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Experimentation Platforms Meet Reinforcement Learning: Bayesian Sequential Decision-Making for Continuous Monitoring.

, , , , and . KDD, page 5016-5027. ACM, (2023)

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STEEL: Singularity-aware Reinforcement Learning., , and . CoRR, (2023)Effect Size Estimation for Duration Recommendation in Online Experiments: Leveraging Hierarchical Models and Objective Utility Approaches., , , , , and . CoRR, (2023)Effect Size Estimation for Duration Recommendation in Online Experiments: Leveraging Hierarchical Models and Objective Utility Approaches., , , , , and . AAAI, page 14044-14051. AAAI Press, (2024)Safe Exploration for Efficient Policy Evaluation and Comparison., , and . ICML, volume 162 of Proceedings of Machine Learning Research, page 22491-22511. PMLR, (2022)Robust Offline Reinforcement Learning with Heavy-Tailed Rewards., , , , and . AISTATS, volume 238 of Proceedings of Machine Learning Research, page 541-549. PMLR, (2024)Heterogeneous Synthetic Learner for Panel Data., , , and . CoRR, (2022)Mining the Factor Zoo: Estimation of Latent Factor Models with Sufficient Proxies., , , and . CoRR, (2022)Experimentation Platforms Meet Reinforcement Learning: Bayesian Sequential Decision-Making for Continuous Monitoring., , , , and . KDD, page 5016-5027. ACM, (2023)Does the Markov Decision Process Fit the Data: Testing for the Markov Property in Sequential Decision Making., , , , and . ICML, volume 119 of Proceedings of Machine Learning Research, page 8807-8817. PMLR, (2020)Robust Offline Policy Evaluation and Optimization with Heavy-Tailed Rewards., , , , and . CoRR, (2023)