Research map / Learning theory and algorithms / Prediction and decision losses
A Distributional Framework For Data Valuation
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Measured effects reported in the paper
| What was changed | Where | Measured | Effect |
|---|---|---|---|
| Combine weighted sampling and interpolation | D-Shapley · CIFAR10 | speedup: 500× speed-up | Helped |
| Use weighted sampling or interpolation | D-Shapley · UK Biobank and Adult Income | point-removal performance | No clear effect |
| Remove high distributional Shapley-valued points first | Logistic regression · UK Biobank and Adult Income | classification accuracy | Hurt |
| Add points in distributional Shapley value order rather than random order | Buyer model in the data-pricing case study · Diabetes130 | classification accuracy | Helped |
Closest papers by meaning
- DU-Shapley: A Shapley Value Proxy for Efficient Dataset Valuation (NeurIPS 2024 · similarity 0.91)
- Rethinking Data Shapley for Data Selection Tasks: Misleads and Merits (ICML 2024 · similarity 0.89)
- Faithful Group Shapley Value (NeurIPS 2025 · similarity 0.88)
- shapiq: Shapley Interactions for Machine Learning (NeurIPS 2024 · similarity 0.88)
- Regression-adjusted Monte Carlo Estimators for Shapley Values and Probabilistic Values (NeurIPS 2025 · similarity 0.87)
- A Unified Framework for Provably Efficient Algorithms to Estimate Shapley Values (NeurIPS 2025 · similarity 0.87)
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