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How Much Should I Trust You? Modeling Uncertainty of Black Box Explanations
As local explanations of black box models are increasingly being employe...
08/11/2020 ∙ by Dylan Slack, et al. ∙
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From Predictions to Decisions: Using Lookahead Regularization
Machine learning is a powerful tool for predicting human-related outcome...
06/20/2020 ∙ by Nir Rosenfeld, et al. ∙
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How can we fool LIME and SHAP? Adversarial Attacks on Post hoc Explanation Methods
As machine learning black boxes are increasingly being deployed in domai...
11/06/2019 ∙ by Dylan Slack, et al. ∙
20
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Learning Key-Value Store Design
We introduce the concept of design continuums for the data layout of key...
07/11/2019 ∙ by Stratos Idreos, et al. ∙
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Learning Representations by Humans, for Humans
We propose a new, complementary approach to interpretability, in which m...
05/29/2019 ∙ by Sophie Hilgard, et al. ∙
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