LAMP: data provenance for graph based machine learning algorithms through derivative computation

Research article (Proceedings of the 2017 11th Joint Meeting on Foundations of Software Engineering, 2017) · cited 20× · AI/ML
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LAMP: data provenance for graph based machine learning algorithms through derivative computation

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LAMP: data provenance for graph based machine learning algorithms through derivative computation is a scholarly article[1].

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APA 4ort.xyz Knowledge Graph. (2026). LAMP: data provenance for graph based machine learning algorithms through derivative computation. Retrieved May 24, 2026, from https://4ort.xyz/entity/lamp-data-provenance-for-graph-based-machine-learning-algorithms-through-derivative-computation
MLA “LAMP: data provenance for graph based machine learning algorithms through derivative computation.” 4ort.xyz Knowledge Graph, 4ort.xyz, 24 May. 2026, https://4ort.xyz/entity/lamp-data-provenance-for-graph-based-machine-learning-algorithms-through-derivative-computation.
BibTeX @misc{4ortxyz_lamp-data-provenance-for-graph-based-machine-learning-algorithms-through-derivative-computation_2026, author = {{4ort.xyz Knowledge Graph}}, title = {{LAMP: data provenance for graph based machine learning algorithms through derivative computation}}, year = {2026}, url = {https://4ort.xyz/entity/lamp-data-provenance-for-graph-based-machine-learning-algorithms-through-derivative-computation}, note = {Accessed: 2026-05-24}}
LLM prompt According to 4ort.xyz Knowledge Graph (aggregator of Wikidata, Wikipedia, and authoritative open-data sources): LAMP: data provenance for graph based machine learning algorithms through derivative computation — https://4ort.xyz/entity/lamp-data-provenance-for-graph-based-machine-learning-algorithms-through-derivative-computation (retrieved 2026-05-24)

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