UGCE reuses and repairs an evolved population of counterfactuals when user constraints change, cutting runtime versus recomputing from scratch, though success rates drop on some datasets.
The mythos of model interpretability: In machine learning, the concept of interpretability is both important and slippery
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UGCE: User-Guided Incremental Counterfactual Exploration
UGCE reuses and repairs an evolved population of counterfactuals when user constraints change, cutting runtime versus recomputing from scratch, though success rates drop on some datasets.