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Learning to Validate the Predictions of Black Box Machine Learning Models on Unseen Data.

, , , , and . HILDA@SIGMOD, page 4:1-4:4. ACM, (2019)

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Learning to Validate the Predictions of Black Box Machine Learning Models on Unseen Data., , , , and . HILDA@SIGMOD, page 4:1-4:4. ACM, (2019)Automating Data Quality Validation for Dynamic Data Ingestion., , , and . EDBT, page 61-72. OpenProceedings.org, (2021)ExDRa: Exploratory Data Science on Federated Raw Data., , , , , , , , , and 7 other author(s). SIGMOD Conference, page 2450-2463. ACM, (2021)P2D: A Transpiler Framework for Optimizing Data Science Pipelines., , , , and . DEEM@SIGMOD, page 3:1-3:4. ACM, (2023)Tactile Interaction and Social Touch: Classifying Human Touch Using a Soft Tactile Sensor., , , , and . HAI, page 523-526. ACM, (2017)Explanation of Air Pollution Using External Data Sources., , , , , and . BTW (Workshops), volume P-290 of LNI, page 297-300. Gesellschaft für Informatik, Bonn, (2019)Towards Unsupervised Data Quality Validation on Dynamic Data., , and . EDBT/ICDT Workshops, volume 2578 of CEUR Workshop Proceedings, CEUR-WS.org, (2020)DORIAN in action: Assisted Design of Data Science Pipelines., , , and . Proc. VLDB Endow., 15 (12): 3714-3717 (2022)Automated Documentation of End-to-End Experiments in Data Science.. ICDE, page 2076-2080. IEEE, (2019)Assisted design of data science pipelines., , , and . VLDB J., 33 (4): 1129-1153 (July 2024)