Research map / Learning theory and algorithms / Prediction and decision losses
If You Like Shapley Then You’ll Love the Core
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Measured effects reported in the paper
| What was changed | Where | Measured | Effect |
|---|---|---|---|
| Use the least core instead of Shapley-based valuation with a limited sample budget | Data valuation algorithms · Synthetic data removal | test performance | Helped |
| Use the least core instead of Shapley-based valuation with a limited sample budget | Data valuation algorithms · Dog-vs-fish data removal | test performance | Helped |
| Rank data using least-core values to remove the most valuable points | Data valuation algorithms · Synthetic data removal | test performance | Helped |
| Rank data using least-core values to remove the least valuable points | Data valuation algorithms · Synthetic data removal | test performance | Helped |
| Use least-core values to select mislabeled data for correction | Naive Bayes data valuation · Enron Dataset | test performance | Helped |
| Increase Gaussian noise in the noised portion of the dataset | Least-core data valuation · Synthetic noisy data | percentage of utility allocated to clean data | Helped |
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