%0 Conference Paper %1 vasileva2020dark %A Vasileva, Mariya I %B Proceedings of the 26th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining %D 2020 %K fairness subgroups subgroup algorithm machine learning bias citedby:scholar:count:2 citedby:scholar:timestamp:2021-8-8 %P 3586--3587 %T The Dark Side of Machine Learning Algorithms: How and Why They Can Leverage Bias, and What Can Be Done to Pursue Algorithmic Fairness

@inproceedings{vasileva2020dark, added-at = {2021-08-08T22:48:25.000+0200}, author = {Vasileva, Mariya I}, biburl = {https://www.bibsonomy.org/bibtex/21d5fd3043e284079f130dabaa13d0c1e/becker}, booktitle = {Proceedings of the 26th ACM SIGKDD International Conference on Knowledge Discovery \& Data Mining}, interhash = {45e87242a4c781ed851644120ac271ac}, intrahash = {1d5fd3043e284079f130dabaa13d0c1e}, keywords = {fairness subgroups subgroup algorithm machine learning bias citedby:scholar:count:2 citedby:scholar:timestamp:2021-8-8}, pages = {3586--3587}, timestamp = {2021-08-08T22:48:25.000+0200}, title = {The Dark Side of Machine Learning Algorithms: How and Why They Can Leverage Bias, and What Can Be Done to Pursue Algorithmic Fairness}, year = 2020 }