aai-institute / aai-institute/pyDVL
Implement AME
Ouverte
new-method
- Langage dominant
- Python
- Étoiles
- 146
- Forks
- 10
- Métriques de merge des PR
- Aucune PR mergée en 30 j
Description
Introduced in _Lin, Jinkun, Anqi Zhang, Mathias Lécuyer, Jinyang Li, Aurojit Panda, and Siddhartha Sen. “[Measuring the Effect of Training Data on Deep Learning Predictions via Randomized Experiments](https://proceedings.mlr.press/v162/lin22h.html).” In Proceedings of the 39th International Conference on Machine Learning, 13468–504. PMLR, 2022._
For the "exact" AME, a very similar sampling scheme to Owen sampling makes for a trivial implementation.
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