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%0 Conference Paper
%1 schwinn2022improving
%A Schwinn, Leo
%A Bungert, Leon
%A Nguyen, An
%A Raab, René
%A Pulsmeyer, Falk
%A Precup, Doina
%A Eskofier, Bjoern
%A Zanca, Dario
%B Proceedings of the 39th International Conference on Machine Learning
%D 2022
%E Chaudhuri, Kamalika
%E Jegelka, Stefanie
%E Song, Le
%E Szepesvari, Csaba
%E Niu, Gang
%E Sabato, Sivan
%I PMLR
%K chapter imported
%P 19434--19449
%T Improving Robustness against Real-World and Worst-Case Distribution Shifts through Decision Region Quantification
%V 162
@inproceedings{schwinn2022improving,
added-at = {2023-07-27T10:31:18.000+0200},
author = {Schwinn, Leo and Bungert, Leon and Nguyen, An and Raab, Ren{\'e} and Pulsmeyer, Falk and Precup, Doina and Eskofier, Bjoern and Zanca, Dario},
biburl = {https://www.bibsonomy.org/bibtex/23ff0ed84c5b8c4cf328db1a50e0711ec/l_bungert},
booktitle = {Proceedings of the 39th International Conference on Machine Learning},
editor = {Chaudhuri, Kamalika and Jegelka, Stefanie and Song, Le and Szepesvari, Csaba and Niu, Gang and Sabato, Sivan},
interhash = {d4c34100ffb0da7c3fc3accc5c3c08ac},
intrahash = {3ff0ed84c5b8c4cf328db1a50e0711ec},
keywords = {chapter imported},
month = {17--23 Jul},
pages = {19434--19449},
publisher = {PMLR},
series = {Proceedings of Machine Learning Research},
timestamp = {2023-08-29T13:28:51.000+0200},
title = {Improving Robustness against Real-World and Worst-Case Distribution Shifts through Decision Region Quantification},
volume = 162,
year = 2022
}