This repo contains annotated fairness papers that I've read as well as my notes.
This repository contains the list of papers related to fairness in ML that I've read over time. Each paper has an associated folder. These folders contain a couple of files each; an annotated version of the paper (by me😁) as well as my notes.
The notes PDFs can be handy in a couple of cases:
- You've read the paper and you just would like to remember key ideas of the paper
- You haven't read the paper but you'd like to know what's the paper is really about (needless to say that the abstract might come handy if that's your goal😅)
To get started on fairness challenges in machine learning, these couple of talks might be really helpful (and they're really amazing👍!):
- Aileen Nielsen for her book Practical Fairness
- IBM team for the amazing package AIF 360
- Microsoft team for Fairlearn