1.6k citations · 2.1k across the 53 of their papers we have counts for
6 papers · 1 filter
PICPIs: Prediction-Interval-Conditional Prediction Intervals
Xuelin Yang, Baihe Huang, Yilong Hou +2
A classical question in statistics is which observable quantities to condition on when drawing inferences about unobservable targets. For conformal prediction in nonparametric unce…
Estimating Causal Effects from Data Generated by Stochastic Algorithms
Susan Athey, Guido Imbens, Zoe Ji
Recommendation systems and chatbots present content to users, typically using stochastic algorithms that select the content based on user characteristics or context. Examples of co…
Regression Adjustments for Double Randomization in Two-Sided Marketplaces
Timothy Sudijono, Lihua Lei, Lorenzo Masoero +3
Multiple randomization designs (MRDs) are a class of experimental designs used to handle interference in two-sided marketplaces. We investigate regression adjustment strategies for…
Demonstration Experiments
Guido Imbens, Lorenzo Masoero, Alexander Rakhlin +2
Adaptive experiments are used extensively in online platforms, healthcare and biotechnology, and the social sciences. Often, the primary goal is not to precisely estimate a treatme…
Scalable Decisions using a Bayesian Decision-Theoretic Approach
Hoiyi Ng, Guido Imbens
Randomized controlled experiments assess new policy impacts on performance metrics to inform launch decisions. Traditional approaches evaluate metrics independently despite correla…
Long-Term Causal Inference with Many Noisy Proxies
Apoorva Lal, Guido Imbens, Peter Hull
We propose a method for estimating long-term treatment effects with many short-term proxy outcomes: a central challenge when experimenting on digital platforms. We formalize this c…