A survey of bias in Machine Learning through the prism of Statistical Parity for the Adult Data Set

31 March 2020

Papers citing "A survey of bias in Machine Learning through the prism of Statistical Parity for the Adult Data Set"

10 / 10 papers shown

Title
Learning with Differentially Private (Sliced) Wasserstein Gradients David Rodríguez-Vítores Clément Lalanne Jean-Michel Loubes FedML 46 0 0 03 Feb 2025
Bias Testing and Mitigation in LLM-based Code Generation Dong Huang Qingwen Bu Jie M. Zhang Xiaofei Xie Junjie Chen Heming Cui 48 21 0 03 Sep 2023
Uncertainty in Fairness Assessment: Maintaining Stable Conclusions Despite Fluctuations Ainhize Barrainkua Paula Gordaliza Jose A. Lozano Novi Quadrianto 21 1 0 02 Feb 2023
Cluster-level Group Representativity Fairness in $k$ -means Clustering Stanley Simoes Deepak P Muiris Maccarthaigh FaML 22 0 0 29 Dec 2022
Debiasing Deep Chest X-Ray Classifiers using Intra- and Post-processing Methods Ricards Marcinkevics Ece Ozkan Julia E. Vogt 25 18 0 26 Jul 2022
Fairness constraint in Structural Econometrics and Application to fair estimation using Instrumental Variables S. Centorrino J. Florens Jean-Michel Loubes FaML 20 1 0 16 Feb 2022
To what extent should we trust AI models when they extrapolate? Roozbeh Yousefzadeh Xuenan Cao 27 5 0 27 Jan 2022
Representative & Fair Synthetic Data P. Tiwald Alexandra Ebert Daniel Soukup 21 12 0 07 Apr 2021
Projection to Fairness in Statistical Learning Thibaut Le Gouic Jean-Michel Loubes Philippe Rigollet 17 3 0 24 May 2020
Fair prediction with disparate impact: A study of bias in recidivism prediction instruments Alexandra Chouldechova FaML 207 2,090 0 24 Oct 2016