Cover Image

ML-assisted Randomization Tests for Detecting Treatment Effects in A/B Experiments

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Guo, Wenxuan, Lee, JungHo, Toulis, Panos
Format:	Preprint
Published:	2025
Subjects:	Methodology Machine Learning
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Asymptotic Validity and Finite-Sample Properties of Approximate Randomization Tests
by: Toulis, Panos
Published: (2019)

Learning Treatment Effects during Resource Allocation via Priority-Queue Randomization
by: Lee, JungHo, et al.
Published: (2026)

Gaussianized Design Optimization for Covariate Balance in Randomized Experiments
by: Guo, Wenxuan, et al.
Published: (2025)

Finite-Sample Valid Randomization Tests for Monotone Spillover Effects
by: Huang, Shunzhuang, et al.
Published: (2025)

The Proximal Robbins-Monro Method
by: Toulis, Panos, et al.
Published: (2015)

Randomization Inference in Two-Sided Market Experiments
by: Liu, Jizhou, et al.
Published: (2025)

Permutation Inference under Multi-way Clustering and Missing Data
by: Guo, Wenxuan, et al.
Published: (2026)

Nonparametric Estimation of Local Treatment Effects with Continuous Instruments
by: Zeng, Zhenghao, et al.
Published: (2025)

On Nonasymptotic Confidence Intervals for Treatment Effects in Randomized Experiments
by: Sandoval, Ricardo J., et al.
Published: (2026)

Statistical Inference for Heterogeneous Treatment Effects Discovered by Generic Machine Learning in Randomized Experiments
by: Imai, Kosuke, et al.
Published: (2022)

Interpretable Network-assisted Random Forest+
by: Tang, Tiffany M., et al.
Published: (2025)

Combining Incomplete Observational and Randomized Data for Heterogeneous Treatment Effects
by: Yao, Dong, et al.
Published: (2024)

Modeling Covariate Transition for Efficient Estimation of Longitudinal Treatment Effects in Randomized Experiments
by: Chihara, Naoki, et al.
Published: (2026)

Improving the Estimation of Lifetime Effects in A/B Testing via Treatment Locality
by: Chen, Shuze, et al.
Published: (2024)

Designing Time Series Experiments in A/B Testing with Transformer Reinforcement Learning
by: Wu, Xiangkun, et al.
Published: (2026)

Dynamic Treatment on Networks
by: Nar, Bengusu, et al.
Published: (2026)

Active Adaptive Experimental Design for Treatment Effect Estimation with Covariate Choices
by: Kato, Masahiro, et al.
Published: (2024)

Adaptive-TMLE for the Average Treatment Effect based on Randomized Controlled Trial Augmented with Real-World Data
by: van der Laan, Mark, et al.
Published: (2024)

Extrapolating Single-Treatment Effects Out of Factorial Experiments
by: Duarte, Guilherme
Published: (2024)

Efficient Randomized Experiments Using Foundation Models
by: De Bartolomeis, Piersilvio, et al.
Published: (2025)

Detecting and Mitigating Group Bias in Heterogeneous Treatment Effects
by: Persson, Joel, et al.
Published: (2026)

SubgroupTE: Advancing Treatment Effect Estimation with Subgroup Identification
by: Lee, Seungyeon, et al.
Published: (2024)

Design Stability in Adaptive Experiments: Implications for Treatment Effect Estimation
by: Sengupta, Saikat, et al.
Published: (2025)

Causal Rule Ensemble: Interpretable Discovery and Inference of Heterogeneous Treatment Effects
by: Bargagli-Stoffi, Falco J., et al.
Published: (2020)

Random-Effects Algorithm for Random Objects in Metric Spaces
by: Matabuena, Marcos, et al.
Published: (2026)

Conditional Distributional Treatment Effects: Doubly Robust Estimation and Testing
by: Jain, Saksham, et al.
Published: (2026)

ABC3: Active Bayesian Causal Inference with Cohn Criteria in Randomized Experiments
by: Cha, Taehun, et al.
Published: (2024)

Treatment Effects in Extreme Regimes
by: Aloui, Ahmed, et al.
Published: (2023)

Ordinal Mixed-Effects Random Forest
by: Bergonzoli, Giulia, et al.
Published: (2024)

Continuous Treatment Effects with Surrogate Outcomes
by: Zeng, Zhenghao, et al.
Published: (2024)

$t$-Testing the Waters: Empirically Validating Assumptions for Reliable A/B-Testing
by: Jeunen, Olivier
Published: (2025)

Wahkon: A Statistically Principled Deep RKHS Superposition Network
by: Chen, Yongkai, et al.
Published: (2026)

Neyman Meets Causal Machine Learning: Experimental Evaluation of Individualized Treatment Rules
by: Li, Michael Lingzhi, et al.
Published: (2024)

A Randomized Permutation Whole-Model Test Heuristic for Self-Validated Ensemble Models (SVEM)
by: Karl, Andrew T.
Published: (2024)

A Multivariate Unimodality Test Harnessing the Dip Statistic of Mahalanobis Distances Over Random Projections
by: Kolyvakis, Prodromos, et al.
Published: (2023)

Sequential Treatment Effect Estimation with Unmeasured Confounders
by: Wang, Yingrong, et al.
Published: (2025)

Kernel Treatment Effects with Adaptively Collected Data
by: Zenati, Houssam, et al.
Published: (2025)

Educational Effects in Mathematics: Conditional Average Treatment Effect depending on the Number of Treatments
by: Nagai, Tomoko, et al.
Published: (2024)

A Semi-Supervised Kernel Two-Sample Test
by: Lee, Gyumin, et al.
Published: (2026)

Fast Rerandomization for Balancing Covariates in Randomized Experiments: A Metropolis-Hastings Framework
by: Lu, Jiuyao, et al.
Published: (2026)