. Ind. Informatics 18(6): 4059-4068 (2022) - [j15]Shiyao Ma, Jiangtian Nie, Jiawen Kang, Lingjuan Lyu, Ryan Wen Liu, Ruihui Zhao, Ziyao Liu, Dusit Niyato:
Privacy-Preserving Anomaly Detection in Cloud Manufacturing Via Federated Transformer. IEEE Trans. Ind. Informatics 18(12): 8977-8987 (2022) - [j14]Chuhan Wu, Fangzhao Wu, Lingjuan Lyu, Yongfeng Huang, Xing Xie:
FedCTR: Federated Native Ad CTR Prediction with Cross-platform User Behavior Data. ACM Trans. Intell. Syst. Technol. 13(4): 62:1-62:19 (2022) - [j13]Yuanyishu Tian, Yao Wan, Lingjuan Lyu, Dezhong Yao, Hai Jin, Lichao Sun:
FedBERT: When Federated Learning Meets Pre-training. ACM Trans. Intell. Syst. Technol. 13(4): 66:1-66:26 (2022) - [j12]Chen Li, Hao Peng, Jianxin Li, Lichao Sun, Lingjuan Lyu, Lihong Wang, Philip S. Yu, Lifang He:
Joint Stance and Rumor Detection in Hierarchical Heterogeneous Graph. IEEE Trans. Neural Networks Learn. Syst. 33(6): 2530-2542 (2022) - [c40]Xuanli He, Qiongkai Xu, Lingjuan Lyu, Fangzhao Wu, Chenguang Wang:
Protecting Intellectual Property of Language Generation APIs with Lexical Watermark. AAAI 2022: 10758-10766 - [c39]Jiaqian Ren, Lei Jiang, Hao Peng, Lingjuan Lyu, Zhiwei Liu, Chaochao Chen, Jia Wu, Xu Bai, Philip S. Yu:
Cross-Network Social User Embedding with Hybrid Differential Privacy Guarantees. CIKM 2022: 1685-1695 - [c38]Carl Yang, Xiaoxiao Li, Nathalie Baracaldo, Neil Shah, Chaoyang He, Lingjuan Lyu, Lichao Sun, Salman Avestimehr:
The 1st International Workshop on Federated Learning with Graph Data (FedGraph). CIKM 2022: 5179-5180 - [c37]Qiongkai Xu, Xuanli He, Lingjuan Lyu, Lizhen Qu, Gholamreza Haffari:
Student Surpasses Teacher: Imitation Attack for Black-Box NLP APIs. COLING 2022: 2849-2860 - [c36]Zhiyuan Zhang, Lingjuan Lyu, Xingjun Ma, Chenguang Wang, Xu Sun:
Fine-mixing: Mitigating Backdoors in Fine-tuned Language Models. EMNLP (Findings) 2022: 355-372 - [c35]Xuanli He, Lingjuan Lyu, Chen Chen, Qiongkai Xu:
Extracted BERT Model Leaks More Information than You Think! EMNLP 2022: 1530-1537 - [c34]Xiaolong Xu, Lingjuan Lyu, Hong Jin, Weiqiang Wang, Shuo Jia:
Heterogeneous Graph Node Classification With Multi-Hops Relation Features. ICASSP 2022: 5867-5871 - [c33]Ziqing Fan, Yanfeng Wang, Jiangchao Yao, Lingjuan Lyu, Ya Zhang, Qi Tian:
FedSkip: Combatting Statistical Heterogeneity with Federated Skip Aggregation. ICDM 2022: 131-140 - [c32]Zhiyuan Zhang, Lingjuan Lyu, Weiqiang Wang, Lichao Sun, Xu Sun:
How to Inject Backdoors with Better Consistency: Logit Anchoring on Clean Data. ICLR 2022 - [c31]Tian Dong, Bo Zhao, Lingjuan Lyu:
Privacy for Free: How does Dataset Condensation Help Privacy? ICML 2022: 5378-5396 - [c30]Jiayin Jin, Jiaxiang Ren, Yang Zhou, Lingjuan Lyu, Ji Liu, Dejing Dou:
Accelerated Federated Learning with Decoupled Adaptive Optimization. ICML 2022: 10298-10322 - [c29]Chaochao Chen, Jun Zhou, Longfei Zheng, Huiwen Wu, Lingjuan Lyu, Jia Wu, Bingzhe Wu, Ziqi Liu, Li Wang, Xiaolin Zheng:
Vertically Federated Graph Neural Network for Privacy-Preserving Node Classification. IJCAI 2022: 1959-1965 - [c28]Yuanxin Zhuang, Lingjuan Lyu, Chuan Shi, Carl Yang, Lichao Sun:
Data-Free Adversarial Knowledge Distillation for Graph Neural Networks. IJCAI 2022: 2441-2447 - [c27]Bo Li, Qiang He, Liang Yuan, Feifei Chen, Lingjuan Lyu, Yun Yang:
EdgeWatch: Collaborative Investigation of Data Integrity at the Edge based on Blockchain. KDD 2022: 3208-3218 - [c26]Ruixuan Liu, Fangzhao Wu, Chuhan Wu, Yanlin Wang, Lingjuan Lyu, Hong Chen, Xing Xie:
No One Left Behind: Inclusive Federated Learning over Heterogeneous Devices. KDD 2022: 3398-3406 - [c25]Jie Zhang, Chen Chen, Bo Li, Lingjuan Lyu, Shuang Wu, Shouhong Ding, Chunhua Shen, Chao Wu:
DENSE: Data-Free One-Shot Federated Learning. NeurIPS 2022 - [c24]Chen Chen, Yuchen Liu, Xingjun Ma, Lingjuan Lyu:
CalFAT: Calibrated Federated Adversarial Training with Label Skewness. NeurIPS 2022 - [c23]Xuanli He, Qiongkai Xu, Yi Zeng, Lingjuan Lyu, Fangzhao Wu, Jiwei Li, Ruoxi Jia:
CATER: Intellectual Property Protection on Text Generation APIs via Conditional Watermarks. NeurIPS 2022 - [c22]Junyuan Hong, Lingjuan Lyu, Jiayu Zhou, Michael Spranger:
Outsourcing Training without Uploading Data via Efficient Collaborative Open-Source Sampling. NeurIPS 2022 - [c21]Tao Qi, Fangzhao Wu, Chuhan Wu, Lingjuan Lyu, Tong Xu, Hao Liao, Zhongliang Yang, Yongfeng Huang, Xing Xie:
FairVFL: A Fair Vertical Federated Learning Framework with Contrastive Adversarial Learning. NeurIPS 2022 - [c20]Zijie Zhang, Yang Zhou, Xin Zhao, Tianshi Che, Lingjuan Lyu:
Prompt Certified Machine Unlearning with Randomized Gradient Smoothing and Quantization. NeurIPS 2022 - [c19]Chaochao Chen, Huiwen Wu, Jiajie Su, Lingjuan Lyu, Xiaolin Zheng, Li Wang:
Differential Private Knowledge Transfer for Privacy-Preserving Cross-Domain Recommendation. WWW 2022: 1455-1465 - [i52]Chaochao Chen, Huiwen Wu, Jiajie Su, Lingjuan Lyu, Xiaolin Zheng, Li Wang:
Differential Private Knowledge Transfer for Privacy-Preserving Cross-Domain Recommendation. CoRR abs/2202.04893 (2022) - [i51]Shangwei Guo, Chunlong Xie, Jiwei Li, Lingjuan Lyu, Tianwei Zhang:
Threats to Pre-trained Language Models: Survey and Taxonomy. CoRR abs/2202.06862 (2022) - [i50]Jamie Cui, Chaochao Chen, Lingjuan Lyu, Carl Yang, Li Wang:
Exploiting Data Sparsity in Secure Cross-Platform Social Recommendation. CoRR abs/2202.07253 (2022) - [i49]Ruixuan Liu, Fangzhao Wu, Chuhan Wu, Yanlin Wang, Lingjuan Lyu, Hong Chen, Xing Xie:
No One Left Behind: Inclusive Federated Learning over Heterogeneous Devices. CoRR abs/2202.08036 (2022) - [i48]Shiyao Ma, Jiangtian Nie, Jiawen Kang, Lingjuan Lyu, Ryan Wen Liu, Ruihui Zhao, Ziyao Liu, Dusit Niyato:
Privacy-preserving Anomaly Detection in Cloud Manufacturing via Federated Transformer. CoRR abs/2204.00843 (2022) - [i47]Yi Zeng, Minzhou Pan, Hoang Anh Just, Lingjuan Lyu, Meikang Qiu, Ruoxi Jia:
Narcissus: A Practical Clean-Label Backdoor Attack with Limited Information. CoRR abs/2204.05255 (2022) - [i46]Ruixuan Liu, Fangzhao Wu, Chuhan Wu, Yanlin Wang, Yang Cao, Lingjuan Lyu, Weike Pan, Yun Chen, Hong Chen, Xing Xie:
PrivateRec: Differentially Private Training and Serving for Federated News Recommendation. CoRR abs/2204.08146 (2022) - [i45]Yuanxin Zhuang, Lingjuan Lyu, Chuan Shi, Carl Yang, Lichao Sun:
Data-Free Adversarial Knowledge Distillation for Graph Neural Networks. CoRR abs/2205.03811 (2022) - [i44]Jie Zhang, Chen Chen, Jiahua Dong, Ruoxi Jia, Lingjuan Lyu:
QEKD: Query-Efficient and Data-Free Knowledge Distillation from Black-box Models. CoRR abs/2205.11158 (2022) - [i43]Chen Chen, Yuchen Liu, Xingjun Ma, Lingjuan Lyu:
CalFAT: Calibrated Federated Adversarial Training with Label Skewness. CoRR abs/2205.14926 (2022) - [i42]Tian Dong, Bo Zhao, Lingjuan Lyu:
Privacy for Free: How does Dataset Condensation Help Privacy? CoRR abs/2206.00240 (2022) - [i41]Tao Qi, Fangzhao Wu, Chuhan Wu, Lingjuan Lyu, Tong Xu, Zhongliang Yang, Yongfeng Huang, Xing Xie:
FairVFL: A Fair Vertical Federated Learning Framework with Contrastive Adversarial Learning. CoRR abs/2206.03200 (2022) - [i40]Jiayin Jin, Jiaxiang Ren, Yang Zhou, Lingjuan Lyu, Ji Liu, Dejing Dou:
Accelerated Federated Learning with Decoupled Adaptive Optimization. CoRR abs/2207.07223 (2022) - [i39]Qucheng Peng, Zhengming Ding, Lingjuan Lyu, Lichao Sun, Chen Chen:
Toward Better Target Representation for Source-Free and Black-Box Domain Adaptation. CoRR abs/2208.10531 (2022) - [i38]Jiaqian Ren, Lei Jiang, Hao Peng, Lingjuan Lyu, Zhiwei Liu, Chaochao Chen, Jia Wu, Xu Bai, Philip S. Yu:
Cross-Network Social User Embedding with Hybrid Differential Privacy Guarantees. CoRR abs/2209.01539 (2022) - [i37]Xuanli He, Qiongkai Xu, Yi Zeng, Lingjuan Lyu, Fangzhao Wu, Jiwei Li, Ruoxi Jia:
CATER: Intellectual Property Protection on Text Generation APIs via Conditional Watermarks. CoRR abs/2209.08773 (2022) - [i36]Yi Zeng, Minzhou Pan, Himanshu Jahagirdar, Ming Jin, Lingjuan Lyu, Ruoxi Jia:
How to Sift Out a Clean Data Subset in the Presence of Data Poisoning? CoRR abs/2210.06516 (2022) - [i35]Zhiyuan Zhang, Lingjuan Lyu, Xingjun Ma, Chenguang Wang, Xu Sun:
Fine-mixing: Mitigating Backdoors in Fine-tuned Language Models. CoRR abs/2210.09545 (2022) - [i34]Xuanli He, Chen Chen, Lingjuan Lyu, Qiongkai Xu:
Extracted BERT Model Leaks More Information than You Think! CoRR abs/2210.11735 (2022) - [i33]Junyuan Hong, Lingjuan Lyu, Jiayu Zhou, Michael Spranger:
Outsourcing Training without Uploading Data via Efficient Collaborative Open-Source Sampling. CoRR abs/2210.12575 (2022) - [i32]Virat Shejwalkar, Lingjuan Lyu, Amir Houmansadr:
The Perils of Learning From Unlabeled Data: Backdoor Attacks on Semi-supervised Learning. CoRR abs/2211.00453 (2022) - [i31]Shuhe Wang, Yuxian Meng, Rongbin Ouyang, Jiwei Li, Tianwei Zhang, Lingjuan Lyu, Guoyin Wang:
GNN-SL: Sequence Labeling Based on Nearest Examples via GNN. CoRR abs/2212.02017 (2022) - [i30]Rui Song, Liguo Zhou, Lingjuan Lyu, Andreas Festag, Alois C. Knoll:
ResFed: Communication Efficient Federated Learning by Transmitting Deep Compressed Residuals. CoRR abs/2212.05602 (2022) - [i29]Ziqing Fan, Yanfeng Wang, Jiangchao Yao, Lingjuan Lyu, Ya Zhang, Qi Tian:
FedSkip: Combatting Statistical Heterogeneity with Federated Skip Aggregation. CoRR abs/2212.07224 (2022) - 2021
- [j11]Jianhua Li, Jiong Jin, Lingjuan Lyu, Dong Yuan, Yingying Yang, Longxiang Gao, Chao Shen:
A fast and scalable authentication scheme in IOT for smart living. Future Gener. Comput. Syst. 117: 125-137 (2021) - [j10]Yang Zhao, Jun Zhao, Linshan Jiang, Rui Tan, Dusit Niyato, Zengxiang Li, Lingjuan Lyu, Yingbo Liu:
Privacy-Preserving Blockchain-Based Federated Learning for IoT Devices. IEEE Internet Things J. 8(3): 1817-1829 (2021) - [j9]Yang Zhao, Jun Zhao, Mengmeng Yang, Teng Wang, Ning Wang, Lingjuan Lyu, Dusit Niyato, Kwok-Yan Lam:
Local Differential Privacy-Based Federated Learning for Internet of Things. IEEE Internet Things J. 8(11): 8836-8853 (2021) - [j8]Meng Liu, Hongsheng Hu, Haolong Xiang, Chi Yang, Lingjuan Lyu, Xuyun Zhang:
Clustering-based Efficient Privacy-preserving Face Recognition Scheme without Compromising Accuracy. ACM Trans. Sens. Networks 17(3): 31:1-31:27 (2021) - [c18]Baolai Wang, Shaojing Fu, Xuyun Zhang, Tao Xie, Lingjuan Lyu, Yuchuan Luo:
Reliable and Privacy-Preserving Task Matching in Blockchain-Based Crowdsourcing. CIKM 2021: 1879-1888 - [c17]Zuobin Ying, Shuanglong Cao, Shengmin Xu, Ximeng Liu, Lingjuan Lyu, Cen Chen, Li Wang:
Privacy-Preserving Optimal Insulin Dosing Decision. ICASSP 2021: 2640-2644 - [c16]Yige Li, Xixiang Lyu, Nodens Koren, Lingjuan Lyu, Bo Li, Xingjun Ma:
Neural Attention Distillation: Erasing Backdoor Triggers from Deep Neural Networks. ICLR 2021 - [c15]Lichao Sun, Lingjuan Lyu:
Federated Model Distillation with Noise-Free Differential Privacy. IJCAI 2021: 1563-1570 - [c14]Xuanli He, Lingjuan Lyu, Lichao Sun, Qiongkai Xu:
Model Extraction and Adversarial Transferability, Your BERT is Vulnerable! NAACL-HLT 2021: 2006-2012 - [c13]Jinming Cui, Chaochao Chen, Lingjuan Lyu, Carl Yang, Li Wang:
Exploiting Data Sparsity in Secure Cross-Platform Social Recommendation. NeurIPS 2021: 10524-10534 - [c12]Yige Li, Xixiang Lyu, Nodens Koren, Lingjuan Lyu, Bo Li, Xingjun Ma:
Anti-Backdoor Learning: Training Clean Models on Poisoned Data. NeurIPS 2021: 14900-14912 - [c11]Xinyi Xu, Lingjuan Lyu, Xingjun Ma, Chenglin Miao, Chuan Sheng Foo, Bryan Kian Hsiang Low:
Gradient Driven Rewards to Guarantee Fairness in Collaborative Machine Learning. NeurIPS 2021: 16104-16117 - [i28]Yige Li, Xixiang Lyu, Nodens Koren, Lingjuan Lyu, Bo Li, Xingjun Ma:
Neural Attention Distillation: Erasing Backdoor Triggers from Deep Neural Networks. CoRR abs/2101.05930 (2021) - [i27]Xuanli He, Lingjuan Lyu, Qiongkai Xu, Lichao Sun:
Model Extraction and Adversarial Transferability, Your BERT is Vulnerable! CoRR abs/2103.10013 (2021) - [i26]Shuo Wang, Lingjuan Lyu, Surya Nepal, Carsten Rudolph, Marthie Grobler, Kristen Moore:
Robust Training Using Natural Transformation. CoRR abs/2105.04070 (2021) - [i25]Lingjuan Lyu:
DP-SIGNSGD: When Efficiency Meets Privacy and Robustness. CoRR abs/2105.04808 (2021) - [i24]Lingjuan Lyu, Xuanli He, Fangzhao Wu, Lichao Sun:
Killing Two Birds with One Stone: Stealing Model and Inferring Attribute from BERT-based APIs. CoRR abs/2105.10909 (2021) - [i23]Xiang Ni, Xiaolong Xu, Lingjuan Lyu, Changhua Meng, Weiqiang Wang:
A Vertical Federated Learning Framework for Graph Convolutional Network. CoRR abs/2106.11593 (2021) - [i22]Lingjuan Lyu, Chen Chen:
A Novel Attribute Reconstruction Attack in Federated Learning. CoRR abs/2108.06910 (2021) - [i21]Chuhan Wu, Fangzhao Wu, Ruixuan Liu, Lingjuan Lyu, Yongfeng Huang, Xing Xie:
FedKD: Communication Efficient Federated Learning via Knowledge Distillation. CoRR abs/2108.13323 (2021) - [i20]Qiongkai Xu, Xuanli He, Lingjuan Lyu, Lizhen Qu, Gholamreza Haffari:
Beyond Model Extraction: Imitation Attack for Black-Box NLP APIs. CoRR abs/2108.13873 (2021) - [i19]Zhiyuan Zhang, Lingjuan Lyu, Weiqiang Wang, Lichao Sun, Xu Sun:
How to Inject Backdoors with Better Consistency: Logit Anchoring on Clean Data. CoRR abs/2109.01300 (2021) - [i18]Yige Li, Xixiang Lyu, Nodens Koren, Lingjuan Lyu, Bo Li, Xingjun Ma:
Anti-Backdoor Learning: Training Clean Models on Poisoned Data. CoRR abs/2110.11571 (2021) - [i17]Xuanli He, Qiongkai Xu, Lingjuan Lyu, Fangzhao Wu, Chenguang Wang:
Protecting Intellectual Property of Language Generation APIs with Lexical Watermark. CoRR abs/2112.02701 (2021) - [i16]Jie Zhang, Chen Chen, Bo Li, Lingjuan Lyu, Shuang Wu, Jianghe Xu, Shouhong Ding, Chao Wu:
A Practical Data-Free Approach to One-shot Federated Learning with Heterogeneity. CoRR abs/2112.12371 (2021) - 2020
- [j7]Canyang Guo, Genggeng Liu, Lingjuan Lyu, Chi-Hua Chen:
An Unsupervised PM2.5 Estimation Method With Different Spatio-Temporal Resolutions Based on KIDW-TCGRU. IEEE Access 8: 190263-190276 (2020) - [j6]Lingjuan Lyu, James C. Bezdek, Jiong Jin, Yang Yang:
FORESEEN: Towards Differentially Private Deep Inference for Intelligent Internet of Things. IEEE J. Sel. Areas Commun. 38(10): 2418-2429 (2020) - [j5]Lingjuan Lyu, Jiangshan Yu, Karthik Nandakumar, Yitong Li, Xingjun Ma, Jiong Jin, Han Yu, Kee Siong Ng:
Towards Fair and Privacy-Preserving Federated Deep Models. IEEE Trans. Parallel Distributed Syst. 31(11): 2524-2541 (2020) - [c10]Lingjuan Lyu, Xuanli He, Yitong Li:
Differentially Private Representation for NLP: Formal Guarantee and An Empirical Study on Privacy and Fairness. EMNLP (Findings) 2020: 2355-2365 - [c9]Lingjuan Lyu:
Lightweight Crypto-Assisted Distributed Differential Privacy for Privacy-Preserving Distributed Learning. IJCNN 2020: 1-8 - [c8]Lingjuan Lyu, Chi-Hua Chen:
Differentially Private Knowledge Distillation for Mobile Analytics. SIGIR 2020: 1809-1812 - [c7]Lingjuan Lyu, Yitong Li, Xuanli He, Tong Xiao:
Towards Differentially Private Text Representations. SIGIR 2020: 1813-1816 - [c6]Lingjuan Lyu, Yee Wei Law, Kee Siong Ng, Shibei Xue, Jun Zhao, Mengmeng Yang, Lei Liu:
Towards Distributed Privacy-Preserving Prediction. SMC 2020: 4179-4184 - [c5]Shuo Wang, Lingjuan Lyu, Tianle Chen, Shangyu Chen, Surya Nepal, Carsten Rudolph, Marthie Grobler:
Privacy-Preserving Data Generation and Sharing Using Identification Sanitizer. WISE (2) 2020: 185-200 - [c4]Chi-Hua Chen, Yizhuo Zhang, Wenzhong Guo, Mingyang Pan, Lingjuan Lyu, Chia-Yu Lin:
Contour Accentuation for Transfer Learning-Based Ship Recognition Method. WWW (Companion Volume) 2020: 61-62 - [p2]Lingjuan Lyu, Han Yu, Jun Zhao, Qiang Yang:
Threats to Federated Learning. Federated Learning 2020: 3-16 - [p1]Lingjuan Lyu, Xinyi Xu, Qian Wang, Han Yu:
Collaborative Fairness in Federated Learning. Federated Learning 2020: 189-204 - [i15]Lingjuan Lyu, Han Yu, Qiang Yang:
Threats to Federated Learning: A Survey. CoRR abs/2003.02133 (2020) - [i14]Yang Zhao, Jun Zhao, Mengmeng Yang, Teng Wang, Ning Wang, Lingjuan Lyu, Dusit Niyato, Kwok-Yan Lam:
Local Differential Privacy based Federated Learning for Internet of Things. CoRR abs/2004.08856 (2020) - [i13]Lingjuan Lyu, Yitong Li, Xuanli He, Tong Xiao:
Towards Differentially Private Text Representations. CoRR abs/2006.14170 (2020) - [i12]Lingjuan Lyu, Sid Chi-Kin Chau, Nan Wang, Yifeng Zheng:
Cloud-based Privacy-Preserving Collaborative Consumption for Sharing Economy. CoRR abs/2007.07499 (2020) - [i11]Lingjuan Lyu, Yitong Li, Karthik Nandakumar, Jiangshan Yu, Xingjun Ma:
How to Democratise and Protect AI: Fair and Differentially Private Decentralised Deep Learning. CoRR abs/2007.09370 (2020) - [i10]Mengmeng Yang, Lingjuan Lyu, Jun Zhao, Tianqing Zhu, Kwok-Yan Lam:
Local Differential Privacy and Its Applications: A Comprehensive Survey. CoRR abs/2008.03686 (2020) - [i9]Lingjuan Lyu, Xinyi Xu, Qian Wang:
Collaborative Fairness in Federated Learning. CoRR abs/2008.12161 (2020) - [i8]Lichao Sun, Lingjuan Lyu:
Federated Model Distillation with Noise-Free Differential Privacy. CoRR abs/2009.05537 (2020) - [i7]Lingjuan Lyu, Xuanli He, Yitong Li:
Differentially Private Representation for NLP: Formal Guarantee and An Empirical Study on Privacy and Fairness. CoRR abs/2010.01285 (2020) - [i6]Jianhua Li, Jiong Jin, Lingjuan Lyu, Dong Yuan, Yingying Yang, Longxiang Gao, Chao Shen:
A Fast and Scalable Authentication Scheme in IoT for Smart Living. CoRR abs/2011.06325 (2020) - [i5]Xinyi Xu, Lingjuan Lyu:
Towards Building a Robust and Fair Federated Learning System. CoRR abs/2011.10464 (2020) - [i4]Jianhua Li, Lingjuan Lyu, Ximeng Liu, Xuyun Zhang, Xixiang Lyu:
FLEAM: A Federated Learning Empowered Architecture to Mitigate DDoS in Industrial IoT. CoRR abs/2012.06150 (2020) - [i3]Lingjuan Lyu, Han Yu, Xingjun Ma, Lichao Sun, Jun Zhao, Qiang Yang, Philip S. Yu:
Privacy and Robustness in Federated Learning: Attacks and Defenses. CoRR abs/2012.06337 (2020)
2010 – 2019
- 2019
- [j4]Lingjuan Lyu, James C. Bezdek, Xuanli He, Jiong Jin:
Fog-Embedded Deep Learning for the Internet of Things. IEEE Trans. Ind. Informatics 15(7): 4206-4215 (2019) - [i2]Lingjuan Lyu, Jiangshan Yu, Karthik Nandakumar, Yitong Li, Xingjun Ma, Jiong Jin:
Towards Fair and Decentralized Privacy-Preserving Deep Learning with Blockchain. CoRR abs/1906.01167 (2019) - [i1]Lingjuan Lyu, Yee Wei Law, Kee Siong Ng:
Distributed Privacy-Preserving Prediction. CoRR abs/1910.11478 (2019) - 2018
- [j3]Lingjuan Lyu, James C. Bezdek, Yee Wei Law, Xuanli He, Marimuthu Palaniswami:
Privacy-preserving collaborative fuzzy clustering. Data Knowl. Eng. 116: 21-41 (2018) - [j2]Lingjuan Lyu, Karthik Nandakumar, Benjamin I. P. Rubinstein, Jiong Jin, Justin Bedo, Marimuthu Palaniswami:
PPFA: Privacy Preserving Fog-Enabled Aggregation in Smart Grid. IEEE Trans. Ind. Informatics 14(8): 3733-3744 (2018) - 2017
- [j1]Lingjuan Lyu, Jiong Jin, Sutharshan Rajasegarar, Xuanli He, Marimuthu Palaniswami:
Fog-Empowered Anomaly Detection in IoT Using Hyperellipsoidal Clustering. IEEE Internet Things J. 4(5): 1174-1184 (2017) - [c3]Lingjuan Lyu, Xuanli He, Yee Wei Law, Marimuthu Palaniswami:
Privacy-Preserving Collaborative Deep Learning with Application to Human Activity Recognition. CIKM 2017: 1219-1228 - [c2]Lingjuan Lyu, Yee Wei Law, Jiong Jin, Marimuthu Palaniswami:
Privacy-Preserving Aggregation of Smart Metering via Transformation and Encryption. TrustCom/BigDataSE/ICESS 2017: 472-479 - 2016
- [c1]Lingjuan Lyu, Yee Wei Law, Sarah M. Erfani, Christopher Leckie, Marimuthu Palaniswami:
An improved scheme for privacy-preserving collaborative anomaly detection. PerCom Workshops 2016: 1-6
Coauthor Index
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