Fang Kong - RankMe

27 papers A* 12A 2Journal 13

Year	Rank	Type	Title / 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