| LMC: Fast Training of GNNs via Subgraph Sampling with Provable Convergence Z Shi, X Liang, J Wang International Conference on Learning Representations, 2023 | 27 | 2023 |
| Duality-induced regularizer for semantic matching knowledge graph embeddings J Wang, Z Zhang, Z Shi, J Cai, S Ji, F Wu IEEE Transactions on Pattern Analysis and Machine Intelligence 45 (2), 1652-1667, 2022 | 11 | 2022 |
| Label Deconvolution for Node Representation Learning on Large-scale Attributed Graphs against Learning Bias Z Shi, J Wang, F Lu, H Chen, D Lian, Z Wang, J Ye, F Wu arXiv preprint arXiv:2309.14907, 2023 | 3 | 2023 |
| Robust preference optimization with provable noise tolerance for llms X Liang, C Chen, J Wang, Y Wu, Z Fu, Z Shi, F Wu, J Ye arXiv preprint arXiv:2404.04102, 2024 | 2 | 2024 |
| Learning to Cut via Hierarchical Sequence/Set Model for Efficient Mixed-Integer Programming J Wang, Z Wang, X Li, Y Kuang, Z Shi, F Zhu, M Yuan, J Zeng, Y Zhang, ... arXiv preprint arXiv:2404.12638, 2024 | 1 | 2024 |
| Generalization in Visual Reinforcement Learning with the Reward Sequence Distribution J Wang, R Yang, Z Geng, Z Shi, M Ye, Q Zhou, S Ji, B Li, Y Zhang, F Wu arXiv preprint arXiv:2302.09601, 2023 | 1 | 2023 |
| Learning Complete Topology-Aware Correlations Between Relations for Inductive Link Prediction J Wang, H Chen, Q Lv, Z Shi, J Chen, H He, H Xie, Y Zhang, F Wu arXiv preprint arXiv:2309.11528, 2023 | | 2023 |
| Provably Convergent Subgraph-wise Sampling for Fast GNN Training J Wang, Z Shi, X Liang, S Ji, B Li, F Wu arXiv preprint arXiv:2303.11081, 2023 | | 2023 |
| Solution of Team GraphMIRAcles in the KDD Cup 2022 Query-Product Ranking Task H Chen, Z Shi, Z Zhang, J Wang KDD Work Shop, 2022 | | 2022 |
| EPIC: Compressing Deep GNNs via Expressive Power Gap-Induced Knowledge Distillation X Liang, J Wang, Z Shi, H Chen, B Li, F Wu | | |
