Understanding the Black Box: A Deep Empirical Dive into Shapley Value Approximations for Tabular Data
Summary: Shapley value approximations for tabular data: empirical eval. Evaluates 8 replacement and 17 estimation strategies across 200 datasets; model-based methods beat model-agnostic ones in accuracy and speed, while sampling-based approaches miss interactions. (summarized by gpt-5-nano on Feb 09 2026)
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Authors
- 1. Suchit Gupte (Ohio State University)
- 2. John Paparrizos (Ohio State University)
BibTeX Citation
@inproceedings{gupte_sigmod25,
title = {{Understanding the Black Box: A Deep Empirical Dive into Shapley Value Approximations for Tabular Data}},
author = {Gupte, Suchit and Paparrizos, John},
series = {{SIGMOD} '25},
booktitle = {Proceedings of the {ACM} {SIGMOD} International Conference on Management of Data},
publisher = {Association for Computing Machinery},
doi = {10.1145/3725420},
url = {https://dl.acm.org/doi/10.1145/3725420},
year = {2025}
}
Incoming Citations (Sorted by Pagerank)
Showing 5 of 5 citing papers.
| Rank | Citing Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 9,733 | SPARTAN: Data-Adaptive Symbolic Time-Series Approximation | 2025 | SIGMOD | 5.227679e-05 |
| 10,271 | MUFASA: Fast and Accurate Multivariate Time-Series Clustering | 2026 | SIGMOD | 5.093636e-05 |
| 10,298 | The Power of Anomaly Detection in Predictive Maintenance: [Experiments & Analysis] | 2026 | SIGMOD | 5.093636e-05 |
| 10,747 | A Structured Study of Multivariate Time-Series Distance Measures | 2025 | SIGMOD | 5.093636e-05 |
| 13,315 | ShapX Engine: A Demonstration of Shapley Value Approximations | 2025 | SIGMOD | - |
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Citations counted here include only citations to other VLDB/SIGMOD/CIDR/PODS papers in this database.
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