%0 Conference Paper %1 conf/sigsoft/ChenZSH22 %A Chen, Zhenpeng %A Zhang, Jie M. %A Sarro, Federica %A Harman, Mark %B ESEC/SIGSOFT FSE %D 2022 %E Roychoudhury, Abhik %E Cadar, Cristian %E Kim, Miryung %I ACM %K dblp %P 1122-1134 %T MAAT: a novel ensemble approach to addressing fairness and performance bugs for machine learning software. %U http://dblp.uni-trier.de/db/conf/sigsoft/fse2022.html#ChenZSH22 %@ 978-1-4503-9413-0

@inproceedings{conf/sigsoft/ChenZSH22, added-at = {2024-02-05T00:00:00.000+0100}, author = {Chen, Zhenpeng and Zhang, Jie M. and Sarro, Federica and Harman, Mark}, biburl = {https://www.bibsonomy.org/bibtex/28891c96fb03212794d8513db06143083/dblp}, booktitle = {ESEC/SIGSOFT FSE}, crossref = {conf/sigsoft/2022}, editor = {Roychoudhury, Abhik and Cadar, Cristian and Kim, Miryung}, ee = {https://doi.org/10.1145/3540250.3549093}, interhash = {f8be61115427c6fc83752474135bb2e1}, intrahash = {8891c96fb03212794d8513db06143083}, isbn = {978-1-4503-9413-0}, keywords = {dblp}, pages = {1122-1134}, publisher = {ACM}, timestamp = {2024-04-09T17:53:12.000+0200}, title = {MAAT: a novel ensemble approach to addressing fairness and performance bugs for machine learning software.}, url = {http://dblp.uni-trier.de/db/conf/sigsoft/fse2022.html#ChenZSH22}, year = 2022 }