Search Results for author:
Found 3 papers, 0 papers with code
Interpretable Assessment of Fairness During Model Evaluation
For companies developing products or algorithms, it is important to understand the potential effects not only globally, but also on sub-populations of users.
Fairness through Experimentation: Inequality in A/B testing as an approach to responsible design
We also introduce the concept of site-wide inequality impact, which captures the inclusiveness impact of targeting specific subpopulations for experiments, and show how to conduct statistical inference on this impact.
Social and Information Networks Econometrics
The Bayesian SLOPE
A direct characterization of the posterior is provided which suggests a Gibbs sampler that does not involve latent variables.
