Policy Learning with Asymmetric Counterfactual Utilities*-Reference-Cited by-同舟云学术

Policy Learning with Asymmetric Counterfactual Utilities*

Published:2024-01-08 Issue: Volume: Page:1-25
ISSN:0162-1459
Container-title:Journal of the American Statistical Association
language:en
Short-container-title:Journal of the American Statistical Association

Author:

Ben-Michael Eli¹^ORCID,Imai Kosuke²^ORCID,Jiang Zhichao³^ORCID

Affiliation:

1. Assistant Professor, Department of Statistics & Data Science and Heinz College of Information Systems & Public Policy, Carnegie Mellon University. 4800 Forbes Avenue, Hamburg Hall, Pittsburgh PA 15213

2. Professor, Department of Government and Department of Statistics, Harvard University. 1737 Cambridge Street, Institute for Quantitative Social Science, Cambridge MA 02138

3. Professor, School of mathematics, Sun Yat-sen University, Guangzhou Guangdong 510275

Publisher

Informa UK Limited

Subject

Statistics, Probability and Uncertainty,Statistics and Probability

Link

https://www.tandfonline.com/doi/pdf/10.1080/01621459.2023.2300507

Reference48 articles.

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3. Babii A. Chen X. Ghysels E. and Kumar R. (2021). Binary Choice with Asymmetric Loss in a Data-Rich Environment: Theory and an Application to Racial Justice.

4. Ben-Michael E. Greiner D. J. Imai K. and Jiang Z. (2021). Safe Policy Learning through Extrapolation: Application to Pre-trial Risk Assessment.

5. Bertsimas D. Brown D. B. and Caramanis C. (2011). Theory and applications of robust optimization. SIAM Review 53(3):464–501.