Zhenpeng Chen, Jie M. Zhang, Federica Sarro, Mark Harman. MAAT: a novel ensemble approach to addressing fairness and performance bugs for machine learning software. In Abhik Roychoudhury, Cristian Cadar, Miryung Kim, editors, Proceedings of the 30th ACM Joint European Software Engineering Conference and Symposium on the Foundations of Software Engineering, ESEC/FSE 2022, Singapore, Singapore, November 14-18, 2022. pages 1122-1134, ACM, 2022. [doi]
@inproceedings{ChenZSH22,
title = {MAAT: a novel ensemble approach to addressing fairness and performance bugs for machine learning software},
author = {Zhenpeng Chen and Jie M. Zhang and Federica Sarro and Mark Harman},
year = {2022},
doi = {10.1145/3540250.3549093},
url = {https://doi.org/10.1145/3540250.3549093},
researchr = {https://researchr.org/publication/ChenZSH22},
cites = {0},
citedby = {0},
pages = {1122-1134},
booktitle = {Proceedings of the 30th ACM Joint European Software Engineering Conference and Symposium on the Foundations of Software Engineering, ESEC/FSE 2022, Singapore, Singapore, November 14-18, 2022},
editor = {Abhik Roychoudhury and Cristian Cadar and Miryung Kim},
publisher = {ACM},
isbn = {978-1-4503-9413-0},
}