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Linglong Kong

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#reinforcement learning Open access Sep 2026

ARMA-Design: Optimal Treatment Allocation Strategies for A/B Testing in Partially Observable Experiments

Online experiments are frequently employed in technological companies to evaluate the performance of a newly developed policy, product, or treatment relative to a baseline control. In many applications, the experimental units receive a sequence of treatments over time. To handle these time-dependent settings, existing...

Ke Sun, Linglong Kong, Hongtu Zhu et al. · 0 citations

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