| A survey on dialogue systems: Recent advances and new frontiers H Chen, X Liu, D Yin, J Tang Acm Sigkdd Explorations Newsletter 19 (2), 25-35, 2017 | 752 | 2017 |
| Graph structure learning for robust graph neural networks W Jin, Y Ma, X Liu, X Tang, S Wang, J Tang KDD 2020 (ACM SIGKDD International Conference on Knowledge Discovery & Data …, 2020 | 437 | 2020 |
| Is homophily a necessity for graph neural networks? Y Ma, X Liu, N Shah, J Tang ICLR 2022 (International Conference on Learning Representations), 2021 | 152 | 2021 |
| To be robust or to be fair: Towards fairness in adversarial training H Xu*, X Liu*, Y Li, A Jain, J Tang International Conference on Machine Learning, 11492-11501, 2021 | 127 | 2021 |
| Trustworthy AI: A Computational Perspective H Liu, Y Wang, W Fan, X Liu, Y Li, S Jain, AK Jain, J Tang ACM Transactions on Intelligent Systems and Technology, 2022 | 121 | 2022 |
| A unified view on graph neural networks as graph signal denoising Y Ma, X Liu, T Zhao, Y Liu, J Tang, N Shah Proceedings of the 30th ACM International Conference on Information …, 2021 | 119 | 2021 |
| Elastic graph neural networks X Liu, W Jin, Y Ma, Y Li, H Liu, Y Wang, M Yan, J Tang International Conference on Machine Learning, 6837-6849, 2021 | 89 | 2021 |
| A pointing gesture based egocentric interaction system: Dataset, approach and application Y Huang, X Liu, X Zhang, L Jin Proceedings of the IEEE conference on computer vision and pattern …, 2016 | 65 | 2016 |
| A Double Residual Compression Algorithm for Efficient Distributed Learning X Liu, Y Li, J Tang, M Yan AISTATS 2020 (International Conference on Artificial Intelligence and …, 2020 | 58 | 2020 |
| Graph trend filtering networks for recommendation W Fan, X Liu, W Jin, X Zhao, J Tang, Q Li Proceedings of the 45th International ACM SIGIR Conference on Research and …, 2022 | 54 | 2022 |
| Deep adversarial network alignment T Derr, H Karimi, X Liu, J Xu, J Tang Proceedings of the 30th ACM international conference on information …, 2021 | 49 | 2021 |
| Automated self-supervised learning for graphs W Jin, X Liu, X Zhao, Y Ma, N Shah, J Tang ICLR 2022 (International Conference on Learning Representations), 2021 | 48 | 2021 |
| Linear Convergent Decentralized Optimization with Compression X Liu, Y Li, R Wang, J Tang, M Yan ICLR 2021 (International Conference on Learning Representations), 2021 | 44 | 2021 |
| Deepfinger: A cascade convolutional neuron network approach to finger key point detection in egocentric vision with mobile camera Y Huang, X Liu, L Jin, X Zhang 2015 IEEE international conference on systems, man, and cybernetics, 2944-2949, 2015 | 42 | 2015 |
| Epidemic graph convolutional network T Derr, Y Ma, W Fan, X Liu, C Aggarwal, J Tang WSDM 2020 (International Conference on Web Search and Data Mining), 160-168, 2020 | 34 | 2020 |
| Graph neural networks with adaptive residual X Liu, J Ding, W Jin, H Xu, Y Ma, Z Liu, J Tang Advances in Neural Information Processing Systems 34, 9720-9733, 2021 | 30 | 2021 |
| Jointly attacking graph neural network and its explanations W Fan, W Jin, X Liu, H Xu, X Tang, S Wang, Q Li, J Tang, J Wang, ... IEEE International Conference on Data Engineering (ICDE 2023), 2021 | 20 | 2021 |
| Feature Overcorrelation in Deep Graph Neural Networks: A New Perspective W Jin, X Liu, Y Ma, C Aggarwal, J Tang ACM SIGKDD International Conference on Knowledge Discovery & Data Mining, 2022 | 19 | 2022 |
| Fingertip in the eye: A cascaded cnn pipeline for the real-time fingertip detection in egocentric videos X Liu, Y Huang, X Zhang, L Jin arXiv preprint arXiv:1511.02282, 2015 | 18 | 2015 |
| Deep Adversarial Canonical Correlation Analysis W Fan, Y Ma, H Xu, X Liu, J Wang, Q Li, J Tang ICDM 2020 (SIAM International Conference on Data Mining), 352-360, 2020 | 17 | 2020 |
Jiliang TangUniversity Foundation Professor of Computer Science and Engineering, Michigan State UniversityVerified email at msu.edu
