Fairness and Explainability: Bridging the Gap Towards Fair Model Explanations

7 December 2022

Papers citing "Fairness and Explainability: Bridging the Gap Towards Fair Model Explanations"

7 / 7 papers shown

Title
Procedural Fairness in Machine Learning Ziming Wang Changwu Huang Xin Yao FaML 55 0 0 02 Apr 2024
On Explaining Unfairness: An Overview Christos Fragkathoulas Vasiliki Papanikou Danae Pla Karidi E. Pitoura XAI FaML 23 2 0 16 Feb 2024
On the Relationship Between Interpretability and Explainability in Machine Learning Benjamin Leblanc Pascal Germain FaML 36 0 0 20 Nov 2023
A Framework for Data-Driven Explainability in Mathematical Optimization Kevin-Martin Aigner Marc Goerigk Michael Hartisch F. Liers Arthur Miehlich 32 2 0 16 Aug 2023
Fairness in Machine Learning L. Oneto Silvia Chiappa FaML 256 492 0 31 Dec 2020
Explainability in Graph Neural Networks: A Taxonomic Survey Hao Yuan Haiyang Yu Shurui Gui Shuiwang Ji 167 596 0 31 Dec 2020
A Survey on Bias and Fairness in Machine Learning Ninareh Mehrabi Fred Morstatter N. Saxena Kristina Lerman Aram Galstyan SyDa FaML 349 4,237 0 23 Aug 2019