4 papers
Reinforcement Learning in the Real World: A Survey of Statistical Challenges and Future Directions
Asim H. Gazi, Yongyi Guo, Daiqi Gao +3
Reinforcement learning (RL) has achieved remarkable success in real-world decision-making across diverse domains, including gaming, robotics, online advertising, public health, and…
Statistical Inference for Misspecified Contextual Bandits
Yongyi Guo, Ziping Xu
Contextual bandit algorithms have transformed modern experimentation by enabling real-time adaptation for personalized treatment. Yet these advantages create challenges for statist…
Learning with Incomplete Context: Linear Contextual Bandits with Pretrained Imputation
Hao Yan, Heyan Zhang, Yongyi Guo
The rise of large-scale pretrained models has made it feasible to generate predictive or synthetic features at low cost, raising the question of how to incorporate such surrogate p…
Statistical Inference for Misspecified Contextual Bandits
Yongyi Guo, Ziping Xu
Contextual bandit algorithms have transformed modern experimentation by enabling real-time adaptation for personalized treatment and efficient use of data. Yet these advantages cre…