| A data-driven graph generative model for temporal interaction networks D Zhou, L Zheng, J Han, J He Proceedings of the 26th ACM SIGKDD International Conference on Knowledge …, 2020 | 106 | 2020 |
| Tackling Mental Health by Integrating Unobtrusive Multimodal Sensing D Zhou, J Luo, V Silenzio, Y Zhou, J Hu, G Currier, H Kautz The Twenty-Ninth AAAI Conference on Artificial Intelligence (AAAI-2015), 2015 | 96 | 2015 |
| Hidden: hierarchical dense subgraph detection with application to financial fraud detection S Zhang, D Zhou, MY Yildirim, S Alcorn, J He, H Davulcu, H Tong Proceedings of the 2017 SIAM international conference on data mining, 570-578, 2017 | 84 | 2017 |
| A local algorithm for structure-preserving graph cut D Zhou, S Zhang, MY Yildirim, S Alcorn, H Tong, H Davulcu, J He Proceedings of the 23rd ACM SIGKDD International Conference on Knowledge …, 2017 | 79 | 2017 |
| SPARC: Self-Paced Network Representation for Few-Shot Rare Category Characterization D Zhou, J He, H Yang, W Fan Proceedings of the 24th ACM SIGKDD International Conference on Knowledge …, 2018 | 74 | 2018 |
| Misc-GAN: A multi-scale generative model for graphs D Zhou, L Zheng, J Xu, J He Frontiers in big Data 2, 3, 2019 | 48 | 2019 |
| Local motif clustering on time-evolving graphs D Fu, D Zhou, J He Proceedings of the 26th ACM SIGKDD International conference on knowledge …, 2020 | 47 | 2020 |
| MUVIR: Multi-View Rare Category Detection D Zhou, J He, KS Candan, H Davulcu The 24th International Joint Conference on Artificial Intelligence (IJCAI-15), 2015 | 45 | 2015 |
| Domain adaptive multi-modality neural attention network for financial forecasting D Zhou, L Zheng, Y Zhu, J Li, J He Proceedings of The Web Conference 2020, 2230-2240, 2020 | 44 | 2020 |
| Personalized federated learning under mixture of distributions Y Wu, S Zhang, W Yu, Y Liu, Q Gu, D Zhou, H Chen, W Cheng International Conference on Machine Learning, 37860-37879, 2023 | 39 | 2023 |
| Rare Category Detection on Time-Evolving Graphs D Zhou, K Wang, N Cao, J He IEEE International Conference on Data Mining (ICDM2015), 2015 | 37 | 2015 |
| Towards Fine-Grained Temporal Network Representation via Time-Reinforced Random Walk Z Liu, D Zhou, Y Zhu, J Gu, J He Proceedings of the thirty-fourth AAAI Conference on Artificial Intelligence …, 2020 | 25 | 2020 |
| Towards Explainable Representation of Time-Evolving Graphs via Spatial-Temporal Graph Attention Networks Z Liu, D Zhou, J He Proceedings of the 28th ACM International Conference on Information and …, 2019 | 25 | 2019 |
| REACH^2-Mote: A Range Extending Passive Wake-up Wireless Sensor Node L Chen, J Warner, PL Yung, D Zhou, W Heinzelman, L Demirkol, ... ACM Transactions on Sensor Networks, Vol. V, No. N, Article A,, 2015 | 23 | 2015 |
| High-order structure exploration on massive graphs: A local graph clustering perspective D Zhou, S Zhang, MY Yildirim, S Alcorn, H Tong, H Davulcu, J He ACM Transactions on Knowledge Discovery from Data (TKDD) 15 (2), 1-26, 2021 | 22 | 2021 |
| MentorGNN: Deriving Curriculum for Pre-Training GNNs D Zhou, L Zheng, D Fu, J Han, J He Proceedings of the 31st ACM International Conference on Information …, 2022 | 20 | 2022 |
| Discovering rare categories from graph streams D Zhou, A Karthikeyan, K Wang, N Cao, J He Data mining and knowledge discovery 31 (2), 400-423, 2017 | 19 | 2017 |
| Bi-level Rare Temporal Pattern Detection D Zhou, J He, Y Cao, J Seo IEEE International Conference on Data Mining series (ICDM2016), 2016 | 19 | 2016 |
| Improving adversarial robustness via mutual information estimation D Zhou, N Wang, X Gao, B Han, X Wang, Y Zhan, T Liu International Conference on Machine Learning, 27338-27352, 2022 | 18 | 2022 |
| Adversarial training for prostate cancer classification using magnetic resonance imaging L Hu, DW Zhou, XY Guo, WH Xu, LM Wei, JG Zhao Quantitative Imaging in Medicine and Surgery 12 (6), 3276, 2022 | 18 | 2022 |
Jingrui HeUniversity of Illinois at Urbana-ChampaignVerified email at illinois.edu
