Adaptive quantitative trading: An imitative deep reinforcement learning approach Y Liu, Q Liu, H Zhao, Z Pan, C Liu Proceedings of the AAAI Conference on Artificial Intelligence 34 (02), 2128-2135, 2020 | 116 | 2020 |
Stock Trend Prediction with Multi-granularity Data: A Contrastive Learning Approach with Adaptive Fusion M Hou, C Xu, Y Liu, W Liu, J Bian, L Wu, Z Li, E Chen, TY Liu Proceedings of the 30th ACM International Conference on Information …, 2021 | 27 | 2021 |
Multi-Granularity Residual Learning with Confidence Estimation for Time Series Prediction M Hou, C Xu, Z Li, Y Liu, W Liu, E Chen, J Bian Proceedings of the ACM Web Conference 2022, 112-121, 2022 | 15 | 2022 |
Learning Differential Operators for Interpretable Time Series Modeling Y Luo, C Xu, Y Liu, W Liu, S Zheng, J Bian Proceedings of the 28th ACM SIGKDD Conference on Knowledge Discovery and …, 2022 | 8 | 2022 |
Long-term Joint Scheduling for Urban Traffic X Liang, L Wu, J Chen, Y Liu, R Yu, M Hou, H Wu, Y Ye, Q Liu, E Chen arXiv preprint arXiv:1910.12283, 2019 | 2 | 2019 |