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Fair Generalized Linear Models with a Convex Penalty

Fair Generalized Linear Models with a Convex Penalty

18 June 2022
Hyungrok Do
Preston J. Putzel
Axel Martin
Padhraic Smyth
Judy Zhong
    FaML
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Papers citing "Fair Generalized Linear Models with a Convex Penalty"

14 / 14 papers shown
Title
Blackbox Post-Processing for Multiclass Fairness
Blackbox Post-Processing for Multiclass Fairness
Preston J. Putzel
Scott Lee
FaML
39
19
0
12 Jan 2022
Fairness guarantee in multi-class classification
Fairness guarantee in multi-class classification
Christophe Denis
Romuald Elie
Mohamed Hebiri
Franccois Hu
FaML
104
49
0
28 Sep 2021
Unbiased Subdata Selection for Fair Classification: A Unified Framework
  and Scalable Algorithms
Unbiased Subdata Selection for Fair Classification: A Unified Framework and Scalable Algorithms
Qing Ye
Weijun Xie
FaML
54
13
0
22 Dec 2020
CheXclusion: Fairness gaps in deep chest X-ray classifiers
CheXclusion: Fairness gaps in deep chest X-ray classifiers
Laleh Seyyed-Kalantari
Guanxiong Liu
Matthew B. A. McDermott
Irene Y. Chen
Marzyeh Ghassemi
OOD
83
291
0
14 Feb 2020
Fair Regression: Quantitative Definitions and Reduction-based Algorithms
Fair Regression: Quantitative Definitions and Reduction-based Algorithms
Alekh Agarwal
Miroslav Dudík
Zhiwei Steven Wu
FaML
44
247
0
30 May 2019
General Fair Empirical Risk Minimization
General Fair Empirical Risk Minimization
L. Oneto
Michele Donini
Massimiliano Pontil
FaML
57
38
0
29 Jan 2019
iFair: Learning Individually Fair Data Representations for Algorithmic
  Decision Making
iFair: Learning Individually Fair Data Representations for Algorithmic Decision Making
Preethi Lahoti
Krishna P. Gummadi
Gerhard Weikum
FaML
64
170
0
04 Jun 2018
A Reductions Approach to Fair Classification
A Reductions Approach to Fair Classification
Alekh Agarwal
A. Beygelzimer
Miroslav Dudík
John Langford
Hanna M. Wallach
FaML
203
1,099
0
06 Mar 2018
Empirical Risk Minimization under Fairness Constraints
Empirical Risk Minimization under Fairness Constraints
Michele Donini
L. Oneto
Shai Ben-David
John Shawe-Taylor
Massimiliano Pontil
FaML
76
444
0
23 Feb 2018
Fair Kernel Learning
Fair Kernel Learning
Adrián Pérez-Suay
Valero Laparra
Gonzalo Mateo-García
Jordi Munoz-Marí
L. Gómez-Chova
Gustau Camps-Valls
FaML
57
84
0
16 Oct 2017
A Convex Framework for Fair Regression
A Convex Framework for Fair Regression
R. Berk
Hoda Heidari
S. Jabbari
Matthew Joseph
Michael Kearns
Jamie Morgenstern
Seth Neel
Aaron Roth
FaML
107
342
0
07 Jun 2017
Fairness Beyond Disparate Treatment & Disparate Impact: Learning
  Classification without Disparate Mistreatment
Fairness Beyond Disparate Treatment & Disparate Impact: Learning Classification without Disparate Mistreatment
Muhammad Bilal Zafar
Isabel Valera
Manuel Gomez Rodriguez
Krishna P. Gummadi
FaML
169
1,205
0
26 Oct 2016
Equality of Opportunity in Supervised Learning
Equality of Opportunity in Supervised Learning
Moritz Hardt
Eric Price
Nathan Srebro
FaML
196
4,301
0
07 Oct 2016
Fast and Simple Optimization for Poisson Likelihood Models
Fast and Simple Optimization for Poisson Likelihood Models
Niao He
Zaïd Harchaoui
Yichen Wang
Le Song
93
14
0
03 Aug 2016
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