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Video Highlights: Machine Learning and Causal Inference

For our current edition of “Video Highlights” I’d like to offer this talk that will review a series of recent papers that develop new methods based on machine learning methods to approach problems of causal inference, including estimation of conditional average treatment effects and personalized treatment assignment policies. Approaches for randomized experiments, environments with unconfoundedness, instrumental variables, and panel data will be considered.