Publications

Stefan Grafberger, Zeyu Zhang, Sebastian Schelter, Ce Zhang (2024). Red Onions, Soft Cheese and Data: From Food Safety to Data Traceability for Responsible AI. IEEE Data Engineering Bulletin.

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Stefan Grafberger, Bojan Karlas, Paul Groth, Sebastian Schelter (2023). Towards Declarative Systems for Data-Centric Machine Learning. Data-Centric Machine Learning Research workshop (DMLR) at ICML (abstract).

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Stefan Grafberger, Shubha Guha, Paul Groth, Sebastian Schelter (2023). mlwhatif: What If You Could Stop Re-Implementing Your Machine Learning Pipeline Analyses Over and Over?. VLDB (demo).

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Stefan Grafberger, Paul Groth, Sebastian Schelter (2023). Provenance Tracking for End-to-End Machine Learning Pipelines. ProvenanceWeek at ACM Web Conference (poster).

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Stefan Grafberger, Paul Groth, Sebastian Schelter (2023). Automating and Optimizing Data-Centric What-If Analyses on Native Machine Learning Pipelines. ACM SIGMOD.

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Sebastian Schelter, Stefan Grafberger, Shubha Guha, Bojan Karlas, Ce Zhang (2023). Proactively Screening Machine Learning Pipelines with ArgusEyes. ACM SIGMOD (demo).

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Stefan Grafberger, Paul Groth, Sebastian Schelter (2022). Towards Data-Centric What-If Analysis for Native Machine Learning Pipelines. Data Management for End-to-End Machine Learning workshop at ACM SIGMOD.

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Stefan Grafberger, Paul Groth, Julia Stoyanovich, Sebastian Schelter (2021). Data Distribution Debugging in Machine Learning Pipelines. The VLDB Journal — The International Journal on Very Large Data Bases (Special Issue on Data Science for Responsible Data Management).

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Sebastian Schelter, Stefan Grafberger, Shubha Guha, Olivier Sprangers, Bojan Karlas, Ce Zhang (2021). Screening Native Machine Learning Pipelines with ArgusEyes. Conference on Innovative Data Systems Research (CIDR, abstract).

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Sebastian Schelter, Stefan Grafberger, Ted Dunning (2021). HedgeCut: Maintaining Randomized Trees for Low-Latency Machine Unlearning. ACM SIGMOD.

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Stefan Grafberger, Shubha Guha, Julia Stoyanovich, Sebastian Schelter (2021). mlinspect: a Data Distribution Debugger for Machine Learning Pipelines. ACM SIGMOD (demo).

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Stefan Grafberger, Julia Stoyanovich, Sebastian Schelter (2020). Lightweight Inspection of Data Preprocessing in Native Machine Learning Pipelines. Conference on Innovative Data Systems Research (CIDR).

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Sebastian Schelter, Stefan Grafberger, Philipp Schmidt, Tammo Rukat, Mario Kiessling, Andrey Taptunov, Felix Biessmann, Dustin Lange (2019). Differential Data Quality Verification on Partitioned Data. International Conference on Data Engineering (ICDE).

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Sebastian Schelter, Stefan Grafberger, Philipp Schmidt, Tammo Rukat, Mario Kiessling, Andrey Taptunov, Felix Biessmann, Dustin Lange (2018). Deequ - Data Quality Validation for Machine Learning Pipelines. Machine Learning Systems workshop at the conference on Neural Information Processing Systems (NeurIPS).

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