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Fair Kernel Learning

Fair Kernel Learning

16 October 2017
Adrián Pérez-Suay
Valero Laparra
Gonzalo Mateo-García
Jordi Munoz-Marí
L. Gómez-Chova
Gustau Camps-Valls
    FaML
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Papers citing "Fair Kernel Learning"

16 / 16 papers shown
Title
Intersectional Divergence: Measuring Fairness in Regression
Intersectional Divergence: Measuring Fairness in Regression
Joe Germino
Nuno Moniz
Nitesh V. Chawla
FaML
63
0
0
01 May 2025
A statistical approach to detect sensitive features in a group fairness
  setting
A statistical approach to detect sensitive features in a group fairness setting
G. D. Pelegrina
Miguel Couceiro
L. Duarte
6
3
0
11 May 2023
Returning The Favour: When Regression Benefits From Probabilistic Causal
  Knowledge
Returning The Favour: When Regression Benefits From Probabilistic Causal Knowledge
S. Bouabid
Jake Fawkes
Dino Sejdinovic
CML
36
0
0
26 Jan 2023
Fairness-aware Regression Robust to Adversarial Attacks
Fairness-aware Regression Robust to Adversarial Attacks
Yulu Jin
Lifeng Lai
FaML
OOD
16
4
0
04 Nov 2022
Fairness Reprogramming
Fairness Reprogramming
Guanhua Zhang
Yihua Zhang
Yang Zhang
Wenqi Fan
Qing Li
Sijia Liu
Shiyu Chang
AAML
80
38
0
21 Sep 2022
Error Parity Fairness: Testing for Group Fairness in Regression Tasks
Error Parity Fairness: Testing for Group Fairness in Regression Tasks
Furkan Gursoy
I. Kakadiaris
17
4
0
16 Aug 2022
Attainability and Optimality: The Equalized Odds Fairness Revisited
Attainability and Optimality: The Equalized Odds Fairness Revisited
Zeyu Tang
Kun Zhang
FaML
13
11
0
24 Feb 2022
Learning Fair Canonical Polyadical Decompositions using a Kernel
  Independence Criterion
Learning Fair Canonical Polyadical Decompositions using a Kernel Independence Criterion
Kevin Kim
Alex Gittens
11
1
0
27 Apr 2021
Towards a Collective Agenda on AI for Earth Science Data Analysis
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
39
68
0
11 Apr 2021
Review of Mathematical frameworks for Fairness in Machine Learning
Review of Mathematical frameworks for Fairness in Machine Learning
E. del Barrio
Paula Gordaliza
Jean-Michel Loubes
FaML
FedML
13
38
0
26 May 2020
Explainable Deep Learning: A Field Guide for the Uninitiated
Explainable Deep Learning: A Field Guide for the Uninitiated
Gabrielle Ras
Ning Xie
Marcel van Gerven
Derek Doran
AAML
XAI
29
371
0
30 Apr 2020
Fair Kernel Regression via Fair Feature Embedding in Kernel Space
Fair Kernel Regression via Fair Feature Embedding in Kernel Space
Austin Okray
Hui Hu
Chao Lan
FaML
14
4
0
04 Jul 2019
Pairwise Fairness for Ranking and Regression
Pairwise Fairness for Ranking and Regression
Harikrishna Narasimhan
Andrew Cotter
Maya R. Gupta
S. Wang
14
111
0
12 Jun 2019
Fair Regression: Quantitative Definitions and Reduction-based Algorithms
Fair Regression: Quantitative Definitions and Reduction-based Algorithms
Alekh Agarwal
Miroslav Dudík
Zhiwei Steven Wu
FaML
16
240
0
30 May 2019
Matching Code and Law: Achieving Algorithmic Fairness with Optimal
  Transport
Matching Code and Law: Achieving Algorithmic Fairness with Optimal Transport
Meike Zehlike
P. Hacker
Emil Wiedemann
13
19
0
21 Dec 2017
Fair prediction with disparate impact: A study of bias in recidivism
  prediction instruments
Fair prediction with disparate impact: A study of bias in recidivism prediction instruments
Alexandra Chouldechova
FaML
201
2,082
0
24 Oct 2016
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