Fair for a few: Improving Fairness in Doubly Imbalanced Datasets

17 June 2025

Papers citing "Fair for a few: Improving Fairness in Doubly Imbalanced Datasets"

6 / 6 papers shown

Title
On Hyperparameter Optimization of Machine Learning Algorithms: Theory and Practice Li Yang Abdallah Shami AI4CE 176 2,102 0 30 Jul 2020
Aequitas: A Bias and Fairness Audit Toolkit Pedro Saleiro Benedict Kuester Loren Hinkson J. London Abby Stevens Ari Anisfeld Kit T. Rodolfa Rayid Ghani 109 327 0 14 Nov 2018
AI Fairness 360: An Extensible Toolkit for Detecting, Understanding, and Mitigating Unwanted Algorithmic Bias Rachel K. E. Bellamy Kuntal Dey Michael Hind Samuel C. Hoffman Stephanie Houde ... Diptikalyan Saha P. Sattigeri Moninder Singh Kush R. Varshney Yunfeng Zhang FaML SyDa 101 810 0 03 Oct 2018
A comparative study of fairness-enhancing interventions in machine learning Sorelle A. Friedler C. Scheidegger Suresh Venkatasubramanian Sonam Choudhary Evan P. Hamilton Derek Roth FaML 109 645 0 13 Feb 2018
Certifying and removing disparate impact Michael Feldman Sorelle A. Friedler John Moeller C. Scheidegger Suresh Venkatasubramanian FaML 201 1,992 0 11 Dec 2014
SMOTE: Synthetic Minority Over-sampling Technique Nitesh Chawla Kevin W. Bowyer Lawrence Hall W. Kegelmeyer AI4TS 377 25,678 0 09 Jun 2011