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Guha, S., Khan, F. A., Stoyanovich, J., & Schelter, S. (2023). Automated Data Cleaning Can Hurt Fairness in Machine Learning-based Decision Making. In 2023 IEEE 39th International Conference on Data Engineering: ICDE 2023 : proceedings : 3-7 April 2023, Anaheim, California (pp. 3747-3754). IEEE Computer Society. https://doi.org/10.1109/ICDE55515.2023.00303[details]
Schelter, S., Grafberger, S., Guha, S., Karlaš, B., & Zhang, C. (2023). Proactively Screening Machine Learning Pipelines with ArgusEyes. In SIGMOD '23 Companion: Companion of the 2023 ACM/SIGMOD International Conference on Management of Data : June 18-23, 2023, Seattle, WA, USA (pp. 91–94). Association for Computing Machinery. https://doi.org/10.1145/3555041.3589682[details]
Grafberger, S., Guha, S., Stoyanovich, J., & Schelter, S. (2021). MLINSPECT: A Data Distribution Debugger for Machine Learning Pipelines. In SIGMOD '21: proceedings of the 2021 International Conference on the Management of Data : June 20 -25, 2021, virtual event, China (pp. 2736–2739). Association for Computing Machinery. https://doi.org/10.1145/3448016.3452759[details]
Grafberger, S., Guha, S., Groth, P., & Schelter, S. (2023). Mlwhatif: What If You Could Stop Re-Implementing Your Machine Learning Pipeline Analyses over and Over? Proceedings of the VLDB Endowment, 16(12), 4002–4005. https://doi.org/10.14778/3611540.3611606[details]
Schelter, S., Grafberger, S., Guha, S., Sprangers, O., Karlaš, B., & Zhang, C. (2022). Screening Native Machine Learning Pipelines with ArgusEyes. Abstract from Conference on Innovative Data Systems Research 2022, Chaminade, California, United States. https://ssc.io/publication/screening-native-ml-pipelines-with-arguseyes-cidr/
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