Explainable post-training bias mitigation with distribution-based fairness metrics

1 April 2025

Papers citing "Explainable post-training bias mitigation with distribution-based fairness metrics"

15 / 15 papers shown

Title
Less Discriminatory Alternative and Interpretable XGBoost Framework for Binary Classification Andrew Pangia Agus Sudjianto Aijun Zhang Taufiquar Khan FaML 59 1 0 24 Oct 2024
On marginal feature attributions of tree-based models Khashayar Filom A. Miroshnikov Konstandinos Kotsiopoulos Arjun Ravi Kannan FAtt 57 3 0 16 Feb 2023
Repairing Regressors for Fair Binary Classification at Any Decision Threshold Kweku Kwegyir-Aggrey A. Feder Cooper Jessica Dai John P Dickerson Keegan E. Hines Suresh Venkatasubramanian FaML 89 7 0 14 Mar 2022
Designing Inherently Interpretable Machine Learning Models Agus Sudjianto Aijun Zhang FaML 53 31 0 02 Nov 2021
Tabular Data: Deep Learning is Not All You Need Ravid Shwartz-Ziv Amitai Armon LMTD 162 1,288 0 06 Jun 2021
Wasserstein-based fairness interpretability framework for machine learning models A. Miroshnikov Konstandinos Kotsiopoulos Ryan Franks Arjun Ravi Kannan FAtt 67 15 0 06 Nov 2020
Fair Regression with Wasserstein Barycenters Evgenii Chzhen Christophe Denis Mohamed Hebiri L. Oneto Massimiliano Pontil 82 108 0 12 Jun 2020
GAMI-Net: An Explainable Neural Network based on Generalized Additive Models with Structured Interactions Zebin Yang Aijun Zhang Agus Sudjianto FAtt 155 130 0 16 Mar 2020
Identifying and Correcting Label Bias in Machine Learning Heinrich Jiang Ofir Nachum FaML 101 284 0 15 Jan 2019
A Tutorial on Bayesian Optimization P. Frazier GP 113 1,797 0 08 Jul 2018
Interpretable & Explorable Approximations of Black Box Models Himabindu Lakkaraju Ece Kamar R. Caruana J. Leskovec FAtt 79 254 0 04 Jul 2017
A Unified Approach to Interpreting Model Predictions Scott M. Lundberg Su-In Lee FAtt 1.1K 22,090 0 22 May 2017
Equality of Opportunity in Supervised Learning Moritz Hardt Eric Price Nathan Srebro FaML 236 4,341 0 07 Oct 2016
"Why Should I Trust You?": Explaining the Predictions of Any Classifier Marco Tulio Ribeiro Sameer Singh Carlos Guestrin FAtt FaML 1.2K 17,071 0 16 Feb 2016
Certifying and removing disparate impact Michael Feldman Sorelle A. Friedler John Moeller C. Scheidegger Suresh Venkatasubramanian FaML 212 1,996 0 11 Dec 2014