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stat.ML2025
Scalable Policy Maximization Under Network Interference
Aidan Gleich, Eric Laber, Alexander Volfovsky
Many interventions, such as vaccines in clinical trials or coupons in online marketplaces, must be assigned sequentially without full knowledge of their effects. Multi-armed bandit…
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…