1 citations · 1 across the 4 of their papers we have counts for
4 papers
Inverse Contextual Bandits without Rewards: Learning from a Non-Stationary Learner via Suffix Imitation
Yuqi Kong, Xiao Zhang, Weiran Shen
We study the Inverse Contextual Bandit (ICB) problem, in which a learner seeks to optimize a policy while an observer, who cannot access the learner's rewards and only observes act…
Enhancing Long-Term Welfare in Recommender Systems: An Information Revelation Approach
Xu Zhao, Xiaopeng Ye, Chen Xu +2
Improving the long-term user welfare (e.g., sustained user engagement) has become a central objective of recommender systems (RS). In real-world platforms, the creation behaviors o…
AAVDiff: Experimental Validation of Enhanced Viability and Diversity in Recombinant Adeno-Associated Virus (AAV) Capsids through Diffusion Generation
Lijun Liu, Jiali Yang, Jianfei Song +8
Recombinant adeno-associated virus (rAAV) vectors have revolutionized gene therapy, but their broad tropism and suboptimal transduction efficiency limit their clinical applications…
IBCB: Efficient Inverse Batched Contextual Bandit for Behavioral Evolution History
Yi Xu, Weiran Shen, Xiao Zhang +1
Traditional imitation learning focuses on modeling the behavioral mechanisms of experts, which requires a large amount of interaction history generated by some fixed expert. Howeve…