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Data Acquisition for Improving Machine Learning Models

Summary: Formalizes a data-market framework for acquiring training data to boost ML accuracy, with buyer–provider dynamics. Proposes EA and SPS, strategies balancing exploration and exploitation to improve model accuracy; validated on real datasets. (summarized by gpt-5-nano on Feb 09 2026)

Paper ID
12555
Venue
VLDB
Year
2021
Pagerank
7.8762343e-05
Overall Rank
2,994 | 79.46%
DOI
10.14778/3467861.3467872

Incoming Non-self Citations Over Time

Authors

BibTeX Citation

@article{li_vldb21,
        title = {{Data Acquisition for Improving Machine Learning Models}},
        author = {Li, Yifan and Yu, Xiaohui and Koudas, Nick},
        journal = {PVLDB},
        series = {{VLDB} '21},
        volume = {14},
        number = {10},
        pages = {1832--1844},
        doi = {10.14778/3467861.3467872},
        url = {https://doi.org/10.14778/3467861.3467872},
        year = {2021}
}

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