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

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

Discover Data (DD), 2022

13 July 2022

Bartosz Krawczyk

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

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Title
Understanding Fairness and Prediction Error through Subspace Decomposition and Influence Analysis Enze Shi Pankaj Bhagwat Zhixian Yang Linglong Kong Bei Jiang 96 0 0 27 Oct 2025
Properties of fairness measures in the context of varying class imbalance and protected group ratiosACM Transactions on Knowledge Discovery from Data (TKDD), 2024 D. Brzezinski Julia Stachowiak Jerzy Stefanowski Izabela Szczech R. Susmaga Sofya Aksenyuk Uladzimir Ivashka Oleksandr Yasinskyi 354 7 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 347 3 0 16 Jul 2024
Fair learning with Wasserstein barycenters for non-decomposable performance measuresInternational Conference on Artificial Intelligence and Statistics (AISTATS), 2022 Solenne Gaucher Nicolas Schreuder Evgenii Chzhen 295 19 0 01 Sep 2022
Bias Mitigation for Machine Learning Classifiers: A Comprehensive SurveyACM Journal on Responsible Computing (JRC), 2022 Max Hort Zhenpeng Chen Jie M. Zhang Mark Harman Federica Sarro FaML AI4CE 329 234 0 14 Jul 2022