Shapley Attributed Ablation with Augmented Learning (ShapAAL)

 One new method that improves Shapley values for deep learning explanation is **Shapley Attributed Ablation with Augmented Learning (ShapAAL)**. It is a novel push-pull deep architecture where the subset selection through Shapley value attribution pushes the model to lower dimension while augmented training augments the learning capability of the model over unseen data¹.

ShapAAL demonstrates that a deep learning algorithm with a suitably selected subset of the seen examples or ablating the unimportant ones from the given limited training dataset can ensure consistently better classification performance under augmented training¹.

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Source: Conversation with Bing, 7/2/2023

(1) When less is more powerful: Shapley value attributed ablation with .... https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0277975.

(2) Explaining a series of models by propagating Shapley values. https://www.nature.com/articles/s41467-022-31384-3.

(3) [2104.02297] Shapley Explanation Networks - arXiv.org. https://arxiv.org/abs/2104.02297.

(4) GitHub - slundberg/shap: A game theoretic approach to explain the .... https://github.com/slundberg/shap.