| Attention-based LSTM for aspect-level sentiment classification Y Wang, M Huang, X Zhu, L Zhao Proceedings of the 2016 conference on empirical methods in natural language …, 2016 | 2347 | 2016 |
| Reinforcement learning for relation classification from noisy data J Feng, M Huang, L Zhao, Y Yang, X Zhu Proceedings of the aaai conference on artificial intelligence 32 (1), 2018 | 360 | 2018 |
| Learning structured representation for text classification via reinforcement learning T Zhang, M Huang, L Zhao Proceedings of the AAAI conference on artificial intelligence 32 (1), 2018 | 175 | 2018 |
| Adversarial neural machine translation L Wu, Y Xia, F Tian, L Zhao, T Qin, J Lai, TY Liu Asian Conference on Machine Learning, 534-549, 2018 | 140 | 2018 |
| Fully parameterized quantile function for distributional reinforcement learning D Yang, L Zhao, Z Lin, T Qin, J Bian, TY Liu Advances in neural information processing systems 32, 2019 | 131 | 2019 |
| Suphx: Mastering mahjong with deep reinforcement learning J Li, S Koyamada, Q Ye, G Liu, C Wang, R Yang, L Zhao, T Qin, TY Liu, ... arXiv preprint arXiv:2003.13590, 2020 | 111 | 2020 |
| Leveraging demonstrations for reinforcement recommendation reasoning over knowledge graphs K Zhao, X Wang, Y Zhang, L Zhao, Z Liu, C Xing, X Xie Proceedings of the 43rd international ACM SIGIR conference on research and …, 2020 | 90 | 2020 |
| Investment behaviors can tell what inside: Exploring stock intrinsic properties for stock trend prediction C Chen, L Zhao, J Bian, C Xing, TY Liu Proceedings of the 25th ACM SIGKDD International Conference on Knowledge …, 2019 | 72 | 2019 |
| Dual transfer learning for neural machine translation with marginal distribution regularization Y Wang, Y Xia, L Zhao, J Bian, T Qin, G Liu, TY Liu Proceedings of the AAAI Conference on Artificial Intelligence 32 (1), 2018 | 68 | 2018 |
| Individualized indicator for all: Stock-wise technical indicator optimization with stock embedding Z Li, D Yang, L Zhao, J Bian, T Qin, TY Liu Proceedings of the 25th ACM SIGKDD International Conference on Knowledge …, 2019 | 48 | 2019 |
| Efficient sequence learning with group recurrent networks F Gao, L Wu, L Zhao, T Qin, X Cheng, TY Liu Proceedings of the 2018 Conference of the North American Chapter of the …, 2018 | 48 | 2018 |
| Deep reinforcement learning for information retrieval: Fundamentals and advances W Zhang, X Zhao, L Zhao, D Yin, GH Yang, A Beutel Proceedings of the 43rd International ACM SIGIR Conference on Research and …, 2020 | 40 | 2020 |
| Trust region evolution strategies G Liu, L Zhao, F Yang, J Bian, T Qin, N Yu, TY Liu Proceedings of the AAAI Conference on Artificial Intelligence 33 (01), 4352-4359, 2019 | 38 | 2019 |
| Return-based contrastive representation learning for reinforcement learning G Liu, C Zhang, L Zhao, T Qin, J Zhu, J Li, N Yu, TY Liu arXiv preprint arXiv:2102.10960, 2021 | 35 | 2021 |
| Semi-supervised multinomial naive bayes for text classification by leveraging word-level statistical constraint L Zhao, M Huang, Z Yao, R Su, Y Jiang, X Zhu Proceedings of the AAAI Conference on Artificial Intelligence 30 (1), 2016 | 28 | 2016 |
| Word attention for sequence to sequence text understanding L Wu, F Tian, L Zhao, J Lai, TY Liu Proceedings of the AAAI Conference on Artificial Intelligence 32 (1), 2018 | 27 | 2018 |
| Curriculum offline imitating learning M Liu, H Zhao, Z Yang, J Shen, W Zhang, L Zhao, TY Liu Advances in Neural Information Processing Systems 34, 6266-6277, 2021 | 21 | 2021 |
| Sequence Prediction with Unlabeled Data by Reward Function Learning. L Wu, L Zhao, T Qin, J Lai, TY Liu IJCAI, 3098-3104, 2017 | 21 | 2017 |
| Towards deployment-efficient reinforcement learning: Lower bound and optimality J Huang, J Chen, L Zhao, T Qin, N Jiang, TY Liu arXiv preprint arXiv:2202.06450, 2022 | 19 | 2022 |
| Clustering aspect-related phrases by leveraging sentiment distribution consistency L Zhao, M Huang, H Chen, J Cheng, X Zhu Proceedings of the 2014 conference on empirical methods in natural language …, 2014 | 18 | 2014 |
Tie-Yan LiuDistinguished Scientist, Microsoft Research AI4Science | IEEE Fellow | ACM Fellow | AAIA FellowVerified email at microsoft.com
