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2020 – today
- 2024
[j33]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)- [j32]Chen Chen, Lingjuan Lyu, Han Yu, Gang Chen:
Practical Attribute Reconstruction Attack Against Federated Learning. IEEE Trans. Big Data 10(6): 851-863 (2024) - [j31]Zhuan Shi, Lan Zhang, Zhenyu Yao, Lingjuan Lyu, Cen Chen, Li Wang, Junhao Wang, Xiang-Yang Li:
FedFAIM: A Model Performance-Based Fair Incentive Mechanism for Federated Learning. IEEE Trans. Big Data 10(6): 1038-1050 (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) - [c91]Hong Huang, Weiming Zhuang, Chen Chen, Lingjuan Lyu:
FedMef: Towards Memory-Efficient Federated Dynamic Pruning. CVPR 2024: 27538-27547 - [c90]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 - [c89]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. ECCV (77) 2024: 340-356 - [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 - [i107]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) - [i106]Mengmei Zhang, Xiao Wang, Chuan Shi, Lingjuan Lyu, Tianchi Yang, Junping Du:
Minimum Topology Attacks for Graph Neural Networks. CoRR abs/2403.02723 (2024) - [i105]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) - [i104]Hong Huang, Weiming Zhuang, Chen Chen, Lingjuan Lyu:
FedMef: Towards Memory-efficient Federated Dynamic Pruning. CoRR abs/2403.14737 (2024) - [i103]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) - [i102]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) - [i101]Kai Yi, Nidham Gazagnadou, Peter Richtárik, Lingjuan Lyu:
FedP3: Federated Personalized and Privacy-friendly Network Pruning under Model Heterogeneity. CoRR abs/2404.09816 (2024) - [i100]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) - [i99]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) - [i98]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) - [i97]Zhenting Wang, Chen Chen, Vikash Sehwag, Minzhou Pan, Lingjuan Lyu:
Evaluating and Mitigating IP Infringement in Visual Generative AI. CoRR abs/2406.04662 (2024) - [i96]Wenxiao Wang, Weiming Zhuang, Lingjuan Lyu:
Towards Fundamentally Scalable Model Selection: Asymptotically Fast Update and Selection. CoRR abs/2406.07536 (2024) - [i95]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) - [i94]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) - [i93]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) - [i92]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) - [i91]Weiming Zhuang, Jian Xu, Chen Chen, Jingtao Li, Lingjuan Lyu:
COALA: A Practical and Vision-Centric Federated Learning Platform. CoRR abs/2407.16560 (2024) - [i90]Yuxin Wen, Yuchen Liu, Chen Chen, Lingjuan Lyu:
Detecting, Explaining, and Mitigating Memorization in Diffusion Models. CoRR abs/2407.21720 (2024) - [i89]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) - [i88]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) - [i87]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) - [i86]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) - [i85]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) - [i84]Jie Ren, Kangrui Chen, Chen Chen, Vikash Sehwag, Yue Xing, Jiliang Tang, Lingjuan Lyu:
Self-Comparison for Dataset-Level Membership Inference in Large (Vision-)Language Models. CoRR abs/2410.13088 (2024) - [i83]David Schneider, Sina Sajadmanesh, Vikash Sehwag, M. Saquib Sarfraz, Rainer Stiefelhagen, Lingjuan Lyu, Vivek Sharma:
Masked Differential Privacy. CoRR abs/2410.17098 (2024) - [i82]Zhuan Shi, Yifei Song, Xiaoli Tang, Lingjuan Lyu, Boi Faltings:
Copyright-Aware Incentive Scheme for Generative Art Models Using Hierarchical Reinforcement Learning. CoRR abs/2410.20180 (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]