| 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 | 418 | 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 | 252 | 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 | 183 | 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 | 55 | 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 | 51 | 2021 |
| Reinforcement learning for learning rate control C Xu, T Qin, G Wang, TY Liu arXiv preprint arXiv:1705.11159, 2017 | 36 | 2017 |
| 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 | 35 | 2021 |
| 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 | 33 | 2015 |
| 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 | 26 | 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 | 17 | 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 | 12 | 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 | 10 | 2022 |
| MG-TSD: Multi-granularity time series diffusion models with guided learning process X Fan, Y Wu, C Xu, Y Huang, W Liu, J Bian The Twelfth International Conference on Learning Representations 2024, 2024 | 9 | 2024 |
| 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 | 5 | 2017 |
| An Actor-critic Algorithm for Learning Rate Learning C Xu, T Qin, G Wang, TY Liu | 2 | 2016 |
| MarS: a Financial Market Simulation Engine Powered by Generative Foundation Model J Li, Y Liu, W Liu, S Fang, L Wang, C Xu, J Bian arXiv preprint arXiv:2409.07486, 2024 | 1 | 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 | 1 | 2023 |
| Controllable Financial Market Generation with Diffusion Guided Meta Agent YH Huang, C Xu, Y Liu, W Liu, WJ Li, J Bian arXiv preprint arXiv:2408.12991, 2024 | | 2024 |
| Digger-Guider: High-Frequency Factor Extraction for Stock Trend Prediction Y Liu, C Xu, M Hou, W Liu, J Bian, Q LiuMember, TY LiuFellow IEEE Transactions on Knowledge and Data Engineering, 2024 | | 2024 |
| A multimodal stepwise-coordinating framework for pedestrian trajectory prediction Y Wang, Z Guo, C Xu, J Lin Knowledge-Based Systems, 112038, 2024 | | 2024 |
Jiang BianMicrosoft ResearchVerified email at microsoft.com
