Cover Image

Ranking by Lifts: A Cost-Benefit Approach to Large-Scale A/B Tests

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Basu, Pallavi, Berman, Ron
Format:	Preprint
Published:	2024
Subjects:	Methodology Machine Learning Applications
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

A Large Scale Heterogeneous Treatment Effect Estimation Framework and Its Applications of Users' Journey at Snap
by: Pan, Jing, et al.
Published: (2025)

Fast Uncertainty Quantification for Kernel-Based Estimators in Large-Scale Causal Inference
by: Kosko, Matthew, et al.
Published: (2026)

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

A Unified Combination Framework for Dependent Tests with Applications to Microbiome Association Studies
by: Yu, Xiufan, et al.
Published: (2024)

A Nonparametric Bayes Approach to Online Activity Prediction
by: Beraha, Mario, et al.
Published: (2024)

Inference for Large Scale Regression Models with Dependent Errors
by: Voirol, Lionel, et al.
Published: (2024)

Testing Generalizability in Causal Inference
by: Manela, Daniel de Vassimon, et al.
Published: (2024)

Clustering Approaches for Mixed-Type Data: A Comparative Study
by: Ghattas, Badih, et al.
Published: (2025)

A Bayesian Classification Trees Approach to Treatment Effect Variation with Noncompliance
by: Fisher, Jared D., et al.
Published: (2024)

Testing and Improving the Robustness of Amortized Bayesian Inference for Cognitive Models
by: Wu, Yufei, et al.
Published: (2024)

Neural Network-Based Change Point Detection for Large-Scale Time-Evolving Data
by: Geng, Jialiang, et al.
Published: (2025)

A Transfer Learning Causal Approach to Evaluate Racial/Ethnic and Geographic Variation in Outcomes Following Congenital Heart Surgery
by: Han, Larry, et al.
Published: (2024)

Fit CATE Once: Model-Assisted Randomization Tests Without Sample Splitting
by: Zheng, Fangnan, et al.
Published: (2026)

Improved prediction of future user activity in online A/B testing
by: Masoero, Lorenzo, et al.
Published: (2024)

Nested Atoms Model with Application to Clustering Big Population-Scale Single-Cell Data
by: Chakrabarti, Arhit, et al.
Published: (2026)

Causal Mediation Analysis with Multiple Mediators: A Simulation Approach
by: Zhou, Jesse, et al.
Published: (2025)

Do Large Language Models (Really) Need Statistical Foundations?
by: Su, Weijie
Published: (2025)

Evaluation of Missing Data Analytical Techniques in Longitudinal Research: Traditional and Machine Learning Approaches
by: Tang, Dandan, et al.
Published: (2024)

Ranking Vectors Clustering: Theory and Applications
by: Fattahi, Ali, et al.
Published: (2025)

A Likelihood-Free Approach to Goal-Oriented Bayesian Optimal Experimental Design
by: Chakraborty, Atlanta, et al.
Published: (2024)

On Using Large Language Models to Enhance Clinically-Driven Missing Data Recovery Algorithms in Electronic Health Records
by: Lotspeich, Sarah C., et al.
Published: (2025)

A variational inference framework for inverse problems
by: Maestrini, Luca, et al.
Published: (2021)

Double Machine Learning at Scale to Predict Causal Impact of Customer Actions
by: More, Sushant, et al.
Published: (2024)

A Honest Cross-Validation Estimator for Prediction Performance
by: Pan, Tianyu, et al.
Published: (2025)

Changepoint Detection As Model Selection: A General Framework
by: Grantham, Michael, et al.
Published: (2026)

A Gaussian Process Model for Ordinal Data with Applications to Chemoinformatics
by: Gosnell, Arron, et al.
Published: (2024)

Assessment of Sports Concussion in Female Athletes: A Role for Neuroinformatics?
by: Edelstein, Rachel, et al.
Published: (2024)

A statistical approach to latent dynamic modeling with differential equations
by: Hackenberg, Maren, et al.
Published: (2023)

A Bayesian Non-parametric Approach to Generative Models: Integrating Variational Autoencoder and Generative Adversarial Networks using Wasserstein and Maximum Mean Discrepancy
by: Fazeli-Asl, Forough, et al.
Published: (2023)

meval: A Statistical Toolbox for Fine-Grained Model Performance Analysis
by: Sutariya, Dishantkumar, et al.
Published: (2025)

A Bayesian Framework for Causal Analysis of Recurrent Events with Timing Misalignment
by: Oganisian, Arman, et al.
Published: (2023)

A Bayesian Framework for Post-disruption Travel Time Prediction in Metro Networks
by: Nazemi, Shayan, et al.
Published: (2026)

A Generative Framework for Causal Estimation via Importance-Weighted Diffusion Distillation
by: Song, Xinran, et al.
Published: (2025)

A class of modular and flexible covariate-based covariance functions for nonstationary spatial modeling
by: Blasi, Federico, et al.
Published: (2024)

A Nonparametric Adaptive EWMA Control Chart for Binary Monitoring of Multiple Stream Processes
by: Muritala, Faruk, et al.
Published: (2026)

Double Machine Learning Methods for Estimating Average Treatment Effects: A Comparative Study
by: Tan, Xiaoqing, et al.
Published: (2022)

Depth-Based Local Center Clustering: A Framework for Handling Different Clustering Scenarios
by: Wang, Siyi, et al.
Published: (2025)

A Causal Machine Learning Framework for Treatment Personalization in Clinical Trials: Application to Ulcerative Colitis
by: Minoccheri, Cristian, et al.
Published: (2026)

Stein-Encoder: A White-Box Supervised Encoder via Stein Identities in Multi-Modal Studies
by: Zhang, Jiarui, et al.
Published: (2026)

PliableBVS: A flexible Bayesian variable selection method for modeling interactions with mandatory modifying variables
by: Asenso, Theophilus Quachie, et al.
Published: (2026)