17 citations · 35 across the 14 of their papers we have counts for
14 papers
Can AI Agents Simulate A/B Test Outcomes? A Validation Framework for Agentic Experimentation
Stefan Hut, Lorenzo Masoero
A/B testing remains the standard for rolling out new features in the technology industry. Each experiment, however, consumes real traffic, engineering effort, and weeks of wall-clo…
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…
Robust and efficient multiple-unit switchback experimentation
Paul Missault, Lorenzo Masoero, Christian Delbé +2
User-randomized A/B testing has emerged as the gold standard for online experimentation. However, when this kind of approach is not feasible due to legal, ethical or practical cons…
Online activity prediction via generalized Indian buffet process models
Mario Beraha, Lorenzo Masoero, Stefano Favaro +1
Online A/B tests are the standard tool for data-driven decision-making at scale. Among the design choices with the largest impact on statistical power is the triggering mechanism:…
Improved prediction of future user activity in online A/B testing
Lorenzo Masoero, Mario Beraha, Thomas Richardson +1
In online randomized experiments or A/B tests, accurate predictions of participant inclusion rates are of paramount importance. These predictions not only guide experimenters in op…
A Nonparametric Bayes Approach to Online Activity Prediction
Mario Beraha, Lorenzo Masoero, Stefano Favaro +1
Accurately predicting the onset of specific activities within defined timeframes holds significant importance in several applied contexts. In particular, accurate prediction of the…
Multiple Randomization Designs: Estimation and Inference with Interference
Lorenzo Masoero, Suhas Vijaykumar, Thomas Richardson +5
Classical designs of randomized experiments, going back to Fisher and Neyman in the 1930s still dominate practice even in online experimentation. However, such designs are of limit…
Leveraging covariate adjustments at scale in online A/B testing
Lorenzo Masoero, Doug Hains, James McQueen
Companies offering web services routinely run randomized online experiments to estimate the causal impact associated with the adoption of new features and policies on key performan…
Cross-Study Replicability in Cluster Analysis
Lorenzo Masoero, Emma Thomas, Giovanni Parmigiani +2
In cancer research, clustering techniques are widely used for exploratory analyses and dimensionality reduction, playing a critical role in the identification of novel cancer subty…
Bayesian nonparametric strategies for power maximization in rare variants association studies
Lorenzo Masoero, Joshua Schraiber, Tamara Broderick
Rare variants are hypothesized to be largely responsible for heritability and susceptibility to disease in humans. So rare variants association studies hold promise for understandi…
Multiple Randomization Designs: Estimation and Inference with Interference
Lorenzo Masoero, Suhas Vijaykumar, Thomas Richardson +5
Completely randomized experiments, originally developed by Fisher and Neyman in the 1930s, are still widely used in practice, even in online experimentation. However, such designs…
Scaled process priors for Bayesian nonparametric estimation of the unseen genetic variation
Federico Camerlenghi, Stefano Favaro, Lorenzo Masoero +1
There is a growing interest in the estimation of the number of unseen features, mostly driven by biological applications. A recent work brought out a peculiar property of the popul…
Independent finite approximations for Bayesian nonparametric inference
Tin D. Nguyen, Jonathan Huggins, Lorenzo Masoero +2
Completely random measures (CRMs) and their normalizations (NCRMs) offer flexible models in Bayesian nonparametrics. But their infinite dimensionality presents challenges for infer…
More for less: Predicting and maximizing genetic variant discovery via Bayesian nonparametrics
Lorenzo Masoero, Federico Camerlenghi, Stefano Favaro +1
While the cost of sequencing genomes has decreased dramatically in recent years, this expense often remains non-trivial. Under a fixed budget, then, scientists face a natural trade…