__ indicate Ph.D. students in our lab.
Xu Zheng, Farhad Shirani, T. Wang, S. Gao, W. Dong, W. Cheng, and Dongsheng Luo
PAC Learnability under Explanation-Preserving Graph Perturbations
Arivx, 2024
Guoming Li, Jian Yang, Shangsong Liang, and Dongsheng Luo
Spectral GNN via Two-dimensional (2-D) Graph Convolution
arxiv:2404.04559
Guoming Li, Jian Yang, Shangsong Liang, and Dongsheng Luo
Elevating Spectral GNNs through Enhanced Band-pass Filter Approximation
arxiv:2404.15354
Qianying Ren, Dongsheng Luo, Dongjin Song
Rank Supervised Contrastive Learning for Time Series Classification
Arxiv, 2024
Junjie Xu, Enyan Dai, Dongsheng Luo, Xiang Zhang and Suhang Wang
Learning Graph Filters for Spectral GNNs via Newton Interpolation
arXiv:2310.10064
Tiejin Chen, Wenwang Huang, Linsey Pang, Dongsheng Luo and Hua Wei
Are Classification Robustness and Explanation Robustness Really Strongly Correlated? An Analysis Through Input Loss Landscape
arXiv:2403.06013
Jun-En Ding, Phan Nguyen Minh Thao, Wen-Chih Peng, Jian-Zhe Wang, Chun-Cheng Chug, Min-Chen Hsieh, Yun-Chien Tseng, Ling Chen, Dongsheng Luo, Chi-Te Wang, Pei-fu Chen, Feng Liu, Fang-Ming Hung
Large Language Multimodal Models for 5-Year Chronic Disease Cohort Prediction Using EHR Data
arxiv:2403.04785
Tianxiang Zhao, Dongsheng Luo, Xiang Zhang, and Suhang Wang
Multi-source Unsupervised Domain Adaptation on Graphs with Transferability Modeling
ACM SIGKDD Conference on Knowledge Discovery and Data Mining (SIGKDD), 2024
Zhuomin Chen, J. Zhang, J. Ni, X. Li, Y. Bian, Md Islam, A. Mondal, H. Wei, and Dongsheng Luo
Interpreting Graph Neural Networks with In-Distributed Proxies
The International Conference on Machine Learning (ICML), 2024
TrustLOG @ WWW, 2024
Zichuan Liu, T. Wang, J. Shi, Xu Zheng, Zhuomin Chen, L. Song, W. Dong, J. Obeysekera, Farhad Shirani and Dongsheng Luo
TimeX++: Learning Time-Series Explanations with Information Bottleneck
The International Conference on Machine Learning (ICML), 2024
Xu Zheng, T. Wang, W. Cheng, A. Ma, H. Chen, M. Sha, and Dongsheng Luo
Parametric Augmentation for Time Series Contrastive Learning
The International Conference on Learning Representations (ICLR), 2024
The Second Workshop of Artificial Intelligence for Time Series Analysis: Theory, Algorithms, and Applications (AI4TS), 2023 (Best Paper Award)
Xu Zheng, Farhad Shirani, T. Wang, W. Cheng, Zhuomin Chen, H. Chen, H. Wei, Dongsheng Luo
Towards Robust Fidelity for Evaluating Explainability of Graph Neural Networks
The International Conference on Learning Representations (ICLR), 2024
2nd Workshop on TrustLOG @ WWW, 2024 (Best Paper Award Runner-Up)
Zichuan Liu, Y. Zhang, T. Wang, Z. Wang, Dongsheng Luo, M. Du, M. Wu, Y. Wang, C. Chen, L. Fan, Qingsong Wen
Explaining Time Series via Contrastive and Locally Sparse Perturbations
The International Conference on Learning Representations (ICLR), 2024
Dongsheng Luo, T. Zhao, W. Cheng, D. Xu, F. Han, W. Yu, X. Liu, H. Chen, Xiang Zhang
Towards Inductive and Efficient Explanations for Graph Neural Networks
IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2024
Rundong Huang, Farhad Shirani, Dongsheng Luo
Factorized Explainer for Graph Neural Networks
The AAAI Conference on Artificial Intelligence (AAAI), 2024.
Behzad Ousat, Dongsheng Luo, Amin Kharraz
Breaking the Bot Barrier: Evaluating the Effectiveness of Adversarial AI Techniques Against Multi-Modal Defense Models
Short Paper Track in International World Wide Web Conference (WWW), 2024.
Raihanul Bari Tanvir, Md Mezbahul Islam, Masrur Sobhan, Dongsheng Luo, Ananda Mohan Mondal
MOGAT: An Improved Multi-Omics Integration Framework Using Graph Attention Networks
International Journal of Molecular Sciences (IJMS), 2024
The 15th RECOMB Satellite Workshop on Computational Cancer Biology (RECOMB-CCB), 2023
Jiaxing Zhang, Dongsheng Luo, Hua Wei
MixupExplainer: Generalizing Explanations for Graph Neural Networks with Data Augmentation
Proceedings of 29th ACM SIGKDD Conference on Knowledge Discovery and Data Mining (SIGKDD), 2023
Dongsheng Luo, W. Cheng, Y. Wang, D. Xu, J. Ni, W. Yu, X. Zhang, Y. Liu, Y. Chen, H. Chen, Xiang Zhang
Time Series Contrastive Learning with Information-Aware Augmentations
Proceedings of the AAAI International Conference on Artificial Intelligence (AAAI), 2023
Han Xuanyuan, Tianxiang Zhao, and Dongsheng Luo
Shedding Light on Random Dropping and Oversmoothing
NeurIPS 2023 Workshop: New Frontiers in Graph Learning, 2023
Dongsheng Luo, Y. Bian, Y. Yan, X. Yu, J. Huan, X. Liu, Xiang Zhang
Random Walk on Multiple Networks
IEEE Transactions on Knowledge and Data Engineering (TKDE), 2023
Jiaxing Zhang, Zhuomin Chen, Hao Mei, Dongsheng Luo, Hua Wei
RegExplainer: Generating Explanations for Graph Neural Networks in Regression Task
Learning on Graphs Conference (LOG), 2023
Minghao Lin, Minghao Cheng, Dongsheng Luo, Yueqi Chen
CLExtract: Recovering Highly Corrupted DVB/GSE Satellite Stream with Contrastive Learning
Workshop on Security of Space and Satellite Systems (SpaceSec@ NDSS), 2023
Tianxiang Zhao, Dongsheng Luo, Xiang Zhang, Suhang Wang
Faithful and Consistent Graph Neural Network Explanations with Rationale Alignment
ACM Transactions on Intelligent Systems and Technology (TIST), 2023
Xu Zheng, Tianchun Wang, Samin Yasar Chowdhury, Ruimin Sun, Dongsheng Luo
Unsafe Behavior Detection with Adaptive Contrastive Learning in Industrial Control Systems
IEEE European Symposium on Security and Privacy Workshops (EuroS&PW), 2023
Tianxiang Zhao, Dongsheng Luo, Xiang Zhang, Suhang Wang
Towards Faithful and Consistent Explanations for Graph Neural Networks
Proceedings of the Sixteenth ACM International Conference on Web Search and Data Mining (WSDM), 2023
Huaisheng Zhu, Dongsheng Luo, Xianfeng Tang, Junjie Xu, Hui Liu, Suhang Wang
Self-Explainable Graph Neural Networks for Link Prediction
Arxiv, 2023
Dongsheng Luo, Shuai Ma, Yaowei Yan, Chunming Hu, Xiang Zhang, and Jinpeng Huai
A Collective Approach to Scholar Name Disambiguation
In IEEE Transactions on Knowledge and Data Engineering (TKDE), 2022
IEEE International Conference on Data Engineering (ICDE), 2021.
Tianchun Wang, Wei Cheng, Dongsheng Luo, Wenchao Yu, Jingchao Ni, Liang Tong, Haifeng Chen, Xiang Zhang
Personalized federated learning via heterogeneous modular networks
IEEE International Conference on Data Mining (ICDM), 2022
Tianxiang Zhao, Dongsheng Luo, Xiang Zhang, Suhang Wang
TopoImb: Toward Topology-level Imbalance in Learning from Graphs
Learning on Graphs Conference (LOG), 2022
Dongsheng LuoE, Wei ChengE, Wenchao Yu, Bo Zong, Jingchao Ni, Haifeng Chen, Xiang Zhang
Learning to Drop: Robust Graph Neural Network via Topological Denoising
In Proceedings of 14th ACM International Conference on Web Search and Data Mining (WSDM), 2021
Dongkuan Xu, Wei Cheng, Dongsheng Luo, Haifeng Chen, Xiang Zhang
Infogcl: Information-aware graph contrastive learning
Proceedings of Advances in Neural Information Processing Systems (NeurIPS), 2021
Dongkuan Xu, Wei Cheng, Jingchao Ni, Dongsheng Luo, Masanao Natsumeda, Dongjin Song, Bo Zong, Haifeng Chen, Xiang Zhang
Deep multi-instance contrastive learning with dual attention for anomaly precursor detection
Proceedings of Proceedings of the SIAM International Conference on Data Mining (SDM), 2021
Dongsheng Luo, Yuchen Bian, Xiang Zhang, Jun Huan
Attentive social recommendation: Towards user and item diversities
Workshop of Deep Learning on Graphs: Method and Applications(DLG-AAAI), 2021
Dongsheng Luo, Wei Cheng, Jingchao Ni, Wenchao Yu, Xuchao Zhang, Bo Zong, Yanchi Liu, Zhengzhang Chen, Dongjin Song, Haifeng Chen, Xiang Zhang
Unsupervised document embedding via contrastive augmentation
Arxiv, 2021
Dongsheng LuoE, Wei ChengE, Dongkuan Xu, Wenchao Yu, Bo Zong, Haifeng Chen, Xiang Zhang
Parameterized Explainer for Graph Neural Network
in Proceedings of 34th Conference on Neural Information Processing Systems (NeurIPS), 2020
Dongsheng Luo, Yuchen Bian, Yaowei Yan, Xiao Liu, Jun Huan, Xiang Zhang
Local Community Detection in Multiple Networks
in Proceedings of 26th ACM SIGKDD Conference on Knowledge Discovery and Data Mining (SIGKDD), 2020
Dongsheng Luo, Jingchao Ni, Suhang Wang, Yuchen Bian, Xiong Yu, Xiang Zhang
Deep Multi-Graph Clustering via Attentive Cross-Graph Association
Proceedings of the ACM International Conference on Web Search and Data Mining (WSDM), 2020
Yuchen Bian, Dongsheng Luo, Yaowei Yan, Wei Cheng, Wei Wang, and Xiang Zhang
Memory-based random walk for multi-query local community detection
Knowledge and Information Systems (KAIS), 2020
Dongkuan Xu, Wei Cheng, Dongsheng Luo, Yameng Gu, Xiao Liu, Jingchao Ni, Bo Zong, Haifeng Chen, Xiang Zhang
Adaptive neural network for node classification in dynamic networks
IEEE International Conference on Data Mining (ICDM), 2019
Dongkuan Xu, Wei Cheng, Dongsheng Luo, Xiang Zhang
Spatio-Temporal Attentive RNN for Node Classification in Temporal Attributed Graphs
International Joint Conference on Artificial Intelligence (IJCAI), 2019
Yaowei Yan, Yuchen Bian, Dongsheng Luo, Dongwon Lee, Xiang Zhang
Constrained local graph clustering by colored random walk
The world wide web conference (WWW), 2019
Yuchen Bian, Yaowei Yan, Wei Cheng, Wei Wang, Dongsheng Luo, Xiang Zhang
On multi-query local community detection
IEEE international conference on data mining (ICDM), 2018
Shuai Ma, Chen Gong, Renjun Hu, Dongsheng Luo, Chunming Hu, Jinpeng Huai
Query independent scholarly article ranking
IEEE 34th international conference on data engineering (ICDE), 2018
Yaowei Yan, Dongsheng Luo, Jingchao Ni, Hongliang Fei, Wei Fan, Xiong Yu, John Yen, Xiang Zhang
Local graph clustering by multi-network random walk with restart
PAKDD, 2018
Dongsheng Luo, Chen Gong, Renjun Hu, Liang Duan, and Shuai Ma
Ensemble Enabled Weighted PageRank
The WSDM Cup 2016 - Entity Ranking Challenge (WSDM CUP), 2016