1 citations · 1 across the 5 of their papers we have counts for
5 papers
Evaluating for the long term: Learnings from industry
Leif Sigerson, Tom Cunningham, Winston Chou +22
Online platforms prioritize long-term business outcomes, yet typical experiments are far too short to measure these outcomes directly. Our goal in this paper is to collect and shar…
AI-Assisted Variance Reduction in Randomized Experiments
David Arbour, Eli Ben-Michael, Avi Feller +2
Generative AI and large language models can produce realistic predictions of human behavior from rich, unstructured inputs with little to no task-specific training data. Recent wor…
From Augmentation to Decomposition: A New Look at CUPED in 2023
Alex Deng, Luke Hagar, Nathaniel Stevens +3
Ten years ago, CUPED (Controlled Experiments Utilizing Pre-Experiment Data) mainstreamed the idea of variance reduction leveraging pre-experiment covariates. Since its introduction…
Zero to Hero: Exploiting Null Effects to Achieve Variance Reduction in Experiments with One-sided Triggering
Alex Deng, Lo-Hua Yuan, Naoya Kanai +1
In online experiments where the intervention is only exposed, or "triggered", for a small subset of the population, it is critical to use variance reduction techniques to estimate…
Identifying and Estimating Principal Causal Effects in Multi-site Trials
Lo-Hua Yuan, Avi Feller, Luke W. Miratrix
Randomized trials are often conducted with separate randomizations across multiple sites such as schools, voting districts, or hospitals. These sites can differ in important ways,…