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Dongxian Wu
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Journal Articles
- 2023
- [j1]Yinghua Gao, Yiming Li
, Linghui Zhu, Dongxian Wu, Yong Jiang, Shu-Tao Xia:
Not All Samples Are Born Equal: Towards Effective Clean-Label Backdoor Attacks. Pattern Recognit. 139: 109512 (2023)
Conference and Workshop Papers
- 2023
- [c10]Kuofeng Gao, Jiawang Bai, Bin Chen, Dongxian Wu, Shu-Tao Xia:
Backdoor Attack on Hash-based Image Retrieval via Clean-label Data Poisoning. BMVC 2023: 172-173 - [c9]Guanhao Gan, Yiming Li, Dongxian Wu, Shu-Tao Xia:
Towards Robust Model Watermark via Reducing Parametric Vulnerability. ICCV 2023: 4728-4738 - 2022
- [c8]Yichuan Mo, Dongxian Wu, Yifei Wang, Yiwen Guo, Yisen Wang:
When Adversarial Training Meets Vision Transformers: Recipes from Training to Architecture. NeurIPS 2022 - 2021
- [c7]Dongxian Wu, Yisen Wang:
Adversarial Neuron Pruning Purifies Backdoored Deep Models. NeurIPS 2021: 16913-16925 - 2020
- [c6]Jiawang Bai, Bin Chen, Yiming Li
, Dongxian Wu, Weiwei Guo, Shu-Tao Xia, En-Hui Yang:
Targeted Attack for Deep Hashing Based Retrieval. ECCV (1) 2020: 618-634 - [c5]Dongxian Wu, Yisen Wang, Shu-Tao Xia, James Bailey, Xingjun Ma:
Skip Connections Matter: On the Transferability of Adversarial Examples Generated with ResNets. ICLR 2020 - [c4]Xianbin Lv, Dongxian Wu, Shu-Tao Xia:
Matrix Smoothing: A Regularization For Dnn With Transition Matrix Under Noisy Labels. ICME 2020: 1-6 - [c3]Dongxian Wu, Yisen Wang, Zhuobin Zheng, Shu-Tao Xia:
Temporal Calibrated Regularization for Robust Noisy Label Learning. IJCNN 2020: 1-8 - [c2]Tao Dai, Yan Feng, Dongxian Wu, Bin Chen, Jian Lu, Yong Jiang, Shu-Tao Xia:
DIPDefend: Deep Image Prior Driven Defense against Adversarial Examples. ACM Multimedia 2020: 1404-1412 - [c1]Dongxian Wu, Shu-Tao Xia, Yisen Wang:
Adversarial Weight Perturbation Helps Robust Generalization. NeurIPS 2020
Informal and Other Publications
- 2023
- [i10]Guanhao Gan, Yiming Li, Dongxian Wu, Shutao Xia:
Towards Robust Model Watermark via Reducing Parametric Vulnerability. CoRR abs/2309.04777 (2023) - 2022
- [i9]Yinghua Gao, Dongxian Wu, Jingfeng Zhang, Guanhao Gan, Shu-Tao Xia, Gang Niu, Masashi Sugiyama:
On the Effectiveness of Adversarial Training against Backdoor Attacks. CoRR abs/2202.10627 (2022) - [i8]Yichuan Mo, Dongxian Wu, Yifei Wang, Yiwen Guo, Yisen Wang:
When Adversarial Training Meets Vision Transformers: Recipes from Training to Architecture. CoRR abs/2210.07540 (2022) - 2021
- [i7]Kuofeng Gao, Jiawang Bai, Bin Chen, Dongxian Wu, Shu-Tao Xia:
Clean-label Backdoor Attack against Deep Hashing based Retrieval. CoRR abs/2109.08868 (2021) - [i6]Dongxian Wu, Yisen Wang:
Adversarial Neuron Pruning Purifies Backdoored Deep Models. CoRR abs/2110.14430 (2021) - 2020
- [i5]Dongxian Wu
, Yisen Wang, Shu-Tao Xia, James Bailey, Xingjun Ma:
Skip Connections Matter: On the Transferability of Adversarial Examples Generated with ResNets. CoRR abs/2002.05990 (2020) - [i4]Xianbin Lv, Dongxian Wu, Shu-Tao Xia:
Matrix Smoothing: A Regularization for DNN with Transition Matrix under Noisy Labels. CoRR abs/2003.11904 (2020) - [i3]Dongxian Wu
, Yisen Wang, Shutao Xia:
Revisiting Loss Landscape for Adversarial Robustness. CoRR abs/2004.05884 (2020) - [i2]Jiawang Bai, Bin Chen, Yiming Li, Dongxian Wu, Weiwei Guo, Shu-Tao Xia, En-Hui Yang:
Targeted Attack for Deep Hashing based Retrieval. CoRR abs/2004.07955 (2020) - [i1]Dongxian Wu, Yisen Wang, Zhuobin Zheng, Shutao Xia:
Temporal Calibrated Regularization for Robust Noisy Label Learning. CoRR abs/2007.00240 (2020)
Coauthor Index
aka: Shu-Tao Xia
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