Learning for Counterfactual Fairness from Observational Data

17 July 2023

Aidong Zhang

Papers citing "Learning for Counterfactual Fairness from Observational Data"

20 / 20 papers shown

Title
Counterfactual Invariance to Spurious Correlations: Why and How to Pass Stress Tests Victor Veitch Alexander DÁmour Steve Yadlowsky Jacob Eisenstein OOD 55 93 0 31 May 2021
Out-of-distribution Prediction with Invariant Risk Minimization: The Limitation and An Effective Fix Ruocheng Guo Pengchuan Zhang Hao Liu Emre Kıcıman OOD 73 37 0 16 Jan 2021
Fairness in Machine Learning L. Oneto Silvia Chiappa FaML 282 494 0 31 Dec 2020
Counterfactual Fairness with Disentangled Causal Effect Variational Autoencoder Hyemi Kim Seungjae Shin Joonho Jang Kyungwoo Song Weonyoung Joo Wanmo Kang Il-Chul Moon BDL CML 71 57 0 24 Nov 2020
Survey on Causal-based Machine Learning Fairness Notions K. Makhlouf Sami Zhioua C. Palamidessi FaML 51 85 0 19 Oct 2020
Environment Inference for Invariant Learning Elliot Creager J. Jacobsen R. Zemel OOD 61 382 0 14 Oct 2020
Adversarial Learning for Counterfactual Fairness Vincent Grari Sylvain Lamprier Marcin Detyniecki FaML 47 23 0 30 Aug 2020
Domain Generalization using Causal Matching Divyat Mahajan Shruti Tople Amit Sharma OOD 89 336 0 12 Jun 2020
Enforcing Predictive Invariance across Structured Biomedical Domains Wengong Jin Regina Barzilay Tommi Jaakkola OOD 59 30 0 06 Jun 2020
Distributionally Robust Neural Networks for Group Shifts: On the Importance of Regularization for Worst-Case Generalization Shiori Sagawa Pang Wei Koh Tatsunori B. Hashimoto Percy Liang OOD 108 1,243 0 20 Nov 2019
Invariant Risk Minimization Martín Arjovsky Léon Bottou Ishaan Gulrajani David Lopez-Paz OOD 186 2,229 0 05 Jul 2019
Fairness-Aware Ranking in Search & Recommendation Systems with Application to LinkedIn Talent Search S. Geyik Stuart Ambler K. Kenthapadi 92 382 0 30 Apr 2019
The Frontiers of Fairness in Machine Learning Alexandra Chouldechova Aaron Roth FaML 187 416 0 20 Oct 2018
Pyro: Deep Universal Probabilistic Programming Eli Bingham Jonathan P. Chen M. Jankowiak F. Obermeyer Neeraj Pradhan Theofanis Karaletsos Rohit Singh Paul A. Szerlip Paul Horsfall Noah D. Goodman BDL GP 157 1,054 0 18 Oct 2018
Fairness in Criminal Justice Risk Assessments: The State of the Art R. Berk Hoda Heidari S. Jabbari Michael Kearns Aaron Roth 51 995 0 27 Mar 2017
Fair prediction with disparate impact: A study of bias in recidivism prediction instruments Alexandra Chouldechova FaML 300 2,114 0 24 Oct 2016
Equality of Opportunity in Supervised Learning Moritz Hardt Eric Price Nathan Srebro FaML 228 4,312 0 07 Oct 2016
Learning Transferable Features with Deep Adaptation Networks Mingsheng Long Yue Cao Jianmin Wang Michael I. Jordan OOD 220 5,206 0 10 Feb 2015
Auto-Encoding Variational Bayes Diederik P. Kingma Max Welling BDL 452 16,929 0 20 Dec 2013
Program Evaluation and Causal Inference with High-Dimensional Data A. Belloni Victor Chernozhukov Iván Fernández-Val Christian B. Hansen CML 190 358 0 11 Nov 2013