Browse or search publications from faculty affiliated with the lab.
Estimating Average Treatment Effects: Supplementary Analyses and Remaining Challenges
There is a large literature on semiparametric estimation of average treatment effects under unconfounded treatment assignment in settings with a fixed number of covariates. More recently attention has focused on settings with a large number of…
Beyond Prediction: Using Big Data for Policy Problems
Machine-learning prediction methods have been extremely productive in applications ranging from medicine to allocating fire and health inspectors in cities. However, there are a number of gaps between making a prediction and making a decision,…
Context Selection for Embedding Models
Word embeddings are an effective tool to analyze language. They have been recently extended to model other types of data beyond text, such as items in recommendation systems. Embedding models consider the probability of a target observation (a…
Structured Embedding Models for Grouped Data
Word embeddings are a powerful approach for analyzing language, and exponential family embeddings (EFE) extend them to other types of data. Here we develop structured exponential family embeddings (SEFE), a method for discovering embeddings that…