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Huijun Wu 0001
Person information
- affiliation (PhD 2019): University of New South Wales, School of Computer Science and Engineering, Sydney, Australia
- affiliation: Data61, CSIRO, Sydney, Australia
Other persons with the same name
- Huijun Wu — disambiguation page
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2020 – today
- 2024
- [j4]Xugang Wu, Huijun Wu, Ruibo Wang, Xu Zhou, Kai Lu:
Towards adaptive graph neural networks via solving prior-data conflicts. Frontiers Inf. Technol. Electron. Eng. 25(3): 369-383 (2024) - [c13]Mingtian Shao, Wenzhe Zhang, Ruibo Wang, Huijun Wu, Yiqin Dai, Kai Lu:
Fully Decentralized Data Distribution for Exascale-HPC: End of the Provider-Demander Matching Puzzle. CLUSTER 2024: 310-321 - [c12]Duanyu Li, Huijun Wu, Min Xie, Xugang Wu, Zhenwei Wu, Wenzhe Zhang:
Talos: A More Effective and Efficient Adversarial Defense for GNN Models Based on the Global Homophily of Graphs. ECAI 2024: 1935-1942 - [c11]Huimin Ma, Siwei Wang, Shengju Yu, Suyuan Liu, Junjie Huang, Huijun Wu, Xinwang Liu, En Zhu:
Automatic and Aligned Anchor Learning Strategy for Multi-View Clustering. ACM Multimedia 2024: 5045-5054 - [c10]Xihong Yang, Erxue Min, Ke Liang, Yue Liu, Siwei Wang, Sihang Zhou, Huijun Wu, Xinwang Liu, En Zhu:
GraphLearner: Graph Node Clustering with Fully Learnable Augmentation. ACM Multimedia 2024: 5517-5526 - [i7]Duanyu Li, Huijun Wu, Min Xie, Xugang Wu, Zhenwei Wu, Wenzhe Zhang:
Exploiting Global Graph Homophily for Generalized Defense in Graph Neural Networks. CoRR abs/2406.03833 (2024) - [i6]Kaiwen Xia, Huijun Wu, Duanyu Li, Min Xie, Ruibo Wang, Wenzhe Zhang:
Perseus: Leveraging Common Data Patterns with Curriculum Learning for More Robust Graph Neural Networks. CoRR abs/2410.12425 (2024) - 2023
- [c9]Tai Yue, Pengfei Wang, Lei Zhou, Xu Zhou, Gen Zhang, Kai Lu, Huijun Wu:
ReForker: Patching x86_64 Binaries with the Fork Server to Improve Hardware-Assisted Fuzzing through Trampoline-Based Binary Rewriting. CNCIT 2023: 235-240 - [c8]Xugang Wu, Huijun Wu, Ruibo Wang, Duanyu Li, Xu Zhou, Kai Lu:
Leveraging Free Labels to Power up Heterophilic Graph Learning in Weakly-Supervised Settings: An Empirical Study. ECML/PKDD (3) 2023: 140-156 - 2022
- [j3]Xugang Wu, Huijun Wu, Xu Zhou, Xiang Zhao, Kai Lu:
Towards Defense Against Adversarial Attacks on Graph Neural Networks via Calibrated Co-Training. J. Comput. Sci. Technol. 37(5): 1161-1175 (2022) - 2021
- [i5]Xugang Wu, Huijun Wu, Xu Zhou, Kai Lu:
CoG: a Two-View Co-training Framework for Defending Adversarial Attacks on Graph. CoRR abs/2109.05558 (2021) - 2020
- [j2]Huijun Wu, Chen Wang, Richard Nock, Wei Wang, Jie Yin, Kai Lu, Liming Zhu:
SMINT: Toward Interpretable and Robust Model Sharing for Deep Neural Networks. ACM Trans. Web 14(3): 11:1-11:28 (2020)
2010 – 2019
- 2019
- [b1]Huijun Wu:
Towards integrating learning algorithms into computer system design. University of New South Wales, Sydney, Australia, 2019 - [c7]Huijun Wu, Chen Wang, Yuriy Tyshetskiy, Andrew Docherty, Kai Lu, Liming Zhu:
Adversarial Examples for Graph Data: Deep Insights into Attack and Defense. IJCAI 2019: 4816-4823 - [c6]Rimmal Nadeem, Huijun Wu, Hye-young Paik, Chen Wang:
A Case Based Deep Neural Network Interpretability Framework and Its User Study. WISE 2019: 147-161 - [i4]Huijun Wu, Chen Wang, Yuriy Tyshetskiy, Andrew Docherty, Kai Lu, Liming Zhu:
The Vulnerabilities of Graph Convolutional Networks: Stronger Attacks and Defensive Techniques. CoRR abs/1903.01610 (2019) - [i3]Wenzhe Zhang, Kai Lu, Ruibo Wang, Wanqing Chi, Mingtian Shao, Huijun Wu, Mikel Luján, Xiaoping Wang:
Lightweight Container-based User Environment. CoRR abs/1912.03887 (2019) - 2018
- [j1]Huijun Wu, Chen Wang, Yinjin Fu, Sherif Sakr, Kai Lu, Liming Zhu:
A Differentiated Caching Mechanism to Enable Primary Storage Deduplication in Clouds. IEEE Trans. Parallel Distributed Syst. 29(6): 1202-1216 (2018) - [c5]Huijun Wu, Chen Wang, Kai Lu, Yinjin Fu, Liming Zhu:
One Size Does Not Fit All: The Case for Chunking Configuration in Backup Deduplication. CCGrid 2018: 213-222 - [c4]Dongyao Wu, Sherif Sakr, Liming Zhu, Sung Une Lee, Huijun Wu:
HDM-MC in-Action: A Framework for Big Data Analytics across Multiple Clusters. ICDCS 2018: 1547-1550 - [c3]Huijun Wu, Chen Wang, Jie Yin, Kai Lu, Liming Zhu:
Sharing Deep Neural Network Models with Interpretation. WWW 2018: 177-186 - 2017
- [c2]Dongyao Wu, Sherif Sakr, Liming Zhu, Huijun Wu:
Towards Big Data Analytics across Multiple Clusters. CCGrid 2017: 218-227 - [i2]Huijun Wu, Chen Wang, Yinjin Fu, Sherif Sakr, Liming Zhu, Kai Lu:
HPDedup: A Hybrid Prioritized Data Deduplication Mechanism for Primary Storage in the Cloud. CoRR abs/1702.08153 (2017) - [i1]Huijun Wu, Chen Wang, Jie Yin, Kai Lu, Liming Zhu:
Interpreting Shared Deep Learning Models via Explicable Boundary Trees. CoRR abs/1709.03730 (2017) - 2016
- [c1]Huijun Wu, Liming Zhu, Kai Lu, Gen Li, Dongyao Wu:
StageFS: A Parallel File System Optimizing Metadata Performance for SSD Based Clusters. Trustcom/BigDataSE/ISPA 2016: 2147-2152
Coauthor Index
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last updated on 2024-12-02 21:29 CET by the dblp team
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