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2020 – today
- 2024
[j7]Pengxiang Xu
, Yang He, Jian Yang, Shanshan Zhang:
Uncertainty guided test-time training for face forgery detection. Comput. Vis. Image Underst. 249: 104185 (2024)- [j6]Pengxiang Xu, Zhiyuan Ma, Xue Mei, Jie Shen:
Detecting facial manipulated images via one-class domain generalization. Multim. Syst. 30(1): 33 (2024) - [c2]Yijia Zhang, Qiang Wang, Zhe Lin, Pengxiang Xu, Bingqiang Wang:
Improving GPU Energy Efficiency through an Application-transparent Frequency Scaling Policy with Performance Assurance. EuroSys 2024: 769-785 - [i4]Di He, Ganzhao Yuan, Xiao Wang, Pengxiang Xu:
Block Coordinate Descent Methods for Optimization under J-Orthogonality Constraints with Applications. CoRR abs/2406.09771 (2024) - 2023
- [j5]Minghan Yang, Dong Xu, Qiwen Cui, Zaiwen Wen, Pengxiang Xu:
An Efficient Fisher Matrix Approximation Method for Large-Scale Neural Network Optimization. IEEE Trans. Pattern Anal. Mach. Intell. 45(5): 5391-5403 (2023) - 2022
- [j4]Yi Wei, Mei Xue, Xin Liu, Pengxiang Xu:
Data fusing and joint training for learning with noisy labels. Frontiers Comput. Sci. 16(6): 166338 (2022) - [j3]Minghan Yang, Dong Xu, Zaiwen Wen, Mengyun Chen, Pengxiang Xu:
Sketch-Based Empirical Natural Gradient Methods for Deep Learning. J. Sci. Comput. 92(3): 94 (2022) - 2021
- [j2]Tiancheng Qian, Xue Mei, Pengxiang Xu, Kangqi Ge, Zhelei Qiu:
Filtration network: A frame sampling strategy via deep reinforcement learning for video captioning. J. Intell. Fuzzy Syst. 40(6): 11085-11097 (2021) - [j1]Jinfeng Zeng, Zipeng Wu, Chenfeng Cao, Chao Zhang, Shi-Yao Hou, Pengxiang Xu, Bei Zeng:
Simulating noisy variational quantum eigensolver with local noise models. Quantum Eng. 3(4) (2021) - [c1]Pengxiang Xu, Xue Mei, Yi Wei, Tiancheng Qian:
Robust Facial Manipulation Detection via Domain Generalization. ICCAI 2021: 196-201 - [i3]Yi Wei, Xue Mei, Xin Liu, Pengxiang Xu:
DST: Data Selection and joint Training for Learning with Noisy Labels. CoRR abs/2103.00813 (2021) - [i2]Minghan Yang, Dong Xu, Qiwen Cui, Zaiwen Wen, Pengxiang Xu:
NG+ : A Multi-Step Matrix-Product Natural Gradient Method for Deep Learning. CoRR abs/2106.07454 (2021) - 2020
- [i1]Song Cheng, Chenfeng Cao, Chao Zhang, Yongxiang Liu, Shi-Yao Hou, Pengxiang Xu, Bei Zeng:
Simulating Noisy Quantum Circuits with Matrix Product Density Operators. CoRR abs/2004.02388 (2020)
Coauthor Index
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