Sequential click prediction for sponsored search with recurrent neural networks Y Zhang, H Dai, C Xu, J Feng, T Wang, J Bian, B Wang, TY Liu Proceedings of the AAAI conference on artificial intelligence 28 (1), 2014 | 404 | 2014 |
Rc-net: A general framework for incorporating knowledge into word representations C Xu, Y Bai, J Bian, B Gao, G Wang, X Liu, TY Liu Proceedings of the 23rd ACM international conference on information and …, 2014 | 246 | 2014 |
Health status assessment and failure prediction for hard drives with recurrent neural networks C Xu, G Wang, X Liu, D Guo, TY Liu IEEE Transactions on Computers 65 (11), 3502-3508, 2016 | 167 | 2016 |
Bag-of-words based deep neural network for image retrieval Y Bai, W Yu, T Xiao, C Xu, K Yang, WY Ma, T Zhao Proceedings of the 22nd ACM international conference on Multimedia, 229-232, 2014 | 51 | 2014 |
Rest: Relational event-driven stock trend forecasting W Xu, W Liu, C Xu, J Bian, J Yin, TY Liu Proceedings of the web conference 2021, 1-10, 2021 | 39 | 2021 |
Reinforcement learning for learning rate control C Xu, T Qin, G Wang, TY Liu arXiv preprint arXiv:1705.11159, 2017 | 32 | 2017 |
Automatic image dataset construction from click-through logs using deep neural network Y Bai, K Yang, W Yu, C Xu, WY Ma, T Zhao Proceedings of the 23rd ACM international conference on Multimedia, 441-450, 2015 | 31 | 2015 |
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 |
Modeling Local Dependence in Natural Language with Multi-channel Recurrent Neural Networks C Xu, H Weiran, W Hongwei, W Gang, L Tie-Yan AAAI 2019, 2019 | 15 | 2019 |
Polygon-Net: A General Framework for Jointly Boosting Multiple Unsupervised Neural Machine Translation Models C Xu, T Qin, G Wang, TY Liu IJCAI 2019, 2019 | 11 | 2019 |
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 |
Convolutional neural networks for posed and spontaneous expression recognition C Xu, T Qin, Y Bar, G Wang, TY Liu 2017 IEEE International Conference on Multimedia and Expo (ICME), 769-774, 2017 | 4 | 2017 |
An Actor-critic Algorithm for Learning Rate Learning C Xu, T Qin, G Wang, TY Liu | 1 | 2016 |
MG-TSD: Multi-Granularity Time Series Diffusion Models with Guided Learning Process X Fan, Y Wu, C Xu, Y Huang, W Liu, J Bian arXiv preprint arXiv:2403.05751, 2024 | | 2024 |
Microstructure-Empowered Stock Factor Extraction and Utilization X Jiao, Z Li, C Xu, Y Liu, W Liu, J Bian arXiv preprint arXiv:2308.08135, 2023 | | 2023 |
Efficient Behavior-consistent Calibration for Multi-agent Market Simulation T He, K Lu, C Xu, Y Liu, W Liu, SHG Chan, J Bian arXiv preprint arXiv:2307.12987, 2023 | | 2023 |