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HELIX: Accelerating Human-in-the-loop Machine Learning

Summary: HELIX treats ML development as iterative workflow optimization rather than one-shot execution. Its declarative system combines cross-iteration program analysis with selective result materialization and DAG/version visualization, yielding up to 10× lower cumulative runtime. (summarized by gpt-5.6-luna on Jul 24 2026)

Paper ID
11872
Venue
VLDB
Year
2018
Pagerank
7.7091591e-05
Overall Rank
3,146 | 78.42%
DOI
10.14778/3229863.3236234

Incoming Non-self Citations Over Time

Authors

BibTeX Citation

@article{xin_vldb18,
        title = {{HELIX: Accelerating Human-in-the-loop Machine Learning}},
        author = {Xin, Doris and Ma, Litian and Liu, Jialin and Macke, Stephen and Song, Shuchen and Parameswaran, Aditya},
        journal = {PVLDB},
        series = {{VLDB} '18},
        volume = {11},
        number = {12},
        pages = {1958--1961},
        doi = {10.14778/3229863.3236234},
        url = {https://doi.org/10.14778/3229863.3236234},
        year = {2018}
}

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