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Ease.ML: A Lifecycle Management System for MLDev and MLOps

Summary: Ease.ML automates the entire MLDev/MLOps lifecycle (an eight-step process) rather than improving isolated stages, driven by practical user scenarios. Unique foundation: a probabilistic-database model with information-theoretic grounding to manage cross-stage uncertainty for end-to-end automation. (summarized by gpt-5-mini on Feb 09 2026)

Paper ID
424
Venue
CIDR
Year
2021
Pagerank
5.093636e-05
Overall Rank
11,629 | 20.22%
DOI
-

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BibTeX Citation

@inproceedings{aguilar_cidr21,
        address = {Amsterdam, Netherlands},
        series = {{CIDR} '21},
        title = {{Ease.ML: A Lifecycle Management System for MLDev and MLOps}},
        booktitle = {Proceedings of the {Conference} on {Innovative} {Data} {Systems} {Research}},
        author = {Aguilar, Leonel and Dao, David and Gan, Shaoduo and Gurel, Nezihe Merve and Hollenstein, Nora and Jiang, Jiawei and Karlas, Bojan and Lemmin, Thomas and Li, Tian and Li, Yang and Rao, Susie and Rausch, Johannes and Renggli, Cedric and Rimanic, Luka and Weber, Maurice and Zhang, Shuai and Zhao, Zhikuan and Schawinski, Kevin and Wu, Wentao and Zhang, Ce},
        year = {2021}
}

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