Yongduo Sui

According to our database, Yongduo Sui authored at least 26 papers between 2020 and 2025.

Collaborative distances:

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

2025

A Simple Data Augmentation for Graph Classification: A Perspective of Equivariance and Invariance.

Yongduo Sui, Shuyao Wang, Jie Sun, Zhiyuan Liu, Qing Cui, Longfei Li, Jun Zhou, Xiang Wang, Xiangnan He

ACM Trans. Knowl. Discov. Data, February, 2025

Unleashing the Power of Large Language Model for Denoising Recommendation.

Shuyao Wang, Zhi Zheng, Yongduo Sui, Hui Xiong

Proceedings of the ACM on Web Conference 2025, 2025

Grasp the Key Takeaways from Source Domain for Few Shot Graph Domain Adaptation.

Xiangwei Lv, Jingyuan Chen, Mengze Li, Yongduo Sui, Zemin Liu, Beishui Liao

Proceedings of the ACM on Web Conference 2025, 2025

A Unified Invariant Learning Framework for Graph Classification.

Yongduo Sui, Jie Sun, Shuyao Wang, Zemin Liu, Qing Cui, Longfei Li, Xiang Wang

Proceedings of the 31st ACM SIGKDD Conference on Knowledge Discovery and Data Mining, V.1, 2025

2024

Inductive Lottery Ticket Learning for Graph Neural Networks.

Yongduo Sui, Xiang Wang, Tianlong Chen, Meng Wang, Xiangnan He, Tat-Seng Chua

J. Comput. Sci. Technol., November, 2024

Enhancing Out-of-distribution Generalization on Graphs via Causal Attention Learning.

Yongduo Sui, Wenyu Mao, Shuyao Wang, Xiang Wang, Jiancan Wu, Xiangnan He, Tat-Seng Chua

ACM Trans. Knowl. Discov. Data, June, 2024

Invariant Graph Learning Meets Information Bottleneck for Out-of-Distribution Generalization.

Wenyu Mao, Jiancan Wu, Haoyang Liu, Yongduo Sui, Xiang Wang

CoRR, 2024

EXGC: Bridging Efficiency and Explainability in Graph Condensation.

Junfeng Fang, Xinglin Li, Yongduo Sui, Yuan Gao, Guibin Zhang, Kun Wang, Xiang Wang, Xiangnan He

CoRR, 2024

Unleashing the Power of Knowledge Graph for Recommendation via Invariant Learning.

Shuyao Wang, Yongduo Sui, Chao Wang, Hui Xiong

Proceedings of the ACM on Web Conference 2024, 2024

Invariant Graph Learning for Causal Effect Estimation.

Yongduo Sui, Caizhi Tang, Zhixuan Chu, Junfeng Fang, Yuan Gao, Qing Cui, Longfei Li, Jun Zhou, Xiang Wang

Proceedings of the ACM on Web Conference 2024, 2024

Graph Anomaly Detection with Bi-level Optimization.

Yuan Gao, Junfeng Fang, Yongduo Sui, Yangyang Li, Xiang Wang, Huamin Feng, Yongdong Zhang

Proceedings of the ACM on Web Conference 2024, 2024

EXGC: Bridging Efficiency and Explainability in Graph Condensation.

Junfeng Fang, Xinglin Li, Yongduo Sui, Yuan Gao, Guibin Zhang, Kun Wang, Xiang Wang, Xiangnan He

Proceedings of the ACM on Web Conference 2024, 2024

Dynamic Sparse Learning: A Novel Paradigm for Efficient Recommendation.

Shuyao Wang, Yongduo Sui, Jiancan Wu, Zhi Zheng, Hui Xiong

Proceedings of the 17th ACM International Conference on Web Search and Data Mining, 2024

Two Heads Are Better Than One: Boosting Graph Sparse Training via Semantic and Topological Awareness.

Guibin Zhang, Yanwei Yue, Kun Wang, Junfeng Fang, Yongduo Sui, Kai Wang, Yuxuan Liang, Dawei Cheng, Shirui Pan, Tianlong Chen

Proceedings of the Forty-first International Conference on Machine Learning, 2024

Masked Graph Modeling with Multi- View Contrast.

Yanchen Luo, Sihang Li, Yongduo Sui, Junkang Wu, Jiancan Wu, Xiang Wang

Proceedings of the 40th IEEE International Conference on Data Engineering, 2024

2023

On the Opportunities of Green Computing: A Survey.

You Zhou, Xiujing Lin, Xiang Zhang, Maolin Wang, Gangwei Jiang, Huakang Lu, Yupeng Wu, Kai Zhang, Zhe Yang, Kehang Wang, Yongduo Sui, Fengwei Jia, Zuoli Tang, Yao Zhao, Hongxuan Zhang, Tiannuo Yang, Weibo Chen, Yunong Mao, Yi Li, De Bao, Yu Li, Hongrui Liao, Ting Liu, Jingwen Liu, Jinchi Guo, Xiangyu Zhao, Ying Wei, Hong Qian, Qi Liu, Xiang Wang, Wai Kin Chan, Chenliang Li, Yusen Li, Shiyu Yang, Jining Yan, Chao Mou, Shuai Han, Wuxia Jin, Guannan Zhang, Xiaodong Zeng

CoRR, 2023

GIF: A General Graph Unlearning Strategy via Influence Function.

Jiancan Wu, Yi Yang, Yuchun Qian, Yongduo Sui, Xiang Wang, Xiangnan He

Proceedings of the ACM Web Conference 2023, 2023

Unleashing the Power of Graph Data Augmentation on Covariate Distribution Shift.

Yongduo Sui, Qitian Wu, Jiancan Wu, Qing Cui, Longfei Li, Jun Zhou, Xiang Wang, Xiangnan He

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

2022

Exploring lottery ticket hypothesis in media recommender systems.

Yanfang Wang, Yongduo Sui, Xiang Wang, Zhenguang Liu, Xiangnan He

Int. J. Intell. Syst., 2022

Adversarial Causal Augmentation for Graph Covariate Shift.

Yongduo Sui, Xiang Wang, Jiancan Wu, An Zhang, Xiangnan He

CoRR, 2022

Causal Attention for Interpretable and Generalizable Graph Classification.

Yongduo Sui, Xiang Wang, Jiancan Wu, Min Lin, Xiangnan He, Tat-Seng Chua

Proceedings of the KDD '22: The 28th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, Washington, DC, USA, August 14, 2022

Towards Robust Detection and Segmentation Using Vertical and Horizontal Adversarial Training.

Yongduo Sui, Tianlong Chen, Pengfei Xia, Shuyao Wang, Bin Li

Proceedings of the International Joint Conference on Neural Networks, 2022

2021

Deconfounded Training for Graph Neural Networks.

Yongduo Sui, Xiang Wang, Jiancan Wu, Xiangnan He, Tat-Seng Chua

CoRR, 2021

A Unified Lottery Ticket Hypothesis for Graph Neural Networks.

Tianlong Chen, Yongduo Sui, Xuxi Chen, Aston Zhang, Zhangyang Wang

Proceedings of the 38th International Conference on Machine Learning, 2021

GANs Can Play Lottery Tickets Too.

Xuxi Chen, Zhenyu Zhang, Yongduo Sui, Tianlong Chen

Proceedings of the 9th International Conference on Learning Representations, 2021

2020

Graph Contrastive Learning with Augmentations.

Yuning You, Tianlong Chen, Yongduo Sui, Ting Chen, Zhangyang Wang, Yang Shen

Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020