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Rethinking Fair Representation Learning for Performance-Sensitive Tasks

5 October 2024

Charles Jones

Fabio De Sousa Ribeiro

Mélanie Roschewitz

Daniel Coelho De Castro

Papers citing "Rethinking Fair Representation Learning for Performance-Sensitive Tasks"

41 / 41 papers shown

Title
Subgroups Matter for Robust Bias Mitigation A. Alloula Charles Jones Ben Glocker Bartłomiej W. Papież 36 0 0 27 May 2025
The Vendiscope: An Algorithmic Microscope For Data Collections Amey P. Pasarkar Adji Bousso Dieng 90 2 0 15 Feb 2025
10 Years of Fair Representations: Challenges and Opportunities Mattia Cerrato Marius Köppel Philipp Wolf Stefan Kramer FaML 89 3 0 04 Jul 2024
Causal Context Connects Counterfactual Fairness to Robust Prediction and Group Fairness Jacy Reese Anthis Victor Veitch 74 16 0 30 Oct 2023
FairTune: Optimizing Parameter Efficient Fine Tuning for Fairness in Medical Image Analysis Raman Dutt Ondrej Bohdal Sotirios A. Tsaftaris Timothy M. Hospedales 102 14 0 08 Oct 2023
The Role of Subgroup Separability in Group-Fair Medical Image Classification Charles Jones Mélanie Roschewitz Ben Glocker OOD 70 10 0 06 Jul 2023
Identifiability of latent-variable and structural-equation models: from linear to nonlinear Aapo Hyvarinen Ilyes Khemakhem R. Monti CML 94 46 0 06 Feb 2023
The Unfairness of Fair Machine Learning: Levelling down and strict egalitarianism by default Brent Mittelstadt Sandra Wachter Chris Russell FaML 77 49 0 05 Feb 2023
MEDFAIR: Benchmarking Fairness for Medical Imaging Yongshuo Zong Yongxin Yang Timothy M. Hospedales OOD 148 65 0 04 Oct 2022
Fairness and robustness in anti-causal prediction Maggie Makar Alexander DÁmour OOD 97 12 0 20 Sep 2022
Causal Fairness Analysis Drago Plečko Elias Bareinboim CML 51 49 0 23 Jul 2022
Invariant and Transportable Representations for Anti-Causal Domain Shifts Yibo Jiang Victor Veitch OOD 183 36 0 04 Jul 2022
Improving the Fairness of Chest X-ray Classifiers Haoran Zhang Natalie Dullerud Karsten Roth Lauren Oakden-Rayner Stephen Pfohl Marzyeh Ghassemi 79 66 0 23 Mar 2022
Leveling Down in Computer Vision: Pareto Inefficiencies in Fair Deep Classifiers Dominik Zietlow Michael Lohaus Guha Balakrishnan Matthäus Kleindessner Francesco Locatello Bernhard Schölkopf Chris Russell FaML 69 74 0 09 Mar 2022
Diagnosing failures of fairness transfer across distribution shift in real-world medical settings Jessica Schrouff Natalie Harris Oluwasanmi Koyejo Ibrahim Alabdulmohsin Eva Schnider ... Vivek Natarajan Alan Karthikesalingam Katherine A. Heller Silvia Chiappa Alexander DÁmour OOD 145 56 0 02 Feb 2022
Evaluating Deep Neural Networks Trained on Clinical Images in Dermatology with the Fitzpatrick 17k Dataset Matthew Groh Caleb Harris L. Soenksen Felix Lau Rachel Han Aerin Kim A. Koochek Omar Badri 155 192 0 20 Apr 2021
EnD: Entangling and Disentangling deep representations for bias correction Enzo Tartaglione C. Barbano Marco Grangetto 81 124 0 02 Mar 2021
Fundamental Limits and Tradeoffs in Invariant Representation Learning Han Zhao Chen Dan Bryon Aragam Tommi Jaakkola Geoffrey J. Gordon Pradeep Ravikumar FaML 88 45 0 19 Dec 2020
Minimax Pareto Fairness: A Multi Objective Perspective Natalia Martínez Martín Bertrán Guillermo Sapiro FaML 79 197 0 03 Nov 2020
An Empirical Characterization of Fair Machine Learning For Clinical Risk Prediction Stephen Pfohl Agata Foryciarz N. Shah FaML 102 113 0 20 Jul 2020
Fairness by Learning Orthogonal Disentangled Representations Mhd Hasan Sarhan Nassir Navab Abouzar Eslami Shadi Albarqouni FaML OOD CML 98 97 0 12 Mar 2020
Causality matters in medical imaging Daniel Coelho De Castro Ian Walker Ben Glocker CML 59 346 0 17 Dec 2019
Towards Fairness in Visual Recognition: Effective Strategies for Bias Mitigation Zeyu Wang Klint Qinami Yannis Karakozis Kyle Genova P. Nair Kenji Hata Olga Russakovsky 89 365 0 26 Nov 2019
Conditional Learning of Fair Representations Han Zhao Amanda Coston T. Adel Geoffrey J. Gordon FaML 84 109 0 16 Oct 2019
Variational Autoencoders and Nonlinear ICA: A Unifying Framework Ilyes Khemakhem Diederik P. Kingma Ricardo Pio Monti Aapo Hyvarinen OOD 77 598 0 10 Jul 2019
Invariant Risk Minimization Martín Arjovsky Léon Bottou Ishaan Gulrajani David Lopez-Paz OOD 205 2,246 0 05 Jul 2019
Inherent Tradeoffs in Learning Fair Representations Han Zhao Geoffrey J. Gordon FaML 70 218 0 19 Jun 2019
Flexibly Fair Representation Learning by Disentanglement Elliot Creager David Madras J. Jacobsen Marissa A. Weis Kevin Swersky T. Pitassi R. Zemel FaML OOD 196 334 0 06 Jun 2019
CheXpert: A Large Chest Radiograph Dataset with Uncertainty Labels and Expert Comparison Jeremy Irvin Pranav Rajpurkar M. Ko Yifan Yu Silviana Ciurea-Ilcus ... D. Larson C. Langlotz Bhavik Patel M. Lungren A. Ng 120 2,605 0 21 Jan 2019
Learning Not to Learn: Training Deep Neural Networks with Biased Data Byungju Kim Hyunwoo Kim Kyungsu Kim Sungjin Kim Junmo Kim OOD 62 411 0 26 Dec 2018
Turning a Blind Eye: Explicit Removal of Biases and Variation from Deep Neural Network Embeddings Mohsan S. Alvi Andrew Zisserman C. Nellåker FaML 133 248 0 06 Sep 2018
Path-Specific Counterfactual Fairness Silvia Chiappa Thomas P. S. Gillam CML FaML 95 341 0 22 Feb 2018
Learning Adversarially Fair and Transferable Representations David Madras Elliot Creager T. Pitassi R. Zemel FaML 384 685 0 17 Feb 2018
Counterfactual Fairness Matt J. Kusner Joshua R. Loftus Chris Russell Ricardo M. A. Silva FaML 230 1,587 0 20 Mar 2017
Understanding deep learning requires rethinking generalization Chiyuan Zhang Samy Bengio Moritz Hardt Benjamin Recht Oriol Vinyals HAI 356 4,636 0 10 Nov 2016
Fair prediction with disparate impact: A study of bias in recidivism prediction instruments Alexandra Chouldechova FaML 304 2,131 0 24 Oct 2016
Equality of Opportunity in Supervised Learning Moritz Hardt Eric Price Nathan Srebro FaML 236 4,341 0 07 Oct 2016
Deep Residual Learning for Image Recognition Kaiming He Xinming Zhang Shaoqing Ren Jian Sun MedIm 2.3K 194,641 0 10 Dec 2015
Censoring Representations with an Adversary Harrison Edwards Amos Storkey AAML FaML 74 506 0 18 Nov 2015
Causal inference using invariant prediction: identification and confidence intervals J. Peters Peter Buhlmann N. Meinshausen OOD 124 974 0 06 Jan 2015
Causal Networks: Semantics and Expressiveness Thomas Verma Judea Pearl GNN 108 551 0 27 Mar 2013