Towards Understanding Fairness and its Composition in Ensemble Machine
Learning

Towards Understanding Fairness and its Composition in Ensemble Machine Learning

8 December 2022

Papers citing "Towards Understanding Fairness and its Composition in Ensemble Machine Learning"

15 / 15 papers shown

Title
Whence Is A Model Fair? Fixing Fairness Bugs via Propensity Score Matching Kewen Peng Yicheng Yang Hao Zhuo 32 0 0 23 Apr 2025
Diversity Drives Fairness: Ensemble of Higher Order Mutants for Intersectional Fairness of Machine Learning Software Zhenpeng Chen Xinyue Li Jun Zhang Federica Sarro Yang Liu FaML 83 2 0 11 Dec 2024
Different Horses for Different Courses: Comparing Bias Mitigation Algorithms in ML Prakhar Ganesh Usman Gohar Lu Cheng G. Farnadi FaML 42 2 0 17 Nov 2024
PFAttack: Stealthy Attack Bypassing Group Fairness in Federated Learning Jiashi Gao Ziwei Wang Xiangyu Zhao Xin Yao Xuetao Wei 25 0 0 09 Oct 2024
FAIREDU: A Multiple Regression-Based Method for Enhancing Fairness in Machine Learning Models for Educational Applications Nga Pham Minh Kha Do Tran Vu Dai Pham Ngoc Hung Anh Nguyen-Duc 31 0 0 08 Oct 2024
Bias Testing and Mitigation in LLM-based Code Generation Dong Huang Qingwen Bu Jie M. Zhang Xiaofei Xie Junjie Chen Heming Cui 48 20 0 03 Sep 2023
Towards Better Fairness-Utility Trade-off: A Comprehensive Measurement-Based Reinforcement Learning Framework Simiao Zhang Jitao Bai Menghong Guan Yihao Huang Yueling Zhang Jun Sun G. Pu FaML 32 1 0 21 Jul 2023
Minimum Levels of Interpretability for Artificial Moral Agents Avish Vijayaraghavan C. Badea AI4CE 27 5 0 02 Jul 2023
Fix Fairness, Don't Ruin Accuracy: Performance Aware Fairness Repair using AutoML Giang Nguyen Sumon Biswas Hridesh Rajan FaML 43 13 0 15 Jun 2023
A Survey on Intersectional Fairness in Machine Learning: Notions, Mitigation, and Challenges Usman Gohar Lu Cheng FaML 35 31 0 11 May 2023
Fairify: Fairness Verification of Neural Networks Sumon Biswas Hridesh Rajan 25 24 0 08 Dec 2022
On the Robustness of Random Forest Against Untargeted Data Poisoning: An Ensemble-Based Approach M. Anisetti C. Ardagna Alessandro Balestrucci Nicola Bena Ernesto Damiani C. Yeun AAML OOD 32 10 0 28 Sep 2022
An Empirical Study of Modular Bias Mitigators and Ensembles Michael Feffer Martin Hirzel Samuel C. Hoffman Kiran Kate Parikshit Ram Avraham Shinnar 38 8 0 01 Feb 2022
Improving fairness in machine learning systems: What do industry practitioners need? Kenneth Holstein Jennifer Wortman Vaughan Hal Daumé Miroslav Dudík Hanna M. Wallach FaML HAI 192 743 0 13 Dec 2018
Fair prediction with disparate impact: A study of bias in recidivism prediction instruments Alexandra Chouldechova FaML 207 2,090 0 24 Oct 2016