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CAPS: Cost-Aware ML Pipeline Selection

Summary: CAPS adds cost-aware pipeline selection to AutoML, orthogonal to the underlying search strategy, via lightweight time/cost estimation. Models candidate pipelines as a directed hypergraph and solves a constrained prize-collecting subset problem with a greedy approximation, cutting waste up to 4x. (summarized by gpt-5.4-mini on May 27 2026)

Paper ID
14477
Venue
VLDB
Year
2026
Pagerank
5.093636e-05
Overall Rank
10,540 | 27.69%
DOI
10.14778/3801059.3801060

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Authors

BibTeX Citation

@article{kontaxakis_vldb26,
        title = {{CAPS: Cost-Aware ML Pipeline Selection}},
        author = {Kontaxakis, Antonios and Sacharidis, Dimitris and Abelló, Alberto and Nadal, Sergi and Simitsis, Alkis},
        journal = {PVLDB},
        series = {{VLDB} '26},
        volume = {19},
        number = {7},
        pages = {1427--1440},
        doi = {10.14778/3801059.3801060},
        url = {https://doi.org/10.14778/3801059.3801060},
        year = {2026}
}

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