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Yingwen Wu
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2020 – today
- 2024
- [j7]Kun Fang
, Qinghua Tao
Towards robust neural networks via orthogonal diversity. Pattern Recognit. 149: 110281 (2024) - [j6]Zhehao Huang, Tao Li, Chenhe Yuan, Yingwen Wu, Xiaolin Huang:
Online Continual Learning via Logit Adjusted Softmax. Trans. Mach. Learn. Res. 2024 (2024) - [j5]Tao Li, Qinghua Tao, Weihao Yan, Yingwen Wu, Zehao Lei, Kun Fang, Mingzhen He, Xiaolin Huang:
Revisiting Random Weight Perturbation for Efficiently Improving Generalization. Trans. Mach. Learn. Res. 2024 (2024) - [c4]Zehao Lei
Better Generalization in Fast Training: Flat Trainable Weight in Subspace. ICMLC 2024: 470-477 - [i11]Tao Li, Qinghua Tao, Weihao Yan, Zehao Lei, Yingwen Wu, Kun Fang, Mingzhen He, Xiaolin Huang:
Revisiting Random Weight Perturbation for Efficiently Improving Generalization. CoRR abs/2404.00357 (2024) - [i10]Yingwen Wu, Ruiji Yu, Xinwen Cheng, Zhengbao He, Xiaolin Huang:
Pursuing Feature Separation based on Neural Collapse for Out-of-Distribution Detection. CoRR abs/2405.17816 (2024) - 2023
- [j4]Yingwen Wu, Yangjian Ji, Fu Gu:
Identifying firm-specific technology opportunities in a supply chain: Link prediction analysis in multilayer networks. Expert Syst. Appl. 213(Part): 119053 (2023) - [j3]Yingwen Wu, Yangjian Ji:
Identifying firm-specific technology opportunities from the perspective of competitors by using association rule mining. J. Informetrics 17(2): 101398 (2023) - [j2]Yingwen Wu
Unifying Gradients to Improve Real-World Robustness for Deep Networks. ACM Trans. Intell. Syst. Technol. 14(6): 101:1-101:16 (2023) - [c3]Tao Li, Zhehao Huang, Qinghua Tao, Yingwen Wu, Xiaolin Huang:
Trainable Weight Averaging: Efficient Training by Optimizing Historical Solutions. ICLR 2023 - [i9]Yingwen Wu, Tao Li, Xinwen Cheng, Jie Yang, Xiaolin Huang:
Low-Dimensional Gradient Helps Out-of-Distribution Detection. CoRR abs/2310.17163 (2023) - [i8]Zhehao Huang, Tao Li, Chenhe Yuan, Yingwen Wu, Xiaolin Huang:
Online Continual Learning via Logit Adjusted Softmax. CoRR abs/2311.06460 (2023) - 2022
- [c2]Tao Li, Yingwen Wu, Sizhe Chen, Kun Fang
Subspace Adversarial Training. CVPR 2022: 13399-13408 - [c1]Sizhe Chen, Zhehao Huang, Qinghua Tao, Yingwen Wu, Cihang Xie, Xiaolin Huang:
Adversarial Attack on Attackers: Post-Process to Mitigate Black-Box Score-Based Query Attacks. NeurIPS 2022 - [i7]Sizhe Chen, Zhehao Huang, Qinghua Tao, Yingwen Wu, Cihang Xie
Adversarial Attack on Attackers: Post-Process to Mitigate Black-Box Score-Based Query Attacks. CoRR abs/2205.12134 (2022) - [i6]Tao Li, Zhehao Huang, Qinghua Tao, Yingwen Wu, Xiaolin Huang:
Trainable Weight Averaging for Fast Convergence and Better Generalization. CoRR abs/2205.13104 (2022) - [i5]Yingwen Wu, Sizhe Chen, Kun Fang, Xiaolin Huang:
Unifying Gradients to Improve Real-world Robustness for Deep Networks. CoRR abs/2208.06228 (2022) - [i4]Kun Fang
On Multi-head Ensemble of Smoothed Classifiers for Certified Robustness. CoRR abs/2211.10882 (2022) - [i3]Tao Li, Weihao Yan, Zehao Lei, Yingwen Wu, Kun Fang, Ming Yang, Xiaolin Huang:
Efficient Generalization Improvement Guided by Random Weight Perturbation. CoRR abs/2211.11489 (2022) - 2021
- [i2]Tao Li, Yingwen Wu, Sizhe Chen, Kun Fang, Xiaolin Huang:
Subspace Adversarial Training. CoRR abs/2111.12229 (2021) - 2020
- [i1]Kun Fang, Yingwen Wu, Tao Li, Xiaolin Huang, Jie Yang:
Learn Robust Features via Orthogonal Multi-Path. CoRR abs/2010.12190 (2020)
2010 – 2019
- 2017
- [j1]Li Guo, Long Chen
Image Guided Fuzzy C-Means for Image Segmentation. Int. J. Fuzzy Syst. 19(6): 1660-1669 (2017)
Coauthor Index
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