Bias, Fairness, and Accountability with AI and ML Algorithms

13 May 2021

Jie Chen

Papers citing "Bias, Fairness, and Accountability with AI and ML Algorithms"

26 / 26 papers shown

Title
Properties of fairness measures in the context of varying class imbalance and protected group ratios D. Brzezinski Julia Stachowiak Jerzy Stefanowski Izabela Szczech R. Susmaga Sofya Aksenyuk Uladzimir Ivashka Oleksandr Yasinskyi 219 6 0 13 Nov 2024
Explainable Artificial Intelligence (XAI): Concepts, Taxonomies, Opportunities and Challenges toward Responsible AI Alejandro Barredo Arrieta Natalia Díaz Rodríguez Javier Del Ser Adrien Bennetot Siham Tabik ... S. Gil-Lopez Daniel Molina Richard Benjamins Raja Chatila Francisco Herrera XAI 127 6,293 0 22 Oct 2019
A Debiased MDI Feature Importance Measure for Random Forests Xiao Li Yu Wang Sumanta Basu Karl Kumbier Bin Yu 206 85 0 26 Jun 2019
Enhancing Explainability of Neural Networks through Architecture Constraints Zebin Yang Aijun Zhang Agus Sudjianto AAML 40 87 0 12 Jan 2019
50 Years of Test (Un)fairness: Lessons for Machine Learning Ben Hutchinson Margaret Mitchell AILaw FaML 65 360 0 25 Nov 2018
Aequitas: A Bias and Fairness Audit Toolkit Pedro Saleiro Benedict Kuester Loren Hinkson J. London Abby Stevens Ari Anisfeld Kit T. Rodolfa Rayid Ghani 112 327 0 14 Nov 2018
Model Interpretation: A Unified Derivative-based Framework for Nonparametric Regression and Supervised Machine Learning Xiaoyu Liu Jie Chen Joel Vaughan V. Nair Agus Sudjianto FAtt 27 11 0 22 Aug 2018
Classification with Fairness Constraints: A Meta-Algorithm with Provable Guarantees L. E. Celis Lingxiao Huang Vijay Keswani Nisheeth K. Vishnoi FaML 209 309 0 15 Jun 2018
Explainable Neural Networks based on Additive Index Models J. Vaughan Agus Sudjianto Erind Brahimi Jie Chen V. Nair 57 106 0 05 Jun 2018
Locally Interpretable Models and Effects based on Supervised Partitioning (LIME-SUP) Linwei Hu Jie Chen V. Nair Agus Sudjianto FAtt 57 63 0 02 Jun 2018
A Reductions Approach to Fair Classification Alekh Agarwal A. Beygelzimer Miroslav Dudík John Langford Hanna M. Wallach FaML 227 1,103 0 06 Mar 2018
Consistent Individualized Feature Attribution for Tree Ensembles Scott M. Lundberg G. Erion Su-In Lee FAtt TDI 66 1,405 0 12 Feb 2018
Mitigating Unwanted Biases with Adversarial Learning B. Zhang Blake Lemoine Margaret Mitchell FaML 199 1,390 0 22 Jan 2018
Distill-and-Compare: Auditing Black-Box Models Using Transparent Model Distillation S. Tan R. Caruana Giles Hooker Yin Lou MLAU 108 186 0 17 Oct 2017
On Fairness and Calibration Geoff Pleiss Manish Raghavan Felix Wu Jon M. Kleinberg Kilian Q. Weinberger FaML 200 880 0 06 Sep 2017
On conditional parity as a notion of non-discrimination in machine learning Yaácov Ritov Yuekai Sun Ruofei Zhao 43 40 0 26 Jun 2017
A Unified Approach to Interpreting Model Predictions Scott M. Lundberg Su-In Lee FAtt 1.1K 22,002 0 22 May 2017
Learning Important Features Through Propagating Activation Differences Avanti Shrikumar Peyton Greenside A. Kundaje FAtt 203 3,881 0 10 Apr 2017
Axiomatic Attribution for Deep Networks Mukund Sundararajan Ankur Taly Qiqi Yan OOD FAtt 193 6,018 0 04 Mar 2017
Fairness Beyond Disparate Treatment & Disparate Impact: Learning Classification without Disparate Mistreatment Muhammad Bilal Zafar Isabel Valera Manuel Gomez Rodriguez Krishna P. Gummadi FaML 201 1,213 0 26 Oct 2016
Fair prediction with disparate impact: A study of bias in recidivism prediction instruments Alexandra Chouldechova FaML 302 2,121 0 24 Oct 2016
Equality of Opportunity in Supervised Learning Moritz Hardt Eric Price Nathan Srebro FaML 233 4,330 0 07 Oct 2016
Inherent Trade-Offs in the Fair Determination of Risk Scores Jon M. Kleinberg S. Mullainathan Manish Raghavan FaML 122 1,775 0 19 Sep 2016
Distribution-Free Predictive Inference For Regression Jing Lei M. G'Sell Alessandro Rinaldo Robert Tibshirani Larry A. Wasserman 404 845 0 14 Apr 2016
Layer-wise Relevance Propagation for Neural Networks with Local Renormalization Layers Alexander Binder G. Montavon Sebastian Lapuschkin K. Müller Wojciech Samek FAtt 77 462 0 04 Apr 2016
"Why Should I Trust You?": Explaining the Predictions of Any Classifier Marco Tulio Ribeiro Sameer Singh Carlos Guestrin FAtt FaML 1.2K 17,027 0 16 Feb 2016