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Publications

  • Learning Adversarial Linear Mixture Markov Decision Processes with Bandit Feedback and Unknown Transition
    Canzhe Zhao, Ruofeng Yang, Baoxiang Wang and Shuai Li#.
    Accepted in ICLR. 2023.

  • Stochastic No-Regret Learning for General Games with Variance Reduction
    Yichi Zhou, Fang Kong and Shuai Li.
    Accepted in ICLR. 2023.

  • Online Influence Maximization under Decreasing Cascade Model
    Fang Kong, Jize Xie, Baoxiang Wang, Tao Yao and Shuai Li#.
    Accepted in AAMAS. 2023.

  • CraftEnv: A Flexible Collective Robotic Construction Environment for Multi-Agent Reinforcement Learning
    Rui Zhao*, Xu Liu*, Yizheng Zhang*, Minghao Li, Cheng Zhou, Shuai Li and Lei Han#.
    Accepted in AAMAS. 2023.

  • Understanding Representation Learnability of Nonlinear Self-Supervised Learning
    Ruofeng Yang, Xiangyuan Li, Bo Jiang and Shuai Li#.
    Accepted in AAAI. 2023.

  • Efficient Explorative Key-term Selection Strategies for Conversational Contextual Bandits
    Zhiyong Wang, Xutong Liu, Shuai Li# and John C.S. Lui.
    Accepted in AAAI. 2023.

  • Few-Shot Composition Learning for Image Retrieval with Prompt Tuning
    Junda Wu, Rui Wang, Handong Zhao, Ruiyi Zhang, Chaochao Lu, Shuai Li and Ricardo Henao.
    Accepted in AAAI. 2023.

  • Personalized Diversification for Neural Re-ranking in Recommendation
    Weiwen Liu*, Yunjia Xi*, Jiarui Qin, Xinyi Dai, Ruiming Tang#, Shuai Li, Weinan Zhang and Rui Zhang#.
    Accepted in ICDE. 2023.

  • Differentially Private Temporal Difference Learning with Stochastic Nonconvex-Strongly-Concave Optimization [arXiv]
    Canzhe Zhao, Yanjie Ze, Jing Dong, Baoxiang Wang and Shuai Li#.
    Accepted in WSDM. 2023.

  • Discovering Low-rank Subspaces for Language-agnostic Multilingual Representations [link][code]
    Zhihui Xie, Handong Zhao, Tong Yu and Shuai Li#.
    Proceedings of the 2022 Conference on Empirical Methods in Natural Language Processing (EMNLP). 2022.

  • Context-aware Information-theoretic Causal De-biasing for Interactive Sequence Labeling
    Junda Wu, Rui Wang, Tong Yu#, Ruiyi Zhang, Handong Zhao, Shuai Li, Ricardo Henao and Ani Nenkova.
    Accepted in Findings of EMNLP. 2022.

  • Bandit Learning in Many-to-One Matching Markets [link][code]
    Zilong Wang, Liya Guo, Junming Yin and Shuai Li#.
    Proceedings of the 31st ACM International Conference on Information & Knowledge Management (CIKM). 2022.

  • Hierarchical Conversational Preference Elicitation with Bandit Feedback [arXiv][link]
    Jinhang Zuo, Songwen Hu, Tong Yu, Shuai Li#, Handong Zhao and Carlee Joe-Wong.
    Proceedings of the 31st ACM International Conference on Information & Knowledge Management (CIKM). 2022.

  • Spatial-Temporal Aligned Multi-Agent Learning for Visual Dialog Systems [link]
    Yong Zhuang, Tong Yu, Junda Wu, Shiqu Wu, Shuai Li#.
    Proceedings of the 30th ACM International Conference on Multimedia (MM). 2022.

  • Federated Online Clustering of Bandits [link][code]
    Xutong Liu, Haoru Zhao, Tong Yu, Shuai Li#, John C.S. Lui.
    The 38th Conference on Uncertainty in Artificial Intelligence (UAI). 2022.

  • Simultaneously Learning Stochastic and Adversarial Bandits with General Graph Feedback [arXiv][link]
    Fang Kong, Yichi Zhou, Shuai Li#.
    The 39th International Conference on Machine Learning (ICML). 2022.

  • Thompson Sampling for Bandit Learning in Matching Markets [arXiv][link][code]
    Fang Kong, Junming Yin, Shuai Li#.
    The 31st International Joint Conference on Artificial Intelligence (IJCAI). 2022.

  • Dynamics-Aware Adaptation for Reinforcement Learning Based Cross-Domain Interactive Recommendation [link]
    Junda Wu*, Zhihui Xie*, Tong Yu, Handong Zhao, Ruiyi Zhang, Shuai Li#.
    Proceedings of the 45th International ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR). 2022.
    Previous version:
    Sim-to-Real Interactive Recommendation via Off-Dynamics Reinforcement Learning [link]
    Junda Wu, Zhihui Xie, Tong Yu, Qizhi Li, Shuai Li#.
    Presented in the 2nd Offline Reinforcement Learning Workshop in NeurIPS, 2021.

  • Cascading Bandit under Differential Privacy [arXiv][link]
    Kun Wang, Jing Dong, Baoxiang Wang, Shuai Li, Shuo Shao.
    IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP). 2022.

  • Learning to Plan Variable Length Sequences of Actions with a Cascading Bandit Click Model of User Feedback [arXiv][link]
    Anirban Santara, Gaurav Aggarwal, Shuai Li, Claudio Gentile.
    The 25th International Conference on Artificial Intelligence and Statistics (AISTATS). 2022.

  • Knowledge-aware Conversational Preference Elicitation with Bandit Feedback [link][code][video]
    Canzhe Zhao, Tong Yu, Zhihui Xie, Shuai Li#.
    The Web Conference (WWW). 2022.

  • Simultaneously Learning Stochastic and Adversarial Bandits under the Position-based Model [arXiv][link][video][code]
    Cheng Chen, Canzhe Zhao, Shuai Li#.
    The 36th AAAI Conference on Artificial Intelligence (AAAI). 2022.

  • Combinatorial Bandits under Strategic Manipulations [arXiv][link][code]
    Jing Dong, Ke Li, Shuai Li, Baoxiang Wang#.
    Proceedings of the 15th ACM International Conference on Web Search and Data Mining (WSDM). 2022.

  • The Hardness Analysis of Thompson Sampling for Combinatorial Semi-bandits with Greedy Oracle [link][arXiv]
    Fang Kong, Yueran Yang, Wei Chen, Shuai Li#.
    Thirty-fifth Conference on Neural Information Processing Systems (NeurIPS). 2021.

  • Understanding Bandits with Graph Feedback [arXiv][link]
    Houshuang Chen, Zengfeng Huang, Shuai Li, Chihao Zhang#. (alphabetical order)
    Thirty-fifth Conference on Neural Information Processing Systems (NeurIPS). 2021.

  • Combinatorial online learning based on optimizing feedbacks (in Chinese) [link]
    Fang Kong, Yueran Yang, Wei Chen, Shuai Li#.
    Big Data Research. 2021.

  • A robust and generalizable immune-related signature for sepsis diagnostics [link]
    Yueran Yang*, Yu Zhang*, Shuai Li, Xubin Zheng, Man Hon Wong, Kwong-Sak Leung, Lixin Cheng#
    IEEE/ACM Transactions on Computational Biology and Bioinformatics (TCBB). 2021.

  • Clustering of Conversational Bandits for User Preference Learning and Elicitation [link]
    Junda Wu*, Canzhe Zhao*, Tong Yu, Jingyang Li, Shuai Li#.
    Proceedings of the 30th ACM International Conference on Information & Knowledge Management (CIKM). 2021.

  • Deconfounded and Explainable Interactive Vision-Language Retrieval of Complex Scenes [link]
    Junda Wu, Tong Yu, Shuai Li#.
    Proceedings of the 29th ACM International Conference on Multimedia (MM). 2021.

  • Comparison-based Conversational Recommender System with Relative Bandit Feedback [link][code]
    Zhihui Xie, Tong Yu, Canzhe Zhao, Shuai Li#.
    The 44th International ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR). 2021.

  • A Graph-Enhanced Click Model for Web Search [link]
    Jianghao Lin, Weiwen Liu, Xinyi Dai, Weinan Zhang#, Shuai Li, Ruiming Tang, Xiuqiang He, Jianye Hao and Yong Yu.
    The 44th International ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR). 2021.

  • An Adversarial Imitation Click Model for Information Retrieval [arXiv][link][code][video]
    Xinyi Dai, Jianghao Lin, Weinan Zhang#, Shuai Li, Weiwen Liu, Ruiming Tang, Xiuqiang He, Jianye Hao, Jun Wang, Yong Yu.
    30th The Web Conference (WWW). 2021.

  • Online Influence Maximization under Linear Threshold Model [arXiv][link][slides][poster]
    Shuai Li#, Fang Kong, Kejie Tang, Qizhi Li, Wei Chen.
    The 34th Conference on Neural Information Processing Systems (NeurIPS). 2020.

  • A Survey on Online Influence Maximization (in Chinese) [link]
    Fang Kong, Qizhi Li, Shuai Li#.
    Computer Science. 2020.

  • The Gambler’s Problem and Beyond [arXiv]
    Baoxiang Wang, Shuai Li, Jiajin Li, Siu On Chan.
    Eighth International Conference on Learning Representations (ICLR). 2020.
    Also presented at the OptRL workshop in NeurIPS 2019.

  • Stochastic Online Learning with Probabilistic Graph Feedback [arXiv][link][slides][poster]
    Shuai Li, Wei Chen, Zheng Wen, Kwong-Sak Leung.
    The 34th AAAI Conference on Artificial Intelligence (AAAI). 2020.

  • Predicting Associations among Drugs, Targets and Diseases by Tensor Decomposition for Drug Repositioning [link]
    Ran Wang, Shuai Li, Lixin Cheng, Man-Hon Wong, Kwong-Sak Leung.
    BMC Bioinformatics, 2019.
    Previous conference version:
    Drug-Protein-Disease Association Prediction and Drug Repositioning Based on Tensor Decomposition [link]
    Ran Wang, Shuai Li, Man-Hon Wong, Kwong-Sak Leung.
    IEEE International Conference on Bioinformatics and Biomedicine (BIBM), 2018.

  • Improving Prediction of Phenotypic Drug Response on Cancer Cell Lines Using Deep Convolutional Network [link]
    Pengfei Liu, Hongjian Li, Shuai Li, Kwong-Sak Leung.
    BMC Bioinformatics, 2019.

  • Improved Algorithm on Online Clustering of Bandits [link][arXiv][code][slides]
    Shuai Li, Wei Chen, S Li, Kwong-Sak Leung.
    The 28th International Joint Conference on Artificial Intelligence (IJCAI), 2019.

  • Online Learning to Rank with Features [link][arXiv][code][slides][poster]
    Shuai Li, Tor Lattimore, Csaba Szepesvari.
    The 36th International Conference on Machine Learning (ICML), 2019.

  • TopRank: A Practical Algorithm for Online Stochastic Ranking [link][arXiv][poster]
    Tor Lattimore, Branislav Kveton, Shuai Li, Csaba Szepesvari.
    The 32nd Conference on Neural Information Processing Systems (NeurIPS). 2018.

  • Offline Evaluations of Ranking Policies with Click Models [link][arXiv][slides][poster][video]
    Shuai Li, Yasin Abbasi-Yadkori, Branislav Kveton, S. Muthukrishnan, Vishwa Vinay, Zheng Wen.
    The 24th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining (KDD Research Track). 2018.
    Also presented in the CausalML Workshop of ICML 2018.

  • Contextual Dependent Click Bandit Algorithm for Web Recommendation [pdf]
    Weiwen Liu, Shuai Li, Shengyu Zhang.
    International Computing and Combinatorics Conference (COCOON), pp. 39-50. Springer, Cham, 2018.

  • Online Clustering of Contextual Cascading Bandits [link][arXiv][slides][poster]
    Shuai Li, Shengyu Zhang.
    The 32nd AAAI Conference on Artificial Intelligence (AAAI). 2018.

  • Contextual Combinatorial Cascading Bandits [link][slides][poster]
    Shuai Li, Baoxiang Wang, Shengyu Zhang, Wei Chen.
    The 33rd International Conference on Machine Learning (ICML), pp. 1245-1253. 2016.
    Also presented in the International Doctoral Forum (oral), Hong Kong, 2016.

  • A Hybrid Distributed Framework for SNP Selections [pdf]
    Pengfei Liu, Shuai Li, Weiying Yi, Kwong-Sak Leung.
    Proceedings of the International Conference on Parallel and Distributed Processing Techniques and Applications (PDPTA), p. 192.
    The Steering Committee of The World Congress in Computer Science, Computer Engineering and Applied Computing (WorldComp), 2016.

  • Design for Triangular Rational Bezier Harmonic and Biharmonic Surfaces (in Chinese) [pdf]
    Shuai Li, Xiaoqian Xu, Guojin Wang
    Journal of Zhejiang University (Science Edition) 2012 39 (2).