Shapley Value Estimation Based on Differential Matrix
Summary: Introduces a differential-matrix framework for Shapley-value estimation: learn Shapley differences and recover values via LS. Also MC-estimates the differential matrix with two stratified MC variants for variance reduction, yielding efficient, accurate Shapley values. (summarized by gpt-5-nano on Feb 09 2026)
Incoming Non-self Citations Over Time
Authors
- 1. Junyuan Pang (Zhejiang University)
- 2. Jian Pei (Duke University)
- 3. Haocheng Xia (University of Illinois Urbana-Champaign)
- 4. Xiang Li (Zhejiang University)
- 5. Jinfei Liu (Zhejiang University)
BibTeX Citation
@inproceedings{pang_sigmod25,
title = {{Shapley Value Estimation Based on Differential Matrix}},
author = {Pang, Junyuan and Pei, Jian and Xia, Haocheng and Li, Xiang and Liu, Jinfei},
series = {{SIGMOD} '25},
booktitle = {Proceedings of the {ACM} {SIGMOD} International Conference on Management of Data},
publisher = {Association for Computing Machinery},
doi = {10.1145/3709725},
url = {https://dl.acm.org/doi/10.1145/3709725},
year = {2025}
}
Incoming Citations (Sorted by Pagerank)
Showing 1 of 1 citing papers.
| Rank | Citing Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 10,214 | CoShap: A Scalable Coalition Growth Approach to Shapley Value Approximation | 2026 | SIGMOD | 5.093636e-05 |
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Outgoing Citations (Sorted by Pagerank)
Showing 25 of 25 cited papers.
Citations counted here include only citations to other VLDB/SIGMOD/CIDR/PODS papers in this database.
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