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Guido Imbens

2 accepted papers

2023

Double and Single Descent in Causal Inference with an Application to High-Dimensional Synthetic Control

NeurIPS 2023poster

Motivated by a recent literature on the double-descent phenomenon in machine learning, we consider highly over-parameterized models in causal inference, including synthetic control with many control units. In such models, there may be so many free parameters that the model fits the training data per…

2021

Synthetic Design: An Optimization Approach to Experimental Design with Synthetic Controls

NeurIPS 2021poster

We investigate the optimal design of experimental studies that have pre-treatment outcome data available. The average treatment effect is estimated as the difference between the weighted average outcomes of the treated and control units. A number of commonly used approaches fit this formulation, in…

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