A Large-Scale Empirical Study on Improving the Fairness of Image Classification Models

8 January 2024

Papers citing "A Large-Scale Empirical Study on Improving the Fairness of Image Classification Models"

5 / 5 papers shown

Title
Whence Is A Model Fair? Fixing Fairness Bugs via Propensity Score Matching Kewen Peng Yicheng Yang Hao Zhuo 25 0 0 23 Apr 2025
Do Existing Testing Tools Really Uncover Gender Bias in Text-to-Image Models? Yunbo Lyu Zhou Yang Yuqing Niu Jing Jiang David Lo 32 1 0 28 Jan 2025
Bias Mimicking: A Simple Sampling Approach for Bias Mitigation Maan Qraitem Kate Saenko Bryan A. Plummer 50 33 0 30 Sep 2022
An Investigation of Why Overparameterization Exacerbates Spurious Correlations Shiori Sagawa Aditi Raghunathan Pang Wei Koh Percy Liang 144 368 0 09 May 2020
A Survey on Bias and Fairness in Machine Learning Ninareh Mehrabi Fred Morstatter N. Saxena Kristina Lerman Aram Galstyan SyDa FaML 286 4,143 0 23 Aug 2019