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7th DEEM@SIGMOD 2024: Santiago, Chile

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Proceedings of the Eighth Workshop on Data Management for End-to-End Machine Learning, DEEM 2024, Santiago, AA, Chile, 9 June 2024. ACM 2024
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Mubashara Akhtar, Omar Benjelloun, Costanza Conforti, Pieter Gijsbers, Joan Giner-Miguelez, Nitisha Jain, Michael Kuchnik, Quentin Lhoest, Pierre Marcenac, Manil Maskey, Peter Mattson, Luis Oala, Pierre Ruyssen, Rajat Shinde, Elena Simperl, Goeffry Thomas, Slava Tykhonov, Joaquin Vanschoren, Jos van der Velde, Steffen Vogler, Carole-Jean Wu:
Croissant: A Metadata Format for ML-Ready Datasets. 1-6
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Stefan Grafberger, Paul Groth, Sebastian Schelter:
Towards Interactively Improving ML Data Preparation Code via "Shadow Pipelines". 7-11
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Timothy Dai, Austin Peters, Jonah B. Gelbach, David Freeman Engstrom, Daniel Kang:
tailwiz: Empowering Domain Experts with Easy-to-Use, Task-Specific Natural Language Processing Models. 12-22
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Tengjun Jin, Akash Mittal, Chenghao Mo, Jiahao Fang, Chengsong Zhang, Timothy Dai, Daniel Kang:
AIDB: a Sparsely Materialized Database for Queries using Machine Learning. 23-28
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Robert Bayer, Julian Priest, Pinar Tözün:
Reaching the Edge of the Edge: Image Analysis in Space. 29-38
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Herbert Woisetschläger, Alexander Erben, Shiqiang Wang, Ruben Mayer, Hans-Arno Jacobsen:
Federated Fine-Tuning of LLMs on the Very Edge: The Good, the Bad, the Ugly. 39-50
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Abhilash Jindal, Kaustubh Beedkar, Vishal Singh, J. Nausheen Mohammed, Tushar Singla, Aman Gupta, Keerti Choudhary:
Reactive Dataflow for Inflight Error Handling in ML Workflows. 51-61
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Xue Li, Till Döhmen:
Towards Efficient Data Wrangling with LLMs using Code Generation. 62-66
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Jacopo Tagliabue, Ciro Greco:
Reproducible data science over data lakes: replayable data pipelines with Bauplan and Nessie. 67-71
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Konstantinos Kanellis, Johannes Freischuetz, Shivaram Venkataraman:
Nautilus: A Benchmarking Platform for DBMS Knob Tuning. 72-76
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Débora B. Pina, Adriane Chapman, Liliane N. O. Kunstmann, Daniel de Oliveira, Marta Mattoso:
DLProv: A Data-Centric Support for Deep Learning Workflow Analyses. 77-85

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