@inproceedings{
ghosh2023influence,
title={Influence Based Approaches to Algorithmic Fairness: A Closer Look},
author={Soumya Ghosh and Prasanna Sattigeri and Inkit Padhi and Manish Nagireddy and Jie Chen},
booktitle={XAI in Action: Past, Present, and Future Applications},
year={2023},
url={https://openreview.net/forum?id=3oysFpd6Pq}
}
Off-the-shelf pre-trained models are increasingly common in machine learning. When deployed in the real world, it is essential that such models are not just accurate but also demonstrate qualities like fairness. This paper takes a closer look at recently proposed approaches that edit a pre-trained model for group fairness by re-weighting the training data. We offer perspectives that unify disparate weighting schemes from past studies and pave the way for new weighting strategies to address group fairness concerns.
Influence Based Approaches to Algorithmic Fairness: A Closer Look
Soumya Ghosh Prasanna Sattigeri Inkit Padhi Manish Nagireddy Jie Chen