| Heterogeneous graph masked autoencoders Y Tian, K Dong, C Zhang, C Zhang, NV Chawla AAAI Conference on Artificial Intelligence (Oral Presentation) 37 (8), 9997 …, 2023 | 98 | 2023 |
| Boosting graph neural networks via adaptive knowledge distillation Z Guo, C Zhang, Y Fan, Y Tian, C Zhang, NV Chawla Proceedings of the AAAI Conference on Artificial Intelligence 37 (6), 7793-7801, 2023 | 36 | 2023 |
| Label-invariant augmentation for semi-supervised graph classification H Yue, C Zhang, C Zhang, H Liu Advances in Neural Information Processing Systems 35, 29350-29361, 2022 | 35 | 2022 |
| Fair graph representation learning via diverse mixture-of-experts Z Liu, C Zhang, Y Tian, E Zhang, C Huang, Y Ye, C Zhang Proceedings of the ACM Web Conference 2023, 28-38, 2023 | 27 | 2023 |
| Toward tailored models on private aiot devices: Federated direct neural architecture search C Zhang, X Yuan, Q Zhang, G Zhu, L Cheng, N Zhang IEEE Internet of Things Journal 9 (18), 17309-17322, 2022 | 25 | 2022 |
| Co-modality graph contrastive learning for imbalanced node classification Y Qian, C Zhang, Y Zhang, Q Wen, Y Ye, C Zhang Advances in Neural Information Processing Systems 35, 15862-15874, 2022 | 21 | 2022 |
| Chasing all-round graph representation robustness: Model, training, and optimization C Zhang, Y Tian, M Ju, Z Liu, Y Ye, N Chawla, C Zhang The Eleventh International Conference on Learning Representations, 2022 | 21 | 2022 |
| 3D Enhanced Multi-scale Network for Thoracic Organs Segmentation. Q Wang, W Zhao, C Zhang, L Zhang, C Wang, Z Li, S Cui, G Li SegTHOR@ ISBI 3 (1), 1-5, 2019 | 21 | 2019 |
| Breaking the trilemma of privacy, utility, and efficiency via controllable machine unlearning Z Liu, G Dou, E Chien, C Zhang, Y Tian, Z Zhu Proceedings of the ACM on Web Conference 2024, 1260-1271, 2024 | 19 | 2024 |
| Graphbert: Bridging graph and text for malicious behavior detection on social media J Wu, C Zhang, Z Liu, E Zhang, S Wilson, C Zhang 2022 IEEE International Conference on Data Mining (ICDM), 548-557, 2022 | 16 | 2022 |
| Look twice as much as you say: Scene graph contrastive learning for self-supervised image caption generation C Zhang, C Huang, Y Li, X Zhang, Y Ye, C Zhang Proceedings of the 31st ACM International Conference on Information …, 2022 | 14 | 2022 |
| When sparsity meets contrastive models: less graph data can bring better class-balanced representations C Zhang, C Huang, Y Tian, Q Wen, Z Ouyang, Y Li, Y Ye, C Zhang International Conference on Machine Learning, 41133-41150, 2023 | 12 | 2023 |
| Mitigating Emergent Robustness Degradation while Scaling Graph Learning X Yuan, C Zhang, Y Tian, Y Ye, C Zhang The Twelfth International Conference on Learning Representations, 2024 | 11 | 2024 |
| How to Improve Representation Alignment and Uniformity in Graph-based Collaborative Filtering? Z Ouyang, C Zhang, S Hou, C Zhang, Y Ye International AAAI Conference on Web and Social Media (ICWSM), 2024 | 9 | 2024 |
| Graph contrastive learning with cross-view reconstruction Q Wen, Z Ouyang, C Zhang, Y Qian, Y Ye, C Zhang arXiv preprint arXiv:2209.07699, 2022 | 9 | 2022 |
| Expedited Training of Visual Conditioned Language Generation via Redundancy Reduction Y Jian, T Liu, Y Tao, C Zhang, S Vosoughi, H Yang Annual Meeting of the Association for Computational Linguistics (ACL), 2024 | 7* | 2024 |
| Aligning relational learning with lipschitz fairness Y Jia, C Zhang, S Vosoughi The Twelfth International Conference on Learning Representations, 2024 | 5 | 2024 |
| Fdnas: Improving data privacy and model diversity in automl C Zhang, Y Liang, X Yuan, L Cheng arXiv preprint arXiv:2011.03372, 2020 | 4 | 2020 |
| Prompt Learning Unlocked for App Promotion in the Wild Z Ouyang, S Hou, S Ma, C Chen, C Zhang, T Li, X Xiao, C Zhang, Y Ye NeurIPS 2023 Workshop: New Frontiers in Graph Learning, 2023 | 3 | 2023 |
| Navigating Graph Robust Learning against All-Intensity Attacks X Yuan, C Zhang, Y Tian, C Zhang The Second Workshop on New Frontiers in Adversarial Machine Learning, 2023 | 2 | 2023 |
Yijun TianAmazon AWS AIVerified email at amazon.com