Wasserstein Distributionally Robust Optimization: Theory and Applications in Machine Learning. Kuhn, D., Esfahani, P. M., Nguyen, V. A., & Shafieezadeh-Abadeh, S. In Netessine, S., Shier, D., & Greenberg, H. J., editors, Operations Research & Management Science in the Age of Analytics, pages 130–166. INFORMS, October, 2019.
Paper doi bibtex @incollection{netessine_wasserstein_2019,
title = {Wasserstein {Distributionally} {Robust} {Optimization}: {Theory} and {Applications} in {Machine} {Learning}},
isbn = {978-0-9906153-3-0},
shorttitle = {Wasserstein {Distributionally} {Robust} {Optimization}},
url = {http://pubsonline.informs.org/doi/10.1287/educ.2019.0198},
language = {en},
urldate = {2022-02-10},
booktitle = {Operations {Research} \& {Management} {Science} in the {Age} of {Analytics}},
publisher = {INFORMS},
author = {Kuhn, Daniel and Esfahani, Peyman Mohajerin and Nguyen, Viet Anh and Shafieezadeh-Abadeh, Soroosh},
editor = {Netessine, Serguei and Shier, Douglas and Greenberg, Harvey J.},
month = oct,
year = {2019},
doi = {10.1287/educ.2019.0198},
keywords = {/unread},
pages = {130--166},
}
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