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Evaluation/Inference for Machine Learning
Another key focus of my research centers around evaluating machine learning methods. This includes both developing new algorithms for consistent inference under observational data, and also creating evaluation metrics for rigorous evaluation of black-box prescription methods.
Statistical Inference for Heterogeneous Treatment Effects in Randomized Experiments (with Imai, K.). Submitted to Biometrika.
Experimental Evaluation of Individualized Treatment Rules (with Imai, K.). Journal of the American Statistical Association (2021): 1-41.
Pricing for Heterogeneous Products: Analytics for Ticket Reselling (with Alley, M., Biggs, M., Hariss, R., Herrmann, C., & Perakis, G.). Manufacturing & Service Operations Management (2022). Ahead of Print.
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