%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 }