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2020 – today
- 2024
[j2]Yu Xia
, Zhihui Xie, Tong Yu, Canzhe Zhao, Shuai Li:
Toward joint utilization of absolute and relative bandit feedback for conversational recommendation. User Model. User Adapt. Interact. 34(5): 1707-1744 (2024)- 2023
- [j1]Qizhi Li, Canzhe Zhao, Tong Yu, Junda Wu, Shuai Li:
Clustering of conversational bandits with posterior sampling for user preference learning and elicitation. User Model. User Adapt. Interact. 33(5): 1065-1112 (2023) - [c9]Fang Kong, Canzhe Zhao, Shuai Li:
Best-of-three-worlds Analysis for Linear Bandits with Follow-the-regularized-leader Algorithm. COLT 2023: 657-673 - [c8]Canzhe Zhao, Ruofeng Yang, Baoxiang Wang, Shuai Li:
Learning Adversarial Linear Mixture Markov Decision Processes with Bandit Feedback and Unknown Transition. ICLR 2023 - [c7]Canzhe Zhao, Yanjie Ze, Jing Dong, Baoxiang Wang, Shuai Li:
DPMAC: Differentially Private Communication for Cooperative Multi-Agent Reinforcement Learning. IJCAI 2023: 4638-4646 - [c6]Canzhe Zhao, Ruofeng Yang, Baoxiang Wang, Xuezhou Zhang, Shuai Li:
Learning Adversarial Low-rank Markov Decision Processes with Unknown Transition and Full-information Feedback. NeurIPS 2023 - [c5]Canzhe Zhao, Yanjie Ze, Jing Dong, Baoxiang Wang, Shuai Li:
Differentially Private Temporal Difference Learning with Stochastic Nonconvex-Strongly-Concave Optimization. WSDM 2023: 985-993 - [i7]Fang Kong, Canzhe Zhao, Shuai Li:
Best-of-three-worlds Analysis for Linear Bandits with Follow-the-regularized-leader Algorithm. CoRR abs/2303.06825 (2023) - [i6]Canzhe Zhao, Yanjie Ze, Jing Dong, Baoxiang Wang, Shuai Li:
DPMAC: Differentially Private Communication for Cooperative Multi-Agent Reinforcement Learning. CoRR abs/2308.09902 (2023) - [i5]Canzhe Zhao, Ruofeng Yang, Baoxiang Wang, Xuezhou Zhang, Shuai Li:
Learning Adversarial Low-rank Markov Decision Processes with Unknown Transition and Full-information Feedback. CoRR abs/2311.07876 (2023) - 2022
- [c4]Cheng Chen, Canzhe Zhao, Shuai Li:
Simultaneously Learning Stochastic and Adversarial Bandits under the Position-Based Model. AAAI 2022: 6202-6210 - [c3]Canzhe Zhao, Tong Yu, Zhihui Xie, Shuai Li:
Knowledge-aware Conversational Preference Elicitation with Bandit Feedback. WWW 2022: 483-492 - [i4]Canzhe Zhao, Yanjie Ze, Jing Dong, Baoxiang Wang, Shuai Li:
Differentially Private Temporal Difference Learning with Stochastic Nonconvex-Strongly-Concave Optimization. CoRR abs/2201.10447 (2022) - [i3]Cheng Chen, Canzhe Zhao, Shuai Li:
Simultaneously Learning Stochastic and Adversarial Bandits under the Position-Based Model. CoRR abs/2207.05437 (2022) - [i2]Zhihui Xie, Tong Yu, Canzhe Zhao, Shuai Li:
Comparison-based Conversational Recommender System with Relative Bandit Feedback. CoRR abs/2208.09837 (2022) - 2021
- [c2]Junda Wu, Canzhe Zhao, Tong Yu, Jingyang Li, Shuai Li:
Clustering of Conversational Bandits for User Preference Learning and Elicitation. CIKM 2021: 2129-2139 - [c1]Zhihui Xie, Tong Yu, Canzhe Zhao, Shuai Li:
Comparison-based Conversational Recommender System with Relative Bandit Feedback. SIGIR 2021: 1400-1409 - [i1]Kun Wang, Canzhe Zhao, Shuai Li, Shuo Shao:
Conservative Contextual Combinatorial Cascading Bandit. CoRR abs/2104.08615 (2021)
Coauthor Index
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