Ninth Workshop on Data Management for End-to-End Machine Learning (DEEM)

The DEEM'25 workshop (Data Management for End-to-End Machine Learning) is held on Friday, June 27th, in conjunction with SIGMOD/PODS 2025. DEEM brings together researchers and practitioners at the intersection of applied machine learning, data management, and systems research, with the goal of discussing the arising data management issues in ML application scenarios. The workshop solicits regular research papers (8 pages) describing preliminary and ongoing research results, including industrial experience reports of end-to-end ML deployments, related to DEEM topics. In addition, DEEM 2025 has a category for short papers (4 pages) as a forum for sharing interesting use cases, problems, datasets, benchmarks, visionary ideas, system designs, preliminary results, and descriptions of system components and tools related to end-to-end ML pipelines. This year, the workshop received 18 high-quality submissions on diverse topics relevant to DEEM.

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Publication Details

Published
2025-06-17
DOI
https://doi.org/10.1145/3722212.3724483
Primary Topic
Machine Learning and Data Classification
Type
article
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article

Ninth Workshop on Data Management for End-to-End Machine Learning (DEEM)

Shreya Shankar, Madelon Hulsebos, Matteo Interlandi, Stefan Grafberger
Machine Learning and Data Classification
article

Ninth Workshop on Data Management for End-to-End Machine Learning (DEEM)

Shreya Shankar, Madelon Hulsebos, Matteo Interlandi, Stefan Grafberger
article en

Abstract

The DEEM'25 workshop (Data Management for End-to-End Machine Learning) is held on Friday, June 27th, in conjunction with SIGMOD/PODS 2025. DEEM brings together researchers and practitioners at the intersection of applied machine learning, data management, and systems research, with the goal of discussing the arising data management issues in ML application scenarios. The workshop solicits regular research papers (8 pages) describing preliminary and ongoing research results, including industrial experience reports of end-to-end ML deployments, related to DEEM topics. In addition, DEEM 2025 has a category for short papers (4 pages) as a forum for sharing interesting use cases, problems, datasets, benchmarks, visionary ideas, system designs, preliminary results, and descriptions of system components and tools related to end-to-end ML pipelines. This year, the workshop received 18 high-quality submissions on diverse topics relevant to DEEM.

Microsoft (United States) (US), Centrum Wiskunde & Informatica (NL), Berkeley College (US), Technische Universität Berlin (DE), University of California, Berkeley (US)
Openalex Percentile: Top 93%
Machine Learning and Data Classification
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