Adaptive Experimentation When You Can't Experiment
Fuente:
arXiv
Saved in:
| Main Authors: | Zhao, Yao, Jun, Kwang-Sung, Fiez, Tanner, Jain, Lalit |
|---|---|
| Format: | Preprint |
| Published: |
2024
|
| Subjects: | |
| Online Access: | |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
Best of Three Worlds: Adaptive Experimentation for Digital Marketing in Practice
by: Fiez, Tanner, et al.
Published: (2024)
by: Fiez, Tanner, et al.
Published: (2024)
Multi-Metric Adaptive Experimental Design under Fixed Budget with Validation
by: Zhang, Qining, et al.
Published: (2025)
by: Zhang, Qining, et al.
Published: (2025)
Efficient Adaptive Experimentation with Noncompliance
by: Oprescu, Miruna, et al.
Published: (2025)
by: Oprescu, Miruna, et al.
Published: (2025)
Simulation-Based Inference for Adaptive Experiments
by: Cho, Brian M, et al.
Published: (2025)
by: Cho, Brian M, et al.
Published: (2025)
Semiparametric Efficient Inference in Adaptive Experiments
by: Cook, Thomas, et al.
Published: (2023)
by: Cook, Thomas, et al.
Published: (2023)
Inference for Batched Adaptive Experiments
by: Kemper, Jan, et al.
Published: (2025)
by: Kemper, Jan, et al.
Published: (2025)
Privacy Preserving Adaptive Experiment Design
by: Li, Jiachun, et al.
Published: (2024)
by: Li, Jiachun, et al.
Published: (2024)
Deep Adaptive Model-Based Design of Experiments
by: Strouwen, Arno, et al.
Published: (2026)
by: Strouwen, Arno, et al.
Published: (2026)
Adaptive Experimental Design for Policy Learning
by: Kato, Masahiro, et al.
Published: (2024)
by: Kato, Masahiro, et al.
Published: (2024)
Demistifying Inference after Adaptive Experiments
by: Bibaut, Aurélien, et al.
Published: (2024)
by: Bibaut, Aurélien, et al.
Published: (2024)
Optimal Conditional Inference in Adaptive Experiments
by: Chen, Jiafeng, et al.
Published: (2023)
by: Chen, Jiafeng, et al.
Published: (2023)
Active Adaptive Experimental Design for Treatment Effect Estimation with Covariate Choices
by: Kato, Masahiro, et al.
Published: (2024)
by: Kato, Masahiro, et al.
Published: (2024)
Stronger Neyman Regret Guarantees for Adaptive Experimental Design
by: Noarov, Georgy, et al.
Published: (2025)
by: Noarov, Georgy, et al.
Published: (2025)
Efficient Inference after Directionally Stable Adaptive Experiments
by: Shen, Zikai, et al.
Published: (2026)
by: Shen, Zikai, et al.
Published: (2026)
Can Large Language Models Help Experimental Design for Causal Discovery?
by: Li, Junyi, et al.
Published: (2025)
by: Li, Junyi, et al.
Published: (2025)
Design Stability in Adaptive Experiments: Implications for Treatment Effect Estimation
by: Sengupta, Saikat, et al.
Published: (2025)
by: Sengupta, Saikat, et al.
Published: (2025)
Targeted Sequential Indirect Experiment Design
by: Ailer, Elisabeth, et al.
Published: (2024)
by: Ailer, Elisabeth, et al.
Published: (2024)
Integrating Active Learning in Causal Inference with Interference: A Novel Approach in Online Experiments
by: Zhu, Hongtao, et al.
Published: (2024)
by: Zhu, Hongtao, et al.
Published: (2024)
Combining Experimental and Historical Data for Policy Evaluation
by: Li, Ting, et al.
Published: (2024)
by: Li, Ting, et al.
Published: (2024)
Efficient Randomized Experiments Using Foundation Models
by: De Bartolomeis, Piersilvio, et al.
Published: (2025)
by: De Bartolomeis, Piersilvio, et al.
Published: (2025)
Probabilistic Factorial Experimental Design for Combinatorial Interventions
by: Shyamal, Divya, et al.
Published: (2025)
by: Shyamal, Divya, et al.
Published: (2025)
The Hardness of Validating Observational Studies with Experimental Data
by: Fawkes, Jake, et al.
Published: (2025)
by: Fawkes, Jake, et al.
Published: (2025)
Minimax and Bayes Optimal Adaptive Experimental Design for Treatment Choice
by: Kato, Masahiro
Published: (2025)
by: Kato, Masahiro
Published: (2025)
Nesting Particle Filters for Experimental Design in Dynamical Systems
by: Iqbal, Sahel, et al.
Published: (2024)
by: Iqbal, Sahel, et al.
Published: (2024)
Actively Learning Joint Contours of Multiple Computer Experiments
by: Prim, Shih-Ni, et al.
Published: (2025)
by: Prim, Shih-Ni, et al.
Published: (2025)
Choosing a Proxy Metric from Past Experiments
by: Tripuraneni, Nilesh, et al.
Published: (2023)
by: Tripuraneni, Nilesh, et al.
Published: (2023)
Policy-Aware Design of Large-Scale Factorial Experiments
by: Wen, Xin, et al.
Published: (2026)
by: Wen, Xin, et al.
Published: (2026)
Globally-Optimal Greedy Experiment Selection for Active Sequential Estimation
by: Li, Xiaoou, et al.
Published: (2024)
by: Li, Xiaoou, et al.
Published: (2024)
Recursive Nested Filtering for Efficient Amortized Bayesian Experimental Design
by: Iqbal, Sahel, et al.
Published: (2024)
by: Iqbal, Sahel, et al.
Published: (2024)
Benchmarking Observational Studies with Experimental Data under Right-Censoring
by: Demirel, Ilker, et al.
Published: (2024)
by: Demirel, Ilker, et al.
Published: (2024)
DARTS: Targeting Prognostic Covariates in Budget-Constrained Sequential Experiments
by: Husar, Kateryna, et al.
Published: (2026)
by: Husar, Kateryna, et al.
Published: (2026)
Green LIME: Improving AI Explainability through Design of Experiments
by: Stadler, Alexandra, et al.
Published: (2025)
by: Stadler, Alexandra, et al.
Published: (2025)
Estimating Total Effects in Bipartite Experiments with Spillovers and Partial Eligibility
by: Tan, Albert, et al.
Published: (2025)
by: Tan, Albert, et al.
Published: (2025)
Causal Message Passing for Experiments with Unknown and General Network Interference
by: Shirani, Sadegh, et al.
Published: (2023)
by: Shirani, Sadegh, et al.
Published: (2023)
An Experimental Design for Anytime-Valid Causal Inference on Multi-Armed Bandits
by: Liang, Biyonka, et al.
Published: (2023)
by: Liang, Biyonka, et al.
Published: (2023)
Environment-Adaptive Covariate Selection: Learning When to Use Spurious Correlations for Out-of-Distribution Prediction
by: Zuo, Shuozhi, et al.
Published: (2026)
by: Zuo, Shuozhi, et al.
Published: (2026)
Neyman Meets Causal Machine Learning: Experimental Evaluation of Individualized Treatment Rules
by: Li, Michael Lingzhi, et al.
Published: (2024)
by: Li, Michael Lingzhi, et al.
Published: (2024)
ML-assisted Randomization Tests for Detecting Treatment Effects in A/B Experiments
by: Guo, Wenxuan, et al.
Published: (2025)
by: Guo, Wenxuan, et al.
Published: (2025)
Designing Time Series Experiments in A/B Testing with Transformer Reinforcement Learning
by: Wu, Xiangkun, et al.
Published: (2026)
by: Wu, Xiangkun, et al.
Published: (2026)
Benchmarking Estimators for Natural Experiments: A Novel Dataset and a Doubly Robust Algorithm
by: Witter, R. Teal, et al.
Published: (2024)
by: Witter, R. Teal, et al.
Published: (2024)
Similar Items
-
Best of Three Worlds: Adaptive Experimentation for Digital Marketing in Practice
by: Fiez, Tanner, et al.
Published: (2024) -
Multi-Metric Adaptive Experimental Design under Fixed Budget with Validation
by: Zhang, Qining, et al.
Published: (2025) -
Efficient Adaptive Experimentation with Noncompliance
by: Oprescu, Miruna, et al.
Published: (2025) -
Simulation-Based Inference for Adaptive Experiments
by: Cho, Brian M, et al.
Published: (2025) -
Semiparametric Efficient Inference in Adaptive Experiments
by: Cook, Thomas, et al.
Published: (2023)