4 papers
Gaussian Rank Verification
Jeremy Goldwasser, Will Fithian, Giles Hooker
Statistical experiments often seek to identify random variables with the largest population means. This inferential task, known as rank verification, has been well-studied on Gauss…
Statistical Significance of Feature Importance Rankings
Jeremy Goldwasser, Giles Hooker
Feature importance scores are ubiquitous tools for understanding the predictions of machine learning models. However, many popular attribution methods suffer from high instability…
Unifying Image Counterfactuals and Feature Attributions with Latent-Space Adversarial Attacks
Jeremy Goldwasser, Giles Hooker
Counterfactuals are a popular framework for interpreting machine learning predictions. These what if explanations are notoriously challenging to create for computer vision models:…
Targeted Learning for Data Fairness
Alexander Asemota, Giles Hooker
Data and algorithms have the potential to produce and perpetuate discrimination and disparate treatment. As such, significant effort has been invested in developing approaches to d…