Browse or search publications from faculty affiliated with the lab.
In severe viral pneumonia, including Coronavirus disease 2019 (COVID-19), the viral replication phase is often followed by hyperinflammation,…
We study the problem of model selection for contextual bandits, in which the algorithm must balance the bias-variance trade-off for model…
It has become increasingly common for data to be collected adaptively, for example using contextual bandits. Historical data of this type can be…
Learning optimal policies from historical data enables the gains from personalization to be realized in a wide variety of applications. The…
In this paper we study estimation of and inference for average treatment effects in a setting with panel data. We focus on the setting where units…
Adaptive experiment designs can dramatically improve statistical efficiency in randomized trials, but they also complicate statistical inference.…
Tractable contextual bandit algorithms often rely on the realizability assumption — i.e., that the true expected reward model belongs to a known…
Effective therapies for coronavirus disease 2019 (COVID-19) are urgently needed, and pre-clinical data suggest alpha-1 adrenergic receptor…
When researchers develop new econometric methods it is common practice to compare the performance of the new methods to those of existing methods…
This report describes insights gleaned from the Data Fellows collaboration among PayPal, Northwestern University’s Kellogg School of Management,…
Adaptive experiments present a unique opportunity to more rapidly learn which of many treatments work best, evaluate multiple hypotheses, and…
Although the value of vaccines may seem obvious, government action and investment in vaccines have not been commensurate with the enormous scale…
In medicine, randomized clinical trials are the gold standard for informing treatment decisions. Observational comparative effectiveness research…
Alpha 1–adrenergic receptor blocking agents (α1-blockers) have been reported to have protective benefits against hyperinflammation and cytokine…
Vaccinating the world’s population quickly in a pandemic has enormous health and economic benefits. We analyze the problem faced by governments in…
In many areas, practitioners seek to use observational data to learn a treatment assignment policy that satisfies application-specific…
Computationally efficient contextual bandits are often based on estimating a predictive model of rewards given contexts and arms using past data.…
Random forests are a powerful method for non-parametric regression, but are limited in their ability to fit smooth signals. Taking the perspective…
Tractable contextual bandit algorithms often rely on the realizability assumption — i.e., that the true expected reward model belongs to a known…
Alongside the outbreak of the novel coronavirus, an “infodemic” of myths and hoax cures is spreading over online media outlets and social media…