| Breaking the curse of horizon: Infinite-horizon off-policy estimation Q Liu, L Li, Z Tang, D Zhou Advances in neural information processing systems 31, 2018 | 402 | 2018 |
| Stein variational gradient descent with matrix-valued kernels D Wang, Z Tang, C Bajaj, Q Liu Advances in neural information processing systems 32, 2019 | 76 | 2019 |
| Doubly robust bias reduction in infinite horizon off-policy estimation Z Tang, Y Feng, L Li, D Zhou, Q Liu arXiv preprint arXiv:1910.07186, 2019 | 74 | 2019 |
| Accountable off-policy evaluation with kernel bellman statistics Y Feng, T Ren, Z Tang, Q Liu International Conference on Machine Learning, 3102-3111, 2020 | 45 | 2020 |
| Complexity of domination, hamiltonicity and treewidth for tree convex bipartite graphs H Chen, Z Lei, T Liu, Z Tang, C Wang, K Xu Journal of Combinatorial Optimization 32 (1), 95-110, 2016 | 26 | 2016 |
| Split localized conformal prediction X Han, Z Tang, J Ghosh, Q Liu arXiv preprint arXiv:2206.13092, 2022 | 13 | 2022 |
| Non-asymptotic confidence intervals of off-policy evaluation: Primal and dual bounds Y Feng, Z Tang, N Zhang, Q Liu arXiv preprint arXiv:2103.05741, 2021 | 12 | 2021 |
| Harnessing infinite-horizon off-policy evaluation: Double robustness via duality Z Tang, Y Feng, L Li, D Zhou, Q Liu ICLR 2020, 1-20, 2020 | 8 | 2020 |
| Robust imitation learning from corrupted demonstrations L Liu, Z Tang, L Li, D Luo arXiv preprint arXiv:2201.12594, 2022 | 7 | 2022 |
| Tree convex bipartite graphs:-complete domination, hamiltonicity and treewidth C Wang, H Chen, Z Lei, Z Tang, T Liu, K Xu International Workshop on Frontiers in Algorithmics, 252-263, 2014 | 7 | 2014 |
| Off-policy interval estimation with lipschitz value iteration Z Tang, Y Feng, N Zhang, J Peng, Q Liu Advances in Neural Information Processing Systems 33, 7887-7897, 2020 | 5 | 2020 |
| A reinforcement learning approach to estimating long-term treatment effects Z Tang, Y Duan, S Zhang, L Li arXiv preprint arXiv:2210.07536, 2022 | 3 | 2022 |
| Estimating Long-term Effects from Experimental Data Z Tang, Y Duan, S Zhu, S Zhang, L Li Proceedings of the 16th ACM Conference on Recommender Systems, 516-518, 2022 | 2 | 2022 |
| Operator Deep Q-Learning: Zero-Shot Reward Transferring in Reinforcement Learning Z Tang, Y Feng, Q Liu arXiv preprint arXiv:2201.00236, 2022 | 1 | 2022 |
| Efficient and safe off-policy evaluation: from point estimation to interval estimation Z Tang | | 2023 |
| A New Doubly Robust Policy Estimator on Infinite Horizon Reinforcement Learning Z Tang, Y Feng, Q Liu | | 2019 |
| Application of Compressed Sensing in Mobile Sparse Aperture Imaging Z Tang, M Wang | | 2016 |
Qiang LiuAssociate Professor of Computer Science, UT Austin在 cs.utexas.edu 的电子邮件经过验证
