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stat.ME2026
Optimal Data Integration and Adaptive Sampling for Efficient Treatment Effect Estimation
Yen-Chun Liu, Alexander Volfovsky, German Schnaidt +2
This study addresses the challenge of estimating average treatment effects (ATEs) for advertising campaigns in online marketplaces where complete randomized experimentation is infe…
stat.ME2025
Reinforcement Learning for Respondent-Driven Sampling
Justin Weltz, Angela Yoon, Yichi Zhang +2
Respondent-driven sampling (RDS) is widely used to study hidden or hard-to-reach populations by incentivizing study participants to recruit their social connections. The success an…