Fang Kong

27 papers A* 12A 2Journal 13
YearRankTypeTitle / Venue / Authors
2026 J jnl
Bandit learning in matching markets with relative feedback.
Theor. Comput. Sci.
Fang Kong, Xiaoxi Zhang, Xiao Huang, Lijun Zhang, Shuai Li
2026 A* conf
Online Multi-LLM Selection via Contextual Bandits Under Unstructured Context Evolution.
AAAI
Manhin Poon, Xiangxiang Dai, Xutong Liu, Fang Kong, John C. S. Lui, Jinhang Zuo
2025 A* conf
Bandit Learning in Matching Markets with Indifference.
ICLR
Fang Kong, Jingqi Tang, Mingzhu Li, Pinyan Lu, John C. S. Lui, Shuai Li
2025 J jnl
Online Multi-LLM Selection via Contextual Bandits under Unstructured Context Evolution.
CoRR
Manhin Poon, Xiangxiang Dai, Xutong Liu, Fang Kong, John C. S. Lui, Jinhang Zuo
2024 A* conf
Improved Analysis for Bandit Learning in Matching Markets.
NeurIPS
Fang Kong, Zilong Wang, Shuai Li
2024 A* conf
Improved Bandits in Many-to-One Matching Markets with Incentive Compatibility.
AAAI
Fang Kong, Shuai Li
2024 J jnl
Improved Bandits in Many-to-one Matching Markets with Incentive Compatibility.
CoRR
Fang Kong, Shuai Li
2024 J jnl
Improved Regret Bounds for Linear Adversarial MDPs via Linear Optimization.
Trans. Mach. Learn. Res.
Fang Kong, Xiangcheng Zhang, Baoxiang Wang, Shuai Li
2024 A conf
Sequential Optimum Test with Multi-armed Bandits for Online Experimentation.
CIKM
Fang Kong, Penglei Zhao, Shichao Han, Yong Wang, Shuai Li
2024 A* conf
Which LLM to Play? Convergence-Aware Online Model Selection with Time-Increasing Bandits.
WWW
Yu Xia, Fang Kong, Tong Yu, Liya Guo, Ryan A. Rossi, Sungchul Kim, Shuai Li
2024 J jnl
Which LLM to Play? Convergence-Aware Online Model Selection with Time-Increasing Bandits.
CoRR
Yu Xia, Fang Kong, Tong Yu, Liya Guo, Ryan A. Rossi, Sungchul Kim, Shuai Li
2023 A* conf
Best-of-three-worlds Analysis for Linear Bandits with Follow-the-regularized-leader Algorithm.
COLT
Fang Kong, Canzhe Zhao, Shuai Li
2023 J jnl
Best-of-three-worlds Analysis for Linear Bandits with Follow-the-regularized-leader Algorithm.
CoRR
Fang Kong, Canzhe Zhao, Shuai Li
2023 J jnl
Improved Regret Bounds for Linear Adversarial MDPs via Linear Optimization.
CoRR
Fang Kong, Xiangcheng Zhang, Baoxiang Wang, Shuai Li
2023 A conf
Online Influence Maximization under Decreasing Cascade Model.
AAMAS
Fang Kong, Jize Xie, Baoxiang Wang, Tao Yao, Shuai Li
2023 J jnl
Online Influence Maximization under Decreasing Cascade Model.
CoRR
Fang Kong, Jize Xie, Baoxiang Wang, Tao Yao, Shuai Li
2023 A* conf
Player-optimal Stable Regret for Bandit Learning in Matching Markets.
SODA
Fang Kong, Shuai Li
2023 J jnl
Player-optimal Stable Regret for Bandit Learning in Matching Markets.
CoRR
Fang Kong, Shuai Li
2023 A* conf
Stochastic No-regret Learning for General Games with Variance Reduction.
ICLR
Yichi Zhou, Fang Kong, Shuai Li
2022 A* conf
Simultaneously Learning Stochastic and Adversarial Bandits with General Graph Feedback.
ICML
Fang Kong, Yichi Zhou, Shuai Li
2022 J jnl
Simultaneously Learning Stochastic and Adversarial Bandits with General Graph Feedback.
CoRR
Fang Kong, Yichi Zhou, Shuai Li
2022 A* conf
Thompson Sampling for Bandit Learning in Matching Markets.
IJCAI
Fang Kong, Junming Yin, Shuai Li
2022 J jnl
Thompson Sampling for Bandit Learning in Matching Markets.
CoRR
Fang Kong, Junming Yin, Shuai Li
2021 A* conf
The Hardness Analysis of Thompson Sampling for Combinatorial Semi-bandits with Greedy Oracle.
NeurIPS
Fang Kong, Yueran Yang, Wei Chen, Shuai Li
2021 J jnl
The Hardness Analysis of Thompson Sampling for Combinatorial Semi-bandits with Greedy Oracle.
CoRR
Fang Kong, Yueran Yang, Wei Chen, Shuai Li
2020 A* conf
Online Influence Maximization under Linear Threshold Model.
NeurIPS
Shuai Li, Fang Kong, Kejie Tang, Qizhi Li, Wei Chen
2020 J jnl
Online Influence Maximization under Linear Threshold Model.
CoRR
Shuai Li, Fang Kong, Kejie Tang, Qizhi Li, Wei Chen