| Deep subdomain adaptation network for image classification Y Zhu, F Zhuang, J Wang, G Ke, J Chen, J Bian, H Xiong, Q He IEEE transactions on neural networks and learning systems 32 (4), 1713-1722, 2020 | 920 | 2020 |
| 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 | 421 | 2014 |
| Finding the right facts in the crowd: factoid question answering over social media J Bian, Y Liu, E Agichtein, H Zha Proceedings of the 17th international conference on World Wide Web, 467-476, 2008 | 411 | 2008 |
| Listening to chaotic whispers: A deep learning framework for news-oriented stock trend prediction Z Hu, W Liu, J Bian, X Liu, TY Liu Proceedings of the eleventh ACM international conference on web search and …, 2018 | 399 | 2018 |
| Predicting information seeker satisfaction in community question answering Y Liu, J Bian, E Agichtein Proceedings of the 31st annual international ACM SIGIR conference on …, 2008 | 383 | 2008 |
| Model complexity of deep learning: A survey X Hu, L Chu, J Pei, W Liu, J Bian Knowledge and Information Systems 63, 2585-2619, 2021 | 337 | 2021 |
| Invertible image rescaling M Xiao, S Zheng, C Liu, Y Wang, D He, G Ke, J Bian, Z Lin, TY Liu Computer Vision–ECCV 2020: 16th European Conference, Glasgow, UK, August 23 …, 2020 | 272 | 2020 |
| 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 conference on …, 2014 | 252 | 2014 |
| Exploring social annotations for information retrieval D Zhou, J Bian, S Zheng, H Zha, CL Giles Proceedings of the 17th international conference on World Wide Web, 715-724, 2008 | 249 | 2008 |
| Evaluation of individual and ensemble probabilistic forecasts of COVID-19 mortality in the United States EY Cramer, EL Ray, VK Lopez, J Bracher, A Brennen, ... Proceedings of the National Academy of Sciences 119 (15), e2113561119, 2022 | 240 | 2022 |
| Knowledge-powered deep learning for word embedding J Bian, B Gao, TY Liu Machine Learning and Knowledge Discovery in Databases: European Conference …, 2014 | 239 | 2014 |
| Learning to recognize reliable users and content in social media with coupled mutual reinforcement J Bian, Y Liu, D Zhou, E Agichtein, H Zha Proceedings of the 18th international conference on World wide web, 51-60, 2009 | 225 | 2009 |
| Doc2EDAG: An end-to-end document-level framework for Chinese financial event extraction S Zheng, W Cao, W Xu, J Bian arXiv preprint arXiv:1904.07535, 2019 | 222 | 2019 |
| Naturalspeech 2: Latent diffusion models are natural and zero-shot speech and singing synthesizers K Shen, Z Ju, X Tan, Y Liu, Y Leng, L He, T Qin, S Zhao, J Bian arXiv preprint arXiv:2304.09116, 2023 | 205 | 2023 |
| Self-paced ensemble for highly imbalanced massive data classification Z Liu, W Cao, Z Gao, J Bian, H Chen, Y Chang, TY Liu 2020 IEEE 36th international conference on data engineering (ICDE), 841-852, 2020 | 198 | 2020 |
| A probabilistic model for learning multi-prototype word embeddings F Tian, H Dai, J Bian, B Gao, R Zhang, E Chen, TY Liu Proceedings of COLING 2014, the 25th International Conference on …, 2014 | 195 | 2014 |
| 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 | 184 | 2019 |
| Dual supervised learning Y Xia, T Qin, W Chen, J Bian, N Yu, TY Liu International conference on machine learning, 3789-3798, 2017 | 184 | 2017 |
| DeepGBM: A deep learning framework distilled by GBDT for online prediction tasks G Ke, Z Xu, J Zhang, J Bian, TY Liu Proceedings of the 25th ACM SIGKDD International Conference on Knowledge …, 2019 | 182 | 2019 |
| Connecting large language models with evolutionary algorithms yields powerful prompt optimizers Q Guo, R Wang, J Guo, B Li, K Song, X Tan, G Liu, J Bian, Y Yang arXiv preprint arXiv:2309.08532, 2023 | 164 | 2023 |
Tie-Yan LiuDistinguished Scientist, Microsoft Research AI4Science | IEEE Fellow | ACM Fellow | AAIA Fellow在 microsoft.com 的電子郵件地址已通過驗證
