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Efficient and Effective Data Imputation with Influence Functions

Summary: EDIT uses influence functions to identify high-impact incomplete samples and selects a minimal representative training set with imputation-accuracy guarantees. A weighted loss emphasizes these samples, achieving ~4× faster training with ~5% of the data and improved accuracy. (summarized by gpt-5.6-luna on Jul 24 2026)

Paper ID
13124
Venue
VLDB
Year
2022
Pagerank
7.453827e-05
Overall Rank
3,386 | 76.78%
DOI
10.14778/3494124.3494143

Incoming Non-self Citations Over Time

Authors

BibTeX Citation

@article{miao_vldb22,
        title = {{Efficient and Effective Data Imputation with Influence Functions}},
        author = {Miao, Xiaoye and Wu, Yangyang and Chen, Lu and Gao, Yunjun and Wang, Jun and Yin, Jianwei},
        journal = {PVLDB},
        series = {{VLDB} '22},
        volume = {15},
        number = {3},
        pages = {624--632},
        doi = {10.14778/3494124.3494143},
        url = {https://doi.org/10.14778/3494124.3494143},
        year = {2022}
}

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