| Contextual Combinatorial Cascading Bandits S Li, B Wang, S Zhang, W Chen Proceedings of The 33rd International Conference on Machine Learning, 1245-1253, 2016 | 152 | 2016 |
| Improving prediction of phenotypic drug response on cancer cell lines using deep convolutional network P Liu, H Li, S Li, KS Leung BMC bioinformatics 20, 1-14, 2019 | 140 | 2019 |
| Toprank: A practical algorithm for online stochastic ranking T Lattimore, B Kveton, S Li, C Szepesvari Advances in Neural Information Processing Systems 31, 2018 | 78 | 2018 |
| Improved algorithm on online clustering of bandits S Li, W Chen, KS Leung arXiv preprint arXiv:1902.09162, 2019 | 77 | 2019 |
| Offline evaluation of ranking policies with click models S Li, Y Abbasi-Yadkori, B Kveton, S Muthukrishnan, V Vinay, Z Wen Proceedings of the 24th ACM SIGKDD International Conference on Knowledge …, 2018 | 75 | 2018 |
| Online influence maximization under linear threshold model S Li, F Kong, K Tang, Q Li, W Chen Advances in neural information processing systems 33, 1192-1204, 2020 | 47 | 2020 |
| Comparison-based conversational recommender system with relative bandit feedback Z Xie, T Yu, C Zhao, S Li Proceedings of the 44th International ACM SIGIR Conference on Research and …, 2021 | 44 | 2021 |
| A graph-enhanced click model for web search J Lin, W Liu, X Dai, W Zhang, S Li, R Tang, X He, J Hao, Y Yu Proceedings of the 44th international ACM SIGIR conference on research and …, 2021 | 41 | 2021 |
| Predicting associations among drugs, targets and diseases by tensor decomposition for drug repositioning R Wang, S Li, L Cheng, MH Wong, KS Leung BMC bioinformatics 20, 1-19, 2019 | 38 | 2019 |
| Online Clustering of Contextual Cascading Bandits S Li, S Zhang Thirty-Second AAAI Conference on Artificial Intelligence, 2018 | 36 | 2018 |
| An adversarial imitation click model for information retrieval X Dai, J Lin, W Zhang, S Li, W Liu, R Tang, X He, J Hao, J Wang, Y Yu Proceedings of the Web Conference 2021, 1809-1820, 2021 | 35 | 2021 |
| The closeness of in-context learning and weight shifting for softmax regression S Li, Z Song, Y Xia, T Yu, T Zhou arXiv preprint arXiv:2304.13276, 2023 | 34 | 2023 |
| Online learning to rank with features S Li, T Lattimore, C Szepesvári International Conference on Machine Learning, 3856-3865, 2019 | 34 | 2019 |
| Knowledge-aware conversational preference elicitation with bandit feedback C Zhao, T Yu, Z Xie, S Li Proceedings of the ACM Web Conference 2022, 483-492, 2022 | 25 | 2022 |
| Drug-protein-disease association prediction and drug repositioning based on tensor decomposition R Wang, S Li, MH Wong, KS Leung 2018 IEEE International Conference on Bioinformatics and Biomedicine (BIBM …, 2018 | 25 | 2018 |
| A robust and generalizable immune-related signature for sepsis diagnostics Y Yang, Y Zhang, S Li, X Zheng, MH Wong, KS Leung, L Cheng IEEE/ACM transactions on computational biology and bioinformatics 19 (6 …, 2021 | 23 | 2021 |
| Future-conditioned unsupervised pretraining for decision transformer Z Xie, Z Lin, D Ye, Q Fu, Y Wei, S Li International Conference on Machine Learning, 38187-38203, 2023 | 22 | 2023 |
| Clustering of conversational bandits for user preference learning and elicitation J Wu, C Zhao, T Yu, J Li, S Li Proceedings of the 30th ACM International Conference on Information …, 2021 | 21 | 2021 |
| Infoprompt: Information-theoretic soft prompt tuning for natural language understanding J Wu, T Yu, R Wang, Z Song, R Zhang, H Zhao, C Lu, S Li, R Henao Advances in Neural Information Processing Systems 36, 2024 | 20 | 2024 |
| Stochastic online learning with probabilistic graph feedback S Li, W Chen, Z Wen, KS Leung Proceedings of the AAAI Conference on Artificial Intelligence 34 (04), 4675-4682, 2020 | 20 | 2020 |
Tong YuAdobe Research在 andrew.cmu.edu 的电子邮件经过验证
