Fair Kernel Learning

16 October 2017

Gustau Camps-Valls

Papers citing "Fair Kernel Learning"

36 / 36 papers shown

Title
fairret: a Framework for Differentiable Fairness Regularization Terms Maarten Buyl Marybeth Defrance T. D. Bie FedML 71 4 0 26 Oct 2023
Mean Parity Fair Regression in RKHS Shaokui Wei Jiayin Liu Bing Li H. Zha 56 3 0 21 Feb 2023
Returning The Favour: When Regression Benefits From Probabilistic Causal Knowledge S. Bouabid Jake Fawkes Dino Sejdinovic CML 93 0 0 26 Jan 2023
Fairness-aware Regression Robust to Adversarial Attacks Yulu Jin Lifeng Lai FaML OOD 83 4 0 04 Nov 2022
Fairness Reprogramming Guanhua Zhang Yihua Zhang Yang Zhang Wenqi Fan Qing Li Sijia Liu Shiyu Chang AAML 213 40 0 21 Sep 2022
Bias Mitigation for Machine Learning Classifiers: A Comprehensive Survey Max Hort Zhenpeng Chen Jie M. Zhang Mark Harman Federica Sarro FaML AI4CE 109 177 0 14 Jul 2022
Fair Generalized Linear Models with a Convex Penalty Hyungrok Do Preston J. Putzel Axel Martin Padhraic Smyth Judy Zhong FaML 68 14 0 18 Jun 2022
Selective Regression Under Fairness Criteria Abhin Shah Yuheng Bu Joshua K. Lee Subhro Das Yikang Shen P. Sattigeri G. Wornell 114 28 0 28 Oct 2021
RKHS-SHAP: Shapley Values for Kernel Methods Siu Lun Chau Robert Hu Javier I. González Dino Sejdinovic FAtt 83 20 0 18 Oct 2021
On Characterizing the Trade-off in Invariant Representation Learning Bashir Sadeghi Sepehr Dehdashtian Vishnu Boddeti 113 7 0 08 Sep 2021
Learning Fair Canonical Polyadical Decompositions using a Kernel Independence Criterion Kevin Kim Alex Gittens 44 2 0 27 Apr 2021
Towards a Collective Agenda on AI for Earth Science Data Analysis D. Tuia R. Roscher Jan Dirk Wegner Nathan Jacobs Xiaoxiang Zhu Gustau Camps-Valls AI4CE 80 70 0 11 Apr 2021
A Stochastic Optimization Framework for Fair Risk Minimization Andrew Lowy Sina Baharlouei Rakesh Pavan Meisam Razaviyayn Ahmad Beirami FaML 69 21 0 24 Feb 2021
Fairness in Machine Learning L. Oneto Silvia Chiappa FaML 324 500 0 31 Dec 2020
Living in the Physics and Machine Learning Interplay for Earth Observation Gustau Camps-Valls D. Svendsen Jordi Cortés-Andrés Álvaro Moreno-Martínez Adrián Pérez-Suay J. Adsuara I. Martín M. Piles Jordi Munoz-Marí Luca Martino PINN AI4CE 39 6 0 18 Oct 2020
Fairness in Machine Learning: A Survey Simon Caton C. Haas FaML 110 654 0 04 Oct 2020
Fair Meta-Learning For Few-Shot Classification Chengli Zhao Changbin Li Jincheng Li Feng Chen FaML 65 26 0 23 Sep 2020
Fair Regression with Wasserstein Barycenters Evgenii Chzhen Christophe Denis Mohamed Hebiri L. Oneto Massimiliano Pontil 97 108 0 12 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
Spectral Ranking with Covariates Siu Lun Chau Ning Zhang Dino Sejdinovic 49 9 0 08 May 2020
Explainable Deep Learning: A Field Guide for the Uninitiated Gabrielle Ras Ning Xie Marcel van Gerven Derek Doran AAML XAI 118 380 0 30 Apr 2020
Deontological Ethics By Monotonicity Shape Constraints S. Wang Maya R. Gupta 69 21 0 31 Jan 2020
Kernel Dependence Regularizers and Gaussian Processes with Applications to Algorithmic Fairness Zhu Li Adrián Pérez-Suay Gustau Camps-Valls Dino Sejdinovic FaML 104 22 0 11 Nov 2019
Optimization Hierarchy for Fair Statistical Decision Problems A. Aswani Matt Olfat 58 3 0 18 Oct 2019
A Distributed Fair Machine Learning Framework with Private Demographic Data Protection Hui Hu Yijun Liu Zhen Wang Chao Lan FaML FedML 86 26 0 17 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
Fair Kernel Regression via Fair Feature Embedding in Kernel Space Austin Okray Hui Hu Chao Lan FaML 80 4 0 04 Jul 2019
Rényi Fair Inference Sina Baharlouei Maher Nouiehed Ahmad Beirami Meisam Razaviyayn FaML 66 67 0 28 Jun 2019
Pairwise Fairness for Ranking and Regression Harikrishna Narasimhan Andrew Cotter Maya R. Gupta S. Wang 98 115 0 12 Jun 2019
Fair Regression: Quantitative Definitions and Reduction-based Algorithms Alekh Agarwal Miroslav Dudík Zhiwei Steven Wu FaML 82 248 0 30 May 2019
Knowledge-Based Regularization in Generative Modeling Naoya Takeishi Yoshinobu Kawahara GAN 49 0 0 06 Feb 2019
General Fair Empirical Risk Minimization L. Oneto Michele Donini Massimiliano Pontil FaML 106 40 0 29 Jan 2019
Fairness risk measures Robert C. Williamson A. Menon FaML 163 142 0 24 Jan 2019
Taking Advantage of Multitask Learning for Fair Classification L. Oneto Michele Donini Amon Elders Massimiliano Pontil FaML 91 60 0 19 Oct 2018
Discovering Fair Representations in the Data Domain Novi Quadrianto V. Sharmanska Oliver Thomas 78 3 0 15 Oct 2018
Empirical Risk Minimization under Fairness Constraints Michele Donini L. Oneto Shai Ben-David John Shawe-Taylor Massimiliano Pontil FaML 86 445 0 23 Feb 2018