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MLog: Towards Declarative In-Database Machine Learning

Summary: Declarative in-database ML with MLog automates data movement, persistence, and training optimizations via tensoral views (TViews). Express models via cascaded TViews, and compile them to native TensorFlow programs with performance comparable to hand-optimized. (summarized by gpt-5-nano on Feb 09 2026)

Paper ID
11678
Venue
VLDB
Year
2017
Pagerank
7.3667971e-05
Overall Rank
3,490 | 76.06%
DOI
10.14778/3137765.3137808

Incoming Non-self Citations Over Time

Authors

BibTeX Citation

@article{li_vldb17,
        title = {{MLog: Towards Declarative In-Database Machine Learning}},
        author = {Li, Xupeng and Cui, Bin and Chen, Yiru and Wu, Wentao and Zhang, Ce},
        journal = {PVLDB},
        series = {{VLDB} '17},
        volume = {10},
        number = {12},
        pages = {1933--1936},
        doi = {10.14778/3137765.3137808},
        url = {https://doi.org/10.14778/3137765.3137808},
        year = {2017}
}

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