Hidden Technical Debts for Fair Machine Learning in Financial Services

Hidden Technical Debts for Fair Machine Learning in Financial Services

18 March 2021

Papers citing "Hidden Technical Debts for Fair Machine Learning in Financial Services"

11 / 11 papers shown

Title
The Criminality From Face Illusion Kevin W. Bowyer Michael C. King Walter J. Scheirer Kushal Vangara CVBM 33 20 0 06 Jun 2020
A Survey on Bias and Fairness in Machine Learning Ninareh Mehrabi Fred Morstatter N. Saxena Kristina Lerman Aram Galstyan SyDa FaML 536 4,333 0 23 Aug 2019
A Unified Approach to Quantifying Algorithmic Unfairness: Measuring Individual & Group Unfairness via Inequality Indices Till Speicher Hoda Heidari Nina Grgic-Hlaca Krishna P. Gummadi Adish Singla Adrian Weller Muhammad Bilal Zafar FaML 58 263 0 02 Jul 2018
iFair: Learning Individually Fair Data Representations for Algorithmic Decision Making Preethi Lahoti Krishna P. Gummadi Gerhard Weikum FaML 64 170 0 04 Jun 2018
A Reductions Approach to Fair Classification Alekh Agarwal A. Beygelzimer Miroslav Dudík John Langford Hanna M. Wallach FaML 203 1,099 0 06 Mar 2018
Learning Adversarially Fair and Transferable Representations David Madras Elliot Creager T. Pitassi R. Zemel FaML 358 681 0 17 Feb 2018
Mitigating Unwanted Biases with Adversarial Learning B. Zhang Blake Lemoine Margaret Mitchell FaML 160 1,380 0 22 Jan 2018
Counterfactual Fairness Matt J. Kusner Joshua R. Loftus Chris Russell Ricardo M. A. Silva FaML 197 1,576 0 20 Mar 2017
Fair prediction with disparate impact: A study of bias in recidivism prediction instruments Alexandra Chouldechova FaML 295 2,109 0 24 Oct 2016
Equality of Opportunity in Supervised Learning Moritz Hardt Eric Price Nathan Srebro FaML 196 4,301 0 07 Oct 2016
Certifying and removing disparate impact Michael Feldman Sorelle A. Friedler John Moeller C. Scheidegger Suresh Venkatasubramanian FaML 173 1,984 0 11 Dec 2014