1 citations · 1 across the 5 of their papers we have counts for
5 papers
Robust Sequential Experimental Design for A/B Testing
Qianglin Wen, Xiangkun Wu, Chengchun Shi +4
Experimental design has emerged as a powerful approach for improving the sample efficiency of A/B testing, yet existing designs rely critically on correctly specified models. We st…
Designing Time Series Experiments in A/B Testing with Transformer Reinforcement Learning
Xiangkun Wu, Qianglin Wen, Yingying Zhang +3
A/B testing has become a gold standard for modern technological companies to conduct policy evaluation. Yet, its application to time series experiments, where policies are sequenti…
A Two-armed Bandit Framework for A/B Testing
Jinjuan Wang, Qianglin Wen, Yu Zhang +2
A/B testing is widely used in modern technology companies for policy evaluation and product deployment, with the goal of comparing the outcomes under a newly-developed policy again…
Combining Experimental and Historical Data for Policy Evaluation
Ting Li, Chengchun Shi, Qianglin Wen +4
This paper studies policy evaluation with multiple data sources, especially in scenarios that involve one experimental dataset with two arms, complemented by a historical dataset g…
Unraveling the Interplay between Carryover Effects and Reward Autocorrelations in Switchback Experiments
Qianglin Wen, Chengchun Shi, Ying Yang +2
A/B testing has become the gold standard for policy evaluation in modern technological industries. Motivated by the widespread use of switchback experiments in A/B testing, this pa…