Towards A Holistic View of Bias in Machine Learning: Bridging Algorithmic Fairness and Imbalanced Learning

13 July 2022

Papers citing "Towards A Holistic View of Bias in Machine Learning: Bridging Algorithmic Fairness and Imbalanced Learning"

5 / 5 papers shown

Title
Properties of fairness measures in the context of varying class imbalance and protected group ratios D. Brzezinski Julia Stachowiak Jerzy Stefanowski Izabela Szczech R. Susmaga Sofya Aksenyuk Uladzimir Ivashka Oleksandr Yasinskyi 143 4 0 13 Nov 2024
EARN Fairness: Explaining, Asking, Reviewing, and Negotiating Artificial Intelligence Fairness Metrics Among Stakeholders Lin Luo Yuri Nakao Mathieu Chollet Hiroya Inakoshi Simone Stumpf 38 0 0 16 Jul 2024
Fairness-aware Class Imbalanced Learning Shivashankar Subramanian Afshin Rahimi Timothy Baldwin Trevor Cohn Lea Frermann FaML 106 28 0 21 Sep 2021
Fair prediction with disparate impact: A study of bias in recidivism prediction instruments Alexandra Chouldechova FaML 207 2,084 0 24 Oct 2016
SMOTE: Synthetic Minority Over-sampling Technique Nitesh V. Chawla Kevin W. Bowyer Lawrence Hall W. Kegelmeyer AI4TS 163 25,256 0 09 Jun 2011