Online Influence Maximization under Linear Threshold Model. - Shuai Li 010; Fang Kong 002; Kejie Tang; Qizhi Li; Wei Chen 013 (NeurIPS, 2020)

The Hardness Analysis of Thompson Sampling for Combinatorial Semi-bandits with Greedy Oracle. - Fang Kong 002; Yueran Yang; Wei Chen 013; Shuai Li 010 (NeurIPS, 2021)

Simultaneously Learning Stochastic and Adversarial Bandits with General Graph Feedback. - Fang Kong 002; Yichi Zhou; Shuai Li 010 (ICML, 2022)

Thompson Sampling for Bandit Learning in Matching Markets. - Fang Kong 002; Junming Yin; Shuai Li 010 (IJCAI, 2022)

Online Influence Maximization under Decreasing Cascade Model. - Fang Kong 002; Jize Xie; Baoxiang Wang 001; Tao Yao; Shuai Li 010 (AAMAS, 2023)

Best-of-three-worlds Analysis for Linear Bandits with Follow-the-regularized-leader Algorithm. - Fang Kong 002; Canzhe Zhao; Shuai Li 010 (COLT, 2023)

Stochastic No-regret Learning for General Games with Variance Reduction. - Yichi Zhou; Fang Kong 002; Shuai Li 010 (ICLR, 2023)

Player-optimal Stable Regret for Bandit Learning in Matching Markets. - Fang Kong 002; Shuai Li 010 (SODA, 2023)

Improved Bandits in Many-to-One Matching Markets with Incentive Compatibility. - Fang Kong 002; Shuai Li 010 (AAAI, 2024)

Sequential Optimum Test with Multi-armed Bandits for Online Experimentation. - Fang Kong 002; Penglei Zhao; Shichao Han; Yong Wang; Shuai Li 010 (CIKM, 2024)

Improved Analysis for Bandit Learning in Matching Markets. - Fang Kong 002; Zilong Wang 010; Shuai Li 010 (NeurIPS, 2024)

Which LLM to Play? Convergence-Aware Online Model Selection with Time-Increasing Bandits. - Yu Xia 007; Fang Kong 002; Tong Yu 001; Liya Guo; Ryan A. Rossi; Sungchul Kim; Shuai Li 010 (WWW, 2024)

Improved Regret Bounds for Linear Adversarial MDPs via Linear Optimization. - Fang Kong 002; Xiangcheng Zhang; Baoxiang Wang 001; Shuai Li 010 (Trans. Mach. Learn. Res., 2024)

Bandit Learning in Matching Markets with Indifference. - Fang Kong 002; Jingqi Tang; Mingzhu Li; Pinyan Lu; John C. S. Lui; Shuai Li 010 (ICLR, 2025)

Online Multi-LLM Selection via Contextual Bandits under Unstructured Context Evolution. - Manhin Poon; Xiangxiang Dai; Xutong Liu 002; Fang Kong 002; John C. S. Lui; Jinhang Zuo (CoRR, 2025)