v1v2 (latest)

Fairness in Multi-Task Learning via Wasserstein Barycenters

16 June 2023

Papers citing "Fairness in Multi-Task Learning via Wasserstein Barycenters"

28 / 28 papers shown

Title
Multi-Output Distributional Fairness via Post-Processing Gang Li Qihang Lin Ayush Ghosh Tianbao Yang 163 0 0 31 Aug 2024
Fair learning with Wasserstein barycenters for non-decomposable performance measures Solenne Gaucher Nicolas Schreuder Evgenii Chzhen 90 15 0 01 Sep 2022
Learning to Teach Fairness-aware Deep Multi-task Learning Arjun Roy Eirini Ntoutsi 76 7 0 16 Jun 2022
Multi-Task Learning as a Bargaining Game Aviv Navon Aviv Shamsian Idan Achituve Haggai Maron Kenji Kawaguchi Gal Chechik Ethan Fetaya 92 154 0 02 Feb 2022
Conflict-Averse Gradient Descent for Multi-task Learning Bo Liu Xingchao Liu Xiaojie Jin Peter Stone Qiang Liu 105 318 0 26 Oct 2021
Fairness guarantee in multi-class classification Christophe Denis Romuald Elie Mohamed Hebiri Franccois Hu FaML 123 50 0 28 Sep 2021
Retiring Adult: New Datasets for Fair Machine Learning Frances Ding Moritz Hardt John Miller Ludwig Schmidt 229 463 0 10 Aug 2021
Understanding and Improving Fairness-Accuracy Trade-offs in Multi-Task Learning Yuyan Wang Xuezhi Wang Alex Beutel Flavien Prost Jilin Chen Ed H. Chi FaML 61 48 0 04 Jun 2021
Gradient Vaccine: Investigating and Improving Multi-task Optimization in Massively Multilingual Models Zirui Wang Yulia Tsvetkov Orhan Firat Yuan Cao 74 202 0 12 Oct 2020
Rank-Based Multi-task Learning for Fair Regression Chen Zhao Feng Chen FaML 53 31 0 23 Sep 2020
Fair Regression with Wasserstein Barycenters Evgenii Chzhen Christophe Denis Mohamed Hebiri L. Oneto Massimiliano Pontil 88 108 0 12 Jun 2020
Gradient Surgery for Multi-Task Learning Tianhe Yu Saurabh Kumar Abhishek Gupta Sergey Levine Karol Hausman Chelsea Finn 197 1,230 0 19 Jan 2020
Fair Data Adaptation with Quantile Preservation Drago Plečko N. Meinshausen 67 30 0 15 Nov 2019
Wasserstein Fair Classification Ray Jiang Aldo Pacchiano T. Stepleton Heinrich Jiang Silvia Chiappa 69 181 0 28 Jul 2019
Leveraging Labeled and Unlabeled Data for Consistent Fair Binary Classification Evgenii Chzhen Christophe Denis Mohamed Hebiri L. Oneto Massimiliano Pontil FaML 215 87 0 12 Jun 2019
Fair Regression: Quantitative Definitions and Reduction-based Algorithms Alekh Agarwal Miroslav Dudík Zhiwei Steven Wu FaML 70 248 0 30 May 2019
Which Tasks Should Be Learned Together in Multi-task Learning? Trevor Scott Standley Amir Zamir Dawn Chen Leonidas Guibas Jitendra Malik Silvio Savarese 120 517 0 18 May 2019
Taking Advantage of Multitask Learning for Fair Classification L. Oneto Michele Donini Amon Elders Massimiliano Pontil FaML 67 60 0 19 Oct 2018
Obtaining fairness using optimal transport theory E. del Barrio Fabrice Gamboa Paula Gordaliza Jean-Michel Loubes FaML 179 181 0 08 Jun 2018
A Reductions Approach to Fair Classification Alekh Agarwal A. Beygelzimer Miroslav Dudík John Langford Hanna M. Wallach FaML 230 1,107 0 06 Mar 2018
Empirical Risk Minimization under Fairness Constraints Michele Donini L. Oneto Shai Ben-David John Shawe-Taylor Massimiliano Pontil FaML 82 445 0 23 Feb 2018
FiLM: Visual Reasoning with a General Conditioning Layer Ethan Perez Florian Strub H. D. Vries Vincent Dumoulin Aaron Courville FAtt AIMat OffRL AI4CE 375 2,239 0 22 Sep 2017
A Survey on Multi-Task Learning Yu Zhang Qiang Yang AIMat 607 2,247 0 25 Jul 2017
An Overview of Multi-Task Learning in Deep Neural Networks Sebastian Ruder CVBM 161 2,833 0 15 Jun 2017
Iterative Orthogonal Feature Projection for Diagnosing Bias in Black-Box Models Julius Adebayo Lalana Kagal MLAU 134 65 0 15 Nov 2016
Fairness Beyond Disparate Treatment & Disparate Impact: Learning Classification without Disparate Mistreatment Muhammad Bilal Zafar Isabel Valera Manuel Gomez Rodriguez Krishna P. Gummadi FaML 210 1,214 0 26 Oct 2016
Equality of Opportunity in Supervised Learning Moritz Hardt Eric Price Nathan Srebro FaML 236 4,341 0 07 Oct 2016
A Model of Inductive Bias Learning Jonathan Baxter 115 1,217 0 01 Jun 2011