Publications

Towards Provably Efficient Learning of Imperfect Information Extensive-Form Games with Linear Function Approximation
Canzhe Zhao, Shuze Chen, Weiming Liu, Haobo Fu, Qiang Fu, Shuai Li#.
Accepted in UAI, 2025.

Learning Imperfect Information Extensive-form Games with Last-iterate Convergence under Bandit Feedback
Canzhe Zhao, Yutian Cheng, Jing Dong, Baoxiang Wang, Shuai Li#.
Accepted in ICML, 2025.

Optimal Algorithm for Max-Min Fair Bandit
Zilong Wang, Zhiyao Zhang, Shuai Li#.
Accepted in ICML, 2025.

Improved Discretization Complexity Analysis of Consistency Models: Variance Exploding Forward Process and Decay Discretization Scheme
Ruofeng Yang, Bo Jiang, Cheng Chen, Shuai Li#.
Accepted in ICML, 2025.

Offline-to-Online Reinforcement Learning with Classifier-Free Diffusion Generation
Xiao Huang, Xu Liu, Enze Zhang, Tong Yu, Shuai Li#.
Accepted in ICML, 2025.

A Survey on Bandit Learning in Matching Markets
Shuai Li#, Zilong Wang, Fang Kong.
Accepted in IJCAI Survey Track, 2025.

Multi-player Multi-armed Bandits with Delayed Feedback
Jingqi Fan, Zilong Wang, Shuai Li#, Linghe Kong.
Accepted in IJCAI, 2025.

Fast Second-Order Online Kernel Learning through Incremental Matrix Sketching and Decomposition
Dongxie Wen, Xiao Zhang, Zhewei Wei, Chenping Hou, Shuai Li, Weinan Zhang.
Accepted in IJCAI, 2025.

Bandit Learning in Matching Markets with Indifference
Fang Kong, Jingqi Tang, Mingzhu Li, Pinyan Lu, John C.S. Lui, Shuai Li#.
Accepted in ICLR, 2025.

Online-to-Offline RL for Agent Alignment
Xu Liu, Haobo Fu, Stefano V Albrecht, Qiang Fu, Shuai Li#.
Accepted in ICLR, 2025.

The Polynomial Iteration Complexity for Variance Exploding Diffusion Models: Elucidating SDE and ODE Samplers
Ruofeng Yang, Bo Jiang, Shuai Li#.
Accepted in AISTATS, 2025.

Interactive Visualization Recommendation with Hier-SUCB
Songwen Hu, Ryan A. Rossi, Tong Yu, Junda Wu, Handong Zhao, Sungchul Kim, Shuai Li#.
Accepted in WWW (oral), 2025.

Adaptive Offline Data Replay in Offline-to-Online Reinforcement Learning
Xu Liu, Tong Yu, Shuai Li#.
Accepted in AAMAS (extended abstract), 2025.

Logarithmic Regret for Linear Markov Decision Processes with Adversarial Corruptions
Canzhe Zhao, XiangCheng Zhang, Baoxiang Wang, Shuai Li#.
Accepted in AAAI (oral), 2025.

Adaptive Merchant-Centric Risk Control via Unbiased Decision-Making and Dynamic Optimization in E-Commerce
Xu Liu, Yiqiang Lu, Jian liu, Tianyi Zhang, Weiqiang Wang, Qian Liu, Shuai Li#.
Accepted in the Thirty-Seventh Annual Conference on Innovative Applications of Artificial Intelligence (IAAI), 2025.

Beyond Chain-of-Thought: A Survey of Chain-of-X Paradigms for LLMs
Yu Xia, Rui Wang, Xu Liu, Mingyan Li, Tong Yu, Xiang Chen, Julian McAuley, Shuai Li#.
Accepted in COLING, 2025.

Improved Analysis for Bandit Learning in Matching Markets
Fang Kong, Zilong Wang, Shuai Li#.
The 38th Conference on Neural Information Processing Systems (NeurIPS). 2024.

Leveraging Drift to Improve Sample Complexity of Variance Exploding Diffusion Models [link]
Ruofeng Yang, Zhijie Wang, Bo Jiang, Shuai Li#.
The 38th Conference on Neural Information Processing Systems (NeurIPS). 2024.

Few-Shot Diffusion Models Escape the Curse of Dimensionality [link]
Ruofeng Yang, Bo Jiang, Cheng Chen, Ruinan Jin, Baoxiang Wang, Shuai Li#.
The 38th Conference on Neural Information Processing Systems (NeurIPS). 2024.

The Closeness of In-Context Learning and Weight Shifting for Softmax Regression
Shuai Li, Zhao Song, Yu Xia, Tong Yu, Tianyi Zhou.
The 38th Conference on Neural Information Processing Systems (NeurIPS). 2024.

Calibrating Reasoning in Language Models with Internal Consistency
Zhihui Xie, Jizhou Guo, Tong Yu, Shuai Li#.
The 38th Conference on Neural Information Processing Systems (NeurIPS). 2024.

Learning Versatile Skills with Curriculum Masking
Yao Tang, Zhihui Xie, Zichuan Lin, Deheng Ye, Shuai Li#.
The 38th Conference on Neural Information Processing Systems (NeurIPS). 2024.

Sequential Optimum Test with Multi-armed Bandits for Online Experimentation
Fang Kong, Penglei Zhao, Shichao Han, Yong Wang, Shuai Li#.
CIKM Applied, 2024.

Optimal Analysis for Bandit Learning in Matching Markets with Serial Dictatorship [link]
Zilong Wang, Shuai Li#.
[J] Theoretical Computer Science (TCS), 2024.

In-Context Learning on Function Classes Unveiled for Transformers [link]
Zhijie Wang, Bo Jiang, and Shuai Li#.
Proceedings of the 41st International Conference on Machine Learning (ICML), 2024.

Combinatorial Multivariant Multi-Armed Bandits with Applications to Episodic Reinforcement Learning and Beyond [arXiv][link]
Xutong Liu, Siwei Wang, Jinhang Zuo, Han Zhong, Xuchuang Wang, Zhiyong Wang, Shuai Li#, Mohammad Hajiesmaili, John C.S. Lui, and Wei Chen.
Proceedings of the 41st International Conference on Machine Learning (ICML), 2024.

Aligning as Debiasing: Causality-Aware Alignment via Reinforcement Learning with Interventional Feedback [link]
Yu Xia, Tong Yu, Zhankui He, Handong Zhao, Julian McAuley, and Shuai Li#.
Proceedings of the 2024 Conference of the North American Chapter of the Association for Computational Linguistics (NAACL), 2024.

Hallucination Diversity-Aware Active Learning for Text Summarization [arXiv][link]
Yu Xia*, Xu Liu*, Tong Yu#, Sungchul Kim, Ryan A. Rossi, Anup Rao, Tung Mai, and Shuai Li.
Proceedings of the 2024 Conference of the North American Chapter of the Association for Computational Linguistics (NAACL), 2024.

Which LLM to Play? Convergence-Aware Online Model Selection with Time-Increasing Bandits [arXiv][link]
Yu Xia*, Fang Kong*, Tong Yu, Liya Guo, Ryan A. Rossi, Sungchul Kim, and Shuai Li#.
Proceedings of the ACM Web Conference (WWW), 2024.

On Stationary Point Convergence of PPO-Clip [link]
Ruinan Jin, Shuai Li, and Baoxiang Wang.
The Twelfth International Conference on Learning Representations (ICLR), 2024.

Exploring Soft Prompt Initialization Strategy for Few-shot Continual Text Classification [link]
Zhehao Zhang, Tong Yu, Handong Zhao, Kaige Xie, Lina Yao, and Shuai Li.
IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), 2024.

Improved Bandits in Many-to-one Matching Markets with Incentive Compatibility [arXiv][link]
Fang Kong and Shuai Li#.
The Thirty-Eighth AAAI Conference on Artificial Intelligence (AAAI). 2024.

Improved Regret Bounds for Linear Adversarial MDPs via Linear Optimization [arXiv][link]
Fang Kong, Xiangcheng Zhang, Baoxiang Wang, and Shuai Li#.
[J] Transactions on Machine Learning Research (TMLR). 2024.

Towards Joint Utilization of Absolute and Relative Bandit Feedback for Conversational Recommendation [link]
Yu Xia, Zhihui Xie, Tong Yu, and Shuai Li#.
[J] User Modeling and User-Adapted Interaction (UMUAI). 2024.
Previous conference version:
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.

Interact with the Explanations: Causal Debiased Explainable Recommendation System [link]
Xu Liu, Tong Yu, Kaige Xie, Junda Wu, and Shuai Li#.
Proceedings of the 17th ACM International Conference on Web Search and Data Mining (WSDM). 2024.

Learning Adversarial Low-rank Markov Decision Processes with Unknown Transition and Full-information Feedback [link][arXiv]
Canzhe Zhao, Ruofeng Yang, Baoxiang Wang, Xuezhou Zhang, and Shuai Li#.
37th Conference on Neural Information Processing Systems (NeurIPS). 2023.

Adversarial Attacks on Online Learning to Rank with Click Feedback [link][arXiv]
Jinhang Zuo, Zhiyao Zhang, Zhiyong Wang, Shuai Li#, Mohammad Hajiesmaili, and Adam Wierman.
37th Conference on Neural Information Processing Systems (NeurIPS). 2023.

Online Corrupted User Detection and Regret Minimization [link][arXiv]
Zhiyong Wang, Jize Xie, Tong Yu, Shuai Li#, and John C.S. Lui.
37th Conference on Neural Information Processing Systems (NeurIPS). 2023.

Online Clustering of Bandits with Misspecified User Models [link][arXiv]
Zhiyong Wang, Jize Xie, Xutong Liu, Shuai Li#, and John C.S. Lui.
37th Conference on Neural Information Processing Systems (NeurIPS). 2023.

InfoPrompt: Information-Theoretic Soft Prompt Tuning for Natural Language Understanding [link][arXiv]
Junda Wu*, Tong Yu*, Rui Wang, Zhao Song, Ruiyi Zhang, Handong Zhao, Chaochao Lu, Shuai Li#, and Ricardo Henao.
37th Conference on Neural Information Processing Systems (NeurIPS). 2023.

User-Regulation Deconfounded Conversational Recommender System with Bandit Feedback [link][video]
Yu Xia, Junda Wu, Tong Yu#, Sungchul Kim, Ryan A. Rossi, and Shuai Li.
Proceedings of the 29th ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD Research Track). 2023.

Best-of-three-worlds Analysis for Linear Bandits with Follow-the-regularized-leader Algorithm [arXiv][link]
Fang Kong, Canzhe Zhao, and Shuai Li#.
Proceedings of Thirty Sixth Conference on Learning Theory (COLT). 2023.

Future-conditioned Unsupervised Pretraining for Decision Transformer [arXiv][link][code]
Zhihui Xie, Zichuan Lin, Deheng Ye, Qiang Fu, Yang Wei, and Shuai Li#.
Proceedings of the 40th International Conference on Machine Learning (ICML). 2023.

DPMAC: Differentially Private Communication for Cooperative Multi-Agent Reinforcement Learning [arXiv][link]
Canzhe Zhao, Yanjie Ze, Jing Dong, Baoxiang Wang, and Shuai Li#.
Proceedings of the Thirty-Second International Joint Conference on Artificial Intelligence (IJCAI). 2023.

bvnGPS: a generalizable diagnostic model for acute bacterial and viral infection using integrative host transcriptomics and pretrained neural networks [link]
Qizhi Li*, Xubin Zheng*, Jize Xie*, Ran Wang, Mengyao Li, Man-Hon Wong, Kwong-Sak Leung, Shuai Li, Qingshan Geng, Lixin Cheng.
[J] Bioinformatics. 2023.

Learning Adversarial Linear Mixture Markov Decision Processes with Bandit Feedback and Unknown Transition [link]
Canzhe Zhao, Ruofeng Yang, Baoxiang Wang and Shuai Li#.
The 11th International Conference on Learning Representations (ICLR). 2023.

Stochastic No-Regret Learning for General Games with Variance Reduction [link]
Yichi Zhou, Fang Kong and Shuai Li.
The 11th International Conference on Learning Representations (ICLR). 2023.

Clustering of Conversational Bandits with Posterior Sampling for User Preference Learning and Elicitation [link]
Qizhi Li*, Canzhe Zhao*, Tong Yu, Junda Wu and Shuai Li#.
[J] User Modeling and User-Adapted Interaction (UMUAI). 2023.
Previous conference version:
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.

Online Influence Maximization under Decreasing Cascade Model [link]
Fang Kong, Jize Xie, Baoxiang Wang, Tao Yao and Shuai Li#.
Proceedings of the 2023 International Conference on Autonomous Agents and Multiagent Systems (AAMAS). 2023.

CraftEnv: A Flexible Collective Robotic Construction Environment for Multi-Agent Reinforcement Learning [link][code]
Rui Zhao*, Xu Liu*, Yizheng Zhang*, Minghao Li, Cheng Zhou, Shuai Li and Lei Han#.
Proceedings of the 2023 International Conference on Autonomous Agents and Multiagent Systems (AAMAS). 2023.

Understanding Representation Learnability of Nonlinear Self-Supervised Learning [link]
Ruofeng Yang, Xiangyuan Li, Bo Jiang and Shuai Li#.
Proceedings of the AAAI Conference on Artificial Intelligence (AAAI, oral). 2023.

Efficient Explorative Key-term Selection Strategies for Conversational Contextual Bandits [arXiv][link][code]
Zhiyong Wang, Xutong Liu, Shuai Li# and John C.S. Lui.
Proceedings of the AAAI Conference on Artificial Intelligence (AAAI). 2023.

Few-Shot Composition Learning for Image Retrieval with Prompt Tuning [link]
Junda Wu, Rui Wang, Handong Zhao, Ruiyi Zhang, Chaochao Lu, Shuai Li and Ricardo Henao.
Proceedings of the AAAI Conference on Artificial Intelligence (AAAI). 2023.

Personalized Diversification for Neural Re-ranking in Recommendation [link]
Weiwen Liu*, Yunjia Xi*, Jiarui Qin, Xinyi Dai, Ruiming Tang#, Shuai Li, Weinan Zhang and Rui Zhang#.
IEEE 39th International Conference on Data Engineering (ICDE). 2023.

Differentially Private Temporal Difference Learning with Stochastic Nonconvex-Strongly-Concave Optimization [arXiv][link][code]
Canzhe Zhao, Yanjie Ze, Jing Dong, Baoxiang Wang and Shuai Li#.
Proceedings of the 16th ACM International Conference on Web Search and Data Mining (WSDM). 2023.

Player-optimal Stable Regret for Bandit Learning in Matching Markets [arXiv][link]
Fang Kong and Shuai Li#.
ACM-SIAM Symposium on Discrete Algorithms (SODA). 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 [link]
Junda Wu, Rui Wang, Tong Yu#, Ruiyi Zhang, Handong Zhao, Shuai Li, Ricardo Henao and Ani Nenkova.
Findings of Empirical Methods in Natural Language Processing (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, Spotlight). 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.
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.

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.

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).