Research Interests

Online Learning, Reinforcement Learning, Machine Learning

Education

2020.9-2024.6 Shanghai Jiao Tong University, PhD in Computer Science

2016.9-2020.6 Shandong University, Bachelor’s Degree in Software Engineering

Research Experiences

2023.2-2023.8 The Chinese University of Hong Kong, Research Assistant

2022.7-2024.7 Tencent WXG, Research Intern

2021.12-2022.5 Microsoft Research Asia, Research Intern

2021.6-2021.8 Alibaba DAMO Academy, Research Intern

Publications

1. Yu Xia*, Fang Kong*, Tong Yu, Liya Guo, Ryan A. Rossi, Sungchul Kim, Shuai Li, “Convergence-Aware Online Model Selection with Time-Increasing Bandits”, The Web Conference (WWW), 2024.

2. Fang Kong, Shuai Li, “Improved Bandits in Many-to-one Matching Markets with Incentive Compatibility”, Proceedings of the 38th Annual AAAI Conference on Artificial Intelligence (AAAI), 2024. 

3. Fang Kong*, Xiangcheng Zhang*, Baoxiang Wang, Shuai Li, “Improved Regret Bounds for Linear Adversarial MDPs via Linear Optimization”, Transactions on Machine Learning Research (TMLR), 2024.

4. Fang Kong, Canzhe Zhao, Shuai Li, “Best-of-three-worlds Analysis for Linear Bandits with Follow-the-regularized-leader Algorithm”, Proceedings of the 36th Conference on Learning Theory (COLT), 2023.

5. Fang Kong, Jize Xie, Baoxiang Wang, Tao Yao, Shuai Li. “Online Influence Maximization under Decreasing Cascade Model”, Proceedings of the 22nd International Conference on Autonomous Agents and Multiagent Systems (AAMAS), 2023.

6. Yichi Zhou, Fang Kong, Shuai Li, “Stochastic No-Regret Learning for General Games with Variance Reduction”, International Conference on Learning Representations (ICLR), 2023.

7. Fang Kong, Shuai Li, “Player-optimal Stable Regret for Bandit Learning in Matching Markets”, Proceedings of the 2023 Annual ACM-SIAM Symposium on Discrete Algorithms (SODA). 2023.

8. Fang Kong, Yichi Zhou, Shuai Li, “Simultaneously Learning Stochastic and Adversarial Bandits with General Graph Feedback”, International Conference on Machine Learning (ICML), 2022.

9. Fang Kong, Junming Yin, Shuai Li, “Thompson Sampling for Bandit Learning in Matching Markets”, International Joint Conference on Artificial Intelligence (IJCAI), 2022.

10. Fang Kong, Yueran Yang, Wei Chen, Shuai Li, “The Hardness Analysis of Thompson Sampling for Combinatorial Semi-bandits with Greedy Oracle”, Proceedings of the Conference on Neural Information Processing Systems (NeurIPS), 2021.

11. Fang Kong, Yueran Yang, Wei Chen, Shuai Li, “Combinatorial Online Learning based on Optimizing Feedbacks (in Chinese)”, Big Data Research, 2021.

12. Shuai Li, Fang Kong, Kejie Tang, Qizhi Li, Wei Chen, “Online Influence Maximization under Linear Threshold Model”, Proceedings of the Conference on Neural Information Processing Systems (NeurIPS), 2020.

13. Fang Kong, Qizhi Li, Shuai Li, “A Survey on Online Influence Maximization” (in Chinese), Computer Science, 2020.