DBScholar

Back to papers

Efficient Sampling Approaches to Shapley Value Approximation

Summary: Treats Shapley value estimation as stratified sampling to accelerate Monte Carlo approximation for data-management tasks. Proposes a novel stratification design with Neyman and empirical Bernstein-based allocations, showing improved efficiency and accuracy on real and synthetic datasets. (summarized by gpt-5-nano on Feb 09 2026)

Paper ID
hdf5c694bc716b8f5
Venue
SIGMOD
Year
2023
Pagerank
6.3502007e-05
Overall Rank
4,928 | 66.87%
DOI
10.1145/3588728

Incoming Non-self Citations Over Time

Authors

BibTeX Citation

@inproceedings{zhang_sigmod23,
        title = {{Efficient Sampling Approaches to Shapley Value Approximation}},
        author = {Zhang, Jiayao and Sun, Qiheng and Liu, Jinfei and Xiong, Li and Pei, Jian and Ren, Kui},
        series = {{SIGMOD} '23},
        booktitle = {Proceedings of the {ACM} {SIGMOD} International Conference on Management of Data},
        publisher = {Association for Computing Machinery},
        doi = {10.1145/3588728},
        url = {https://dl.acm.org/doi/10.1145/3588728},
        year = {2023}
}

Incoming Citations (Sorted by Pagerank)

Showing 14 of 14 citing papers.

Previous Page 1 / 1 Next

Outgoing Citations (Sorted by Pagerank)

Showing 7 of 7 cited papers.

Citations counted here include only citations to other VLDB/SIGMOD/CIDR/PODS papers in this database.

Previous Page 1 / 1 Next

Semantically Similar Papers