| Gromov-wasserstein learning for graph matching and node embedding H Xu, D Luo, H Zha, LC Duke International conference on machine learning, 6932-6941, 2019 | 216 | 2019 |
| Scalable Gromov-Wasserstein learning for graph partitioning and matching H Xu, D Luo, L Carin Advances in neural information processing systems 32, 2019 | 164 | 2019 |
| Learning Hawkes processes from short doubly-censored event sequences H Xu, D Luo, H Zha International Conference on Machine Learning, 3831-3840, 2017 | 77 | 2017 |
| Multi-task multi-dimensional hawkes processes for modeling event sequences D Luo, H Xu, Y Zhen, X Ning, H Zha, X Yang, W Zhang ACM, 2015 | 71 | 2015 |
| Learning autoencoders with relational regularization H Xu, D Luo, R Henao, S Shah, L Carin International Conference on Machine Learning, 10576-10586, 2020 | 46 | 2020 |
| You are what you watch and when you watch: Inferring household structures from IPTV viewing data D Luo, H Xu, H Zha, J Du, R Xie, X Yang, W Zhang IEEE Transactions on Broadcasting 60 (1), 61-72, 2014 | 37 | 2014 |
| Benefits from superposed hawkes processes H Xu, D Luo, X Chen, L Carin International Conference on Artificial Intelligence and Statistics, 623-631, 2018 | 24 | 2018 |
| Learning graphons via structured gromov-wasserstein barycenters H Xu, D Luo, L Carin, H Zha Proceedings of the AAAI Conference on Artificial Intelligence 35 (12), 10505 …, 2021 | 20 | 2021 |
| Learning mixtures of markov chains from aggregate data with structural constraints D Luo, H Xu, Y Zhen, B Dilkina, H Zha, X Yang, W Zhang IEEE Transactions on Knowledge and Data Engineering 28 (6), 1518-1531, 2016 | 18 | 2016 |
| 灰色风险型多属性群决策方法 罗党， 周玲， 罗迪新 系统工程与电子技术 30 (9), 1674-1678, 2008 | 17 | 2008 |
| Online Continuous-Time Tensor Factorization Based on Pairwise Interactive Point Processes. H Xu, D Luo, L Carin IJCAI, 2905-2911, 2018 | 12 | 2018 |
| Representing graphs via Gromov-Wasserstein factorization H Xu, J Liu, D Luo, L Carin IEEE Transactions on Pattern Analysis and Machine Intelligence 45 (1), 999-1016, 2022 | 10 | 2022 |
| Dictionary learning with mutually reinforcing group-graph structures H Xu, L Yu, D Luo, H Zha, Y Xu Proceedings of the AAAI Conference on Artificial Intelligence 29 (1), 2015 | 7 | 2015 |
| Fused gromov-wasserstein alignment for hawkes processes D Luo, H Xu, L Carin arXiv preprint arXiv:1910.02096, 2019 | 5 | 2019 |
| Learning Graphon Autoencoders for Generative Graph Modeling H Xu, P Zhao, J Huang, D Luo arXiv preprint arXiv:2105.14244, 2021 | 4 | 2021 |
| Hierarchical optimal transport for robust multi-view learning D Luo, H Xu, L Carin arXiv preprint arXiv:2006.03160, 2020 | 4 | 2020 |
| CASCONet: A Conference dataset D Luo, K Lyons arXiv preprint arXiv:1706.09485, 2017 | 4 | 2017 |
| Weakly-Supervised Temporal Action Alignment Driven by Unbalanced Spectral Fused Gromov-Wasserstein Distance D Luo, Y Wang, A Yue, H Xu Proceedings of the 30th ACM International Conference on Multimedia, 728-739, 2022 | 3 | 2022 |
| Differentiable Hierarchical Optimal Transport for Robust Multi-View Learning D Luo, H Xu, L Carin IEEE Transactions on Pattern Analysis and Machine Intelligence, 2022 | 2 | 2022 |
| Hawkes processes on graphons H Xu, D Luo, H Zha arXiv preprint arXiv:2102.02741, 2021 | 2 | 2021 |
Hongteng Xu 许洪腾Associate Professor, Renmin University of ChinaVerified email at ruc.edu.cn
