Procedural Fairness Through Decoupling Objectionable Data Generating Components

5 November 2023

Papers citing "Procedural Fairness Through Decoupling Objectionable Data Generating Components"

6 / 6 papers shown

Title
Causal Conceptions of Fairness and their Consequences H. Nilforoshan Johann D. Gaebler Ravi Shroff Sharad Goel FaML 126 45 0 12 Jul 2022
Fair Representation Learning through Implicit Path Alignment Changjian Shui Qi Chen Jiaqi Li Boyu Wang Christian Gagné 36 28 0 26 May 2022
On the Fairness of Causal Algorithmic Recourse Julius von Kügelgen Amir-Hossein Karimi Umang Bhatt Isabel Valera Adrian Weller Bernhard Schölkopf FaML 70 82 0 13 Oct 2020
A Survey on Bias and Fairness in Machine Learning Ninareh Mehrabi Fred Morstatter N. Saxena Kristina Lerman Aram Galstyan SyDa FaML 294 4,187 0 23 Aug 2019
Learning Adversarially Fair and Transferable Representations David Madras Elliot Creager T. Pitassi R. Zemel FaML 213 669 0 17 Feb 2018
Fair prediction with disparate impact: A study of bias in recidivism prediction instruments Alexandra Chouldechova FaML 185 2,082 0 24 Oct 2016