Stein's method compares probability distributions through the study of a class of linear
operators called Stein operators. While mainly studied in probability and used to underpin …

This survey describes probabilistic algorithms for linear algebraic computations, such as
factorizing matrices and solving linear systems. It focuses on techniques that have a proven …

Testing for outliers with conformal p-values Page 1 The Annals of Statistics 2023, Vol. 51, No.
1, 149–178 https://doi.org/10.1214/22-AOS2244 © Institute of Mathematical Statistics, 2023 …

These notes were written for the course APC 550: Probability in High Dimension that I taught
at Princeton in the Spring 2014 and Fall 2016 semesters. The aim was to introduce in as …

It has long been recognized that many inventory models most relevant to practice are
inherently high‐dimensional, and hence generally believed to become computationally …

Concentration inequalities have been the subject of exciting developments during the last
two decades, and have been intensively studied and used as a powerful tool in various …

We describe semiparametric estimation and inference for causal effects using observational
data from a single social network. Our asymptotic results are the first to allow for …

A growing empirical literature examines the role that networks play in a variety of economic
phenomena. This research can be crudely partitioned into two branches. The first holds …

Random graph asymptotics for treatment effect estimation under network interference Page 1
The Annals of Statistics 2022, Vol. 50, No. 4, 2334–2358 https://doi.org/10.1214/22-AOS2191 © …

We study nonparametric and regression estimators of treatment and spillover effects when
interference is mediated by a network. Inference is nonstandard due to dependence induced …