Graph embedding via diffusion-wavelets-based node feature distribution characterization L Wang, C Huang, W Ma, X Cao, S Vosoughi Proceedings of the 30th ACM International Conference on Information …, 2021 | 18 | 2021 |
Provable lifelong learning of representations X Cao, W Liu, S Vempala International Conference on Artificial Intelligence and Statistics, 6334-6356, 2022 | 16 | 2022 |
Learning dynamic graph embeddings using random walk with temporal backtracking C Huang, L Wang, X Cao, W Ma, S Vosoughi NeurIPS 2022 Temporal Graph Learning Workshop, 2022 | 6 | 2022 |
StructComp: Substituting propagation with Structural Compression in Training Graph Contrastive Learning S Zhang, W Yang, X Cao, H Zhang, Z Huang arXiv preprint arXiv:2312.04865, 2023 | 4 | 2023 |
Towards Understanding Neural Collapse: The Effects of Batch Normalization and Weight Decay L Pan, X Cao arXiv preprint arXiv:2309.04644, 2023 | 4 | 2023 |
Learning-augmented b-trees X Cao, J Chen, L Chen, C Lambert, R Peng, D Sleator arXiv preprint arXiv:2211.09251, 2022 | 3 | 2022 |
Graph-level embedding for time-evolving graphs L Wang, C Huang, X Cao, W Ma, S Vosoughi Companion Proceedings of the ACM Web Conference 2023, 5-8, 2023 | 2 | 2023 |
Contrastive moments: Unsupervised halfspace learning in polynomial time X Cao, S Vempala Advances in Neural Information Processing Systems 36, 72540-72582, 2023 | 1 | 2023 |
On the Power of Learning-Augmented Search Trees X Cao, J Chen, A Stepin, L Chen | | |