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Obtaining fairness using optimal transport theory

8 June 2018

Papers citing "Obtaining fairness using optimal transport theory"

50 / 59 papers shown

Title
FaiREE: Fair Classification with Finite-Sample and Distribution-Free Guarantee Puheng Li James Zou Linjun Zhang FaML 532 4 0 13 Mar 2025
Learning with Differentially Private (Sliced) Wasserstein Gradients David Rodríguez-Vítores Clément Lalanne Jean-Michel Loubes FedML 113 0 0 03 Feb 2025
Reducing Biases in Record Matching Through Scores Calibration Mohammad Hossein Moslemi Mostafa Milani 44 0 0 03 Nov 2024
Randomized Transport Plans via Hierarchical Fully Probabilistic Design Sarah Boufelja Anthony Quinn Robert Shorten OT 120 0 0 04 Aug 2024
On the Power of Randomization in Fair Classification and Representation Sushant Agarwal Amit Deshpande FaML 78 5 0 05 Jun 2024
Recent Advances in Optimal Transport for Machine Learning Eduardo Fernandes Montesuma Fred-Maurice Ngole-Mboula Antoine Souloumiac OOD OT 96 39 0 28 Jun 2023
Fairness in Multi-Task Learning via Wasserstein Barycenters Franccois Hu Philipp Ratz Arthur Charpentier 143 10 0 16 Jun 2023
Runtime Monitoring of Dynamic Fairness Properties T. Henzinger Mahyar Karimi Konstantin Kueffner Kaushik Mallik 66 17 0 08 May 2023
Mitigating Source Bias for Fairer Weak Supervision Changho Shin Sonia Cromp Dyah Adila Frederic Sala 71 2 0 30 Mar 2023
Equal Improvability: A New Fairness Notion Considering the Long-term Impact Ozgur Guldogan Yuchen Zeng Jy-yong Sohn Ramtin Pedarsani Kangwook Lee FaML 83 14 0 13 Oct 2022
fAux: Testing Individual Fairness via Gradient Alignment Giuseppe Castiglione Ga Wu C. Srinivasa Simon J. D. Prince 55 4 0 10 Oct 2022
Quantile-constrained Wasserstein projections for robust interpretability of numerical and machine learning models Marouane Il Idrissi Nicolas Bousquet Fabrice Gamboa Bertrand Iooss Jean-Michel Loubes 102 3 0 23 Sep 2022
Fair mapping Sébastien Gambs Rosin Claude Ngueveu 68 0 0 01 Sep 2022
More Data Can Lead Us Astray: Active Data Acquisition in the Presence of Label Bias Yunyi Li Maria De-Arteaga M. Saar-Tsechansky FaML 83 3 0 15 Jul 2022
Bias Mitigation for Machine Learning Classifiers: A Comprehensive Survey Max Hort Zhenpeng Chen Jie M. Zhang Mark Harman Federica Sarro FaML AI4CE 107 177 0 14 Jul 2022
Central limit theorem for the Sliced 1-Wasserstein distance and the max-Sliced 1-Wasserstein distance Xianliang Xu Zhongyi Huang 97 7 0 29 May 2022
An improved central limit theorem and fast convergence rates for entropic transportation costs E. del Barrio Alberto González Sanz Jean-Michel Loubes Jonathan Niles-Weed OT 71 36 0 19 Apr 2022
Obtaining Dyadic Fairness by Optimal Transport Moyi Yang Junjie Sheng Xiangfeng Wang Wenyan Liu Bo Jin Jun Wang H. Zha 70 6 0 09 Feb 2022
Optimal Transport of Classifiers to Fairness Maarten Buyl T. D. Bie FaML 44 11 0 08 Feb 2022
Learning to Predict Graphs with Fused Gromov-Wasserstein Barycenters Luc Brogat-Motte Rémi Flamary Céline Brouard Juho Rousu Florence dÁlché-Buc 92 23 0 08 Feb 2022
A Sociotechnical View of Algorithmic Fairness Mateusz Dolata Stefan Feuerriegel Gerhard Schwabe FaML 76 100 0 27 Sep 2021
Transport-based Counterfactual Models Lucas de Lara Alberto González Sanz Nicholas M. Asher Laurent Risser Jean-Michel Loubes 52 31 0 30 Aug 2021
Plugin Estimation of Smooth Optimal Transport Maps Tudor Manole Sivaraman Balakrishnan Jonathan Niles-Weed Larry A. Wasserman OT 89 100 0 26 Jul 2021
Rates of Estimation of Optimal Transport Maps using Plug-in Estimators via Barycentric Projections Nabarun Deb Promit Ghosal B. Sen OT 126 75 0 04 Jul 2021
Fairness seen as Global Sensitivity Analysis Clément Bénesse Fabrice Gamboa Jean-Michel Loubes Thibaut Boissin 55 16 0 08 Mar 2021
Central Limit Theorems for General Transportation Costs E. del Barrio Alberto González Sanz Jean-Michel Loubes OT 62 28 0 12 Feb 2021
Fairness with Continuous Optimal Transport Silvia Chiappa Aldo Pacchiano OT 92 13 0 06 Jan 2021
Fairness in Machine Learning L. Oneto Silvia Chiappa FaML 321 500 0 31 Dec 2020
A Statistical Test for Probabilistic Fairness Bahar Taşkesen Jose H. Blanchet Daniel Kuhn Viet Anh Nguyen FaML 76 41 0 09 Dec 2020
A contribution to Optimal Transport on incomparable spaces Titouan Vayer OT 73 20 0 09 Nov 2020
All of the Fairness for Edge Prediction with Optimal Transport Charlotte Laclau I. Redko Manvi Choudhary C. Largeron FaML 64 43 0 30 Oct 2020
Robust Fairness under Covariate Shift Ashkan Rezaei Anqi Liu Omid Memarrast Brian Ziebart TTA OOD 135 86 0 11 Oct 2020
Fairness in Machine Learning: A Survey Simon Caton C. Haas FaML 108 653 0 04 Oct 2020
On the Fairness of 'Fake' Data in Legal AI Lauren Boswell A. Prakash 10 1 0 10 Sep 2020
A Distributionally Robust Approach to Fair Classification Bahar Taşkesen Viet Anh Nguyen Daniel Kuhn Jose H. Blanchet FaML 70 62 0 18 Jul 2020
Achieving Fairness via Post-Processing in Web-Scale Recommender Systems Preetam Nandy Cyrus DiCiccio Divya Venugopalan Heloise Logan Kinjal Basu N. Karoui FaML 103 30 0 19 Jun 2020
Fair Regression with Wasserstein Barycenters Evgenii Chzhen Christophe Denis Mohamed Hebiri L. Oneto Massimiliano Pontil 97 108 0 12 Jun 2020
Fair Classification with Noisy Protected Attributes: A Framework with Provable Guarantees L. E. Celis Lingxiao Huang Vijay Keswani Nisheeth K. Vishnoi FaML 44 9 0 08 Jun 2020
Review of Mathematical frameworks for Fairness in Machine Learning E. del Barrio Paula Gordaliza Jean-Michel Loubes FaML FedML 69 40 0 26 May 2020
Projection to Fairness in Statistical Learning Thibaut Le Gouic Jean-Michel Loubes Philippe Rigollet 74 3 0 24 May 2020
Explainable Deep Learning: A Field Guide for the Uninitiated Gabrielle Ras Ning Xie Marcel van Gerven Derek Doran AAML XAI 114 380 0 30 Apr 2020
A survey of bias in Machine Learning through the prism of Statistical Parity for the Adult Data Set Philippe C. Besse E. del Barrio Paula Gordaliza Jean-Michel Loubes Laurent Risser FaML 70 66 0 31 Mar 2020
Fairness in Learning-Based Sequential Decision Algorithms: A Survey Xueru Zhang M. Liu FaML 154 51 0 14 Jan 2020
Quantitative stability of optimal transport maps and linearization of the 2-Wasserstein space Q. Mérigot Alex Delalande Frédéric Chazal OT 53 44 0 14 Oct 2019
Estimation of Wasserstein distances in the Spiked Transport Model Jonathan Niles-Weed Philippe Rigollet 85 103 0 16 Sep 2019
Tackling Algorithmic Bias in Neural-Network Classifiers using Wasserstein-2 Regularization Laurent Risser Alberto González Sanz Quentin Vincenot Jean-Michel Loubes 95 21 0 15 Aug 2019
Wasserstein Fair Classification Ray Jiang Aldo Pacchiano T. Stepleton Heinrich Jiang Silvia Chiappa 71 181 0 28 Jul 2019
Statistical data analysis in the Wasserstein space Jérémie Bigot 69 32 0 19 Jul 2019
Learning Fair Representations for Kernel Models Zilong Tan Samuel Yeom Matt Fredrikson Ameet Talwalkar FaML 110 25 0 27 Jun 2019
Fairness criteria through the lens of directed acyclic graphical models Benjamin R. Baer Daniel E. Gilbert M. Wells FaML 72 6 0 26 Jun 2019