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stat.ML2026
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…
stat.ML2026
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…