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LIMA: Fine-grained Lineage Tracing and Reuse in Machine Learning Systems.

, , and . SIGMOD Conference, page 1426-1439. ACM, (2021)

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Enabling Integrated Data Analysis Pipelines on Heterogeneous Hardware through Holistic Extensibility., and . BTW, volume P-331 of LNI, page 815-818. Gesellschaft für Informatik e.V., (2023)Costing Generated Runtime Execution Plans for Large-Scale Machine Learning Programs.. CoRR, (2015)ExDRa: Exploratory Data Science on Federated Raw Data., , , , , , , , , and 7 other author(s). SIGMOD Conference, page 2450-2463. ACM, (2021)LIMA: Fine-grained Lineage Tracing and Reuse in Machine Learning Systems., , and . SIGMOD Conference, page 1426-1439. ACM, (2021)Usability von Online-Shops - Eine empirische Analyse, , and . page 213-229. Springer-Verlag, Berlin, Heidelberg, (2010)DAPHNE Runtime: Harnessing Parallelism for Integrated Data Analysis Pipelines., , , , , , , , , and 2 other author(s). Euro-Par Workshops, volume 14352 of Lecture Notes in Computer Science, page 242-246. Springer, (2023)Usability of "Trusted Shops" - An Empirical Analysis of eCommerce Shops, , and . (2008)Federated Data Preparation, Learning, and Debugging in Apache SystemDS., , , , , , , , , and . CIKM, page 4813-4817. ACM, (2022)Optimizing Tensor Computations: From Applications to Compilation and Runtime Techniques., , and . SIGMOD Conference Companion, page 53-59. ACM, (2023)Special issue on "Machine learning and databases"., and . VLDB J., 33 (4): 901 (July 2024)