4 citations · 4 across the 1 of their papers we have counts for
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Verified Training for Counterfactual Explanation Robustness under Data Shift
Anna P. Meyer, Yuhao Zhang, Aws Albarghouthi +1
Counterfactual explanations (CEs) enhance the interpretability of machine learning models by describing what changes to an input are necessary to change its prediction to a desired…
On Minimizing the Impact of Dataset Shifts on Actionable Explanations
Anna P. Meyer, Dan Ley, Suraj Srinivas +1
The Right to Explanation is an important regulatory principle that allows individuals to request actionable explanations for algorithmic decisions. However, several technical chall…
The Dataset Multiplicity Problem: How Unreliable Data Impacts Predictions
Anna P. Meyer, Aws Albarghouthi, Loris D'Antoni
We introduce dataset multiplicity, a way to study how inaccuracies, uncertainty, and social bias in training datasets impact test-time predictions. The dataset multiplicity framewo…