Huijun Wu

According to our database, Huijun Wu authored at least 25 papers between 2016 and 2024.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2024

Towards adaptive graph neural networks via solving prior-data conflicts.

Xugang Wu, Huijun Wu, Ruibo Wang, Xu Zhou, Kai Lu

Frontiers Inf. Technol. Electron. Eng., March, 2024

Perseus: Leveraging Common Data Patterns with Curriculum Learning for More Robust Graph Neural Networks.

Kaiwen Xia, Huijun Wu, Duanyu Li, Min Xie, Ruibo Wang, Wenzhe Zhang

CoRR, 2024

Exploiting Global Graph Homophily for Generalized Defense in Graph Neural Networks.

Duanyu Li, Huijun Wu, Min Xie, Xugang Wu, Zhenwei Wu, Wenzhe Zhang

CoRR, 2024

GraphLearner: Graph Node Clustering with Fully Learnable Augmentation.

Xihong Yang, Erxue Min, Ke Liang, Yue Liu, Siwei Wang, Sihang Zhou, Huijun Wu, Xinwang Liu, En Zhu

Proceedings of the 32nd ACM International Conference on Multimedia, MM 2024, Melbourne, VIC, Australia, 28 October 2024, 2024

Automatic and Aligned Anchor Learning Strategy for Multi-View Clustering.

Huimin Ma, Siwei Wang, Shengju Yu, Suyuan Liu, Junjie Huang, Huijun Wu, Xinwang Liu, En Zhu

Proceedings of the 32nd ACM International Conference on Multimedia, MM 2024, Melbourne, VIC, Australia, 28 October 2024, 2024

Talos: A More Effective and Efficient Adversarial Defense for GNN Models Based on the Global Homophily of Graphs.

Duanyu Li, Huijun Wu, Min Xie, Xugang Wu, Zhenwei Wu, Wenzhe Zhang

Proceedings of the ECAI 2024 - 27th European Conference on Artificial Intelligence, 19-24 October 2024, Santiago de Compostela, Spain, 2024

Fully Decentralized Data Distribution for Exascale-HPC: End of the Provider-Demander Matching Puzzle.

Mingtian Shao, Wenzhe Zhang, Ruibo Wang, Huijun Wu, Yiqin Dai, Kai Lu

Proceedings of the IEEE International Conference on Cluster Computing, 2024

2023

Leveraging Free Labels to Power up Heterophilic Graph Learning in Weakly-Supervised Settings: An Empirical Study.

Xugang Wu, Huijun Wu, Ruibo Wang, Duanyu Li, Xu Zhou, Kai Lu

Proceedings of the Machine Learning and Knowledge Discovery in Databases: Research Track, 2023

ReForker: Patching x86_64 Binaries with the Fork Server to Improve Hardware-Assisted Fuzzing through Trampoline-Based Binary Rewriting.

Tai Yue, Pengfei Wang, Lei Zhou, Xu Zhou, Gen Zhang, Kai Lu, Huijun Wu

Proceedings of the 2nd International Conference on Networks, 2023

2022

Towards Defense Against Adversarial Attacks on Graph Neural Networks via Calibrated Co-Training.

Xugang Wu, Huijun Wu, Xu Zhou, Xiang Zhao, Kai Lu

J. Comput. Sci. Technol., 2022

2021

CoG: a Two-View Co-training Framework for Defending Adversarial Attacks on Graph.

Xugang Wu, Huijun Wu, Xu Zhou, Kai Lu

CoRR, 2021

2020

SMINT: Toward Interpretable and Robust Model Sharing for Deep Neural Networks.

Huijun Wu, Chen Wang, Richard Nock, Wei Wang, Jie Yin, Kai Lu, Liming Zhu

ACM Trans. Web, 2020

2019

Towards integrating learning algorithms into computer system design.

Huijun Wu

PhD thesis, 2019

Lightweight Container-based User Environment.

Wenzhe Zhang, Kai Lu, Ruibo Wang, Wanqing Chi, Mingtian Shao, Huijun Wu, Mikel Luján, Xiaoping Wang

CoRR, 2019

The Vulnerabilities of Graph Convolutional Networks: Stronger Attacks and Defensive Techniques.

Huijun Wu, Chen Wang, Yuriy Tyshetskiy, Andrew Docherty, Kai Lu, Liming Zhu

CoRR, 2019

A Case Based Deep Neural Network Interpretability Framework and Its User Study.

Rimmal Nadeem, Huijun Wu, Hye-young Paik, Chen Wang

Proceedings of the Web Information Systems Engineering - WISE 2019, 2019

Adversarial Examples for Graph Data: Deep Insights into Attack and Defense.

Huijun Wu, Chen Wang, Yuriy Tyshetskiy, Andrew Docherty, Kai Lu, Liming Zhu

Proceedings of the Twenty-Eighth International Joint Conference on Artificial Intelligence, 2019

2018

A Differentiated Caching Mechanism to Enable Primary Storage Deduplication in Clouds.

Huijun Wu, Chen Wang, Yinjin Fu, Sherif Sakr, Kai Lu, Liming Zhu

IEEE Trans. Parallel Distributed Syst., 2018

Sharing Deep Neural Network Models with Interpretation.

Huijun Wu, Chen Wang, Jie Yin, Kai Lu, Liming Zhu

Proceedings of the 2018 World Wide Web Conference on World Wide Web, 2018

HDM-MC in-Action: A Framework for Big Data Analytics across Multiple Clusters.

Dongyao Wu, Sherif Sakr, Liming Zhu, Sung Une Lee, Huijun Wu

Proceedings of the 38th IEEE International Conference on Distributed Computing Systems, 2018

One Size Does Not Fit All: The Case for Chunking Configuration in Backup Deduplication.

Huijun Wu, Chen Wang, Kai Lu, Yinjin Fu, Liming Zhu

Proceedings of the 18th IEEE/ACM International Symposium on Cluster, 2018

2017

Interpreting Shared Deep Learning Models via Explicable Boundary Trees.

Huijun Wu, Chen Wang, Jie Yin, Kai Lu, Liming Zhu

CoRR, 2017

HPDedup: A Hybrid Prioritized Data Deduplication Mechanism for Primary Storage in the Cloud.

Huijun Wu, Chen Wang, Yinjin Fu, Sherif Sakr, Liming Zhu, Kai Lu

CoRR, 2017

Towards Big Data Analytics across Multiple Clusters.

Dongyao Wu, Sherif Sakr, Liming Zhu, Huijun Wu

Proceedings of the 17th IEEE/ACM International Symposium on Cluster, 2017

2016

StageFS: A Parallel File System Optimizing Metadata Performance for SSD Based Clusters.

Huijun Wu, Liming Zhu, Kai Lu, Gen Li, Dongyao Wu

Proceedings of the 2016 IEEE Trustcom/BigDataSE/ISPA, 2016