Fairness by Explicability and Adversarial SHAP Learning

11 March 2020

Papers citing "Fairness by Explicability and Adversarial SHAP Learning"

5 / 5 papers shown

Title
Understanding User Preferences in Explainable Artificial Intelligence: A Survey and a Mapping Function Proposal M. Hashemi Ali Darejeh Francisco Cruz 40 3 0 07 Feb 2023
Algorithmic decision making methods for fair credit scoring Darie Moldovan FaML 32 7 0 16 Sep 2022
A Survey on Bias and Fairness in Machine Learning Ninareh Mehrabi Fred Morstatter N. Saxena Kristina Lerman Aram Galstyan SyDa FaML 323 4,203 0 23 Aug 2019
Learning Adversarially Fair and Transferable Representations David Madras Elliot Creager T. Pitassi R. Zemel FaML 233 673 0 17 Feb 2018
Fair prediction with disparate impact: A study of bias in recidivism prediction instruments Alexandra Chouldechova FaML 207 2,082 0 24 Oct 2016