Search Results for author: Emile Givental

Found 2 papers, 1 papers with code

Fair Meta-Learning: Learning How to Learn Fairly

no code implementations • 6 Nov 2019 • Dylan Slack, Sorelle Friedler, Emile Givental

Data sets for fairness relevant tasks can lack examples or be biased according to a specific label in a sensitive attribute.

Attribute Fairness +1

Paper
Add Code

Fairness Warnings and Fair-MAML: Learning Fairly with Minimal Data

1 code implementation • 24 Aug 2019 • Dylan Slack, Sorelle Friedler, Emile Givental

Then, we illustrate the usefulness of both algorithms as a combined method for training models from a few data points on new tasks while using Fairness Warnings as interpretable boundary conditions under which the newly trained model may not be fair.

Fairness Meta-Learning

Paper
Code

Cannot find the paper you are looking for? You can Submit a new open access paper.