Search Results for author: Joshua Loftus

Found 2 papers, 0 papers with code

When Worlds Collide: Integrating Different Counterfactual Assumptions in Fairness

no code implementations NeurIPS 2017 Chris Russell, Matt J. Kusner, Joshua Loftus, Ricardo Silva

In this paper, we show how it is possible to make predictions that are approximately fair with respect to multiple possible causal models at once, thus mitigating the problem of exact causal specification.

counterfactual Counterfactual Inference +1

Tests in adaptive regression via the Kac-Rice formula

no code implementations14 Aug 2013 Jonathan Taylor, Joshua Loftus, Ryan Tibshirani

We derive an exact p-value for testing a global null hypothesis in a general adaptive regression problem.

Methodology

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