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From Parity to Preference-based Notions of Fairness in Classification

From Parity to Preference-based Notions of Fairness in Classification

30 June 2017
Muhammad Bilal Zafar
Isabel Valera
Manuel Gomez Rodriguez
Krishna P. Gummadi
Adrian Weller
    FaML
ArXivPDFHTML

Papers citing "From Parity to Preference-based Notions of Fairness in Classification"

27 / 27 papers shown
Title
Participatory Personalization in Classification
Participatory Personalization in Classification
Hailey J James
Chirag Nagpal
Katherine A. Heller
Berk Ustun
39
4
0
08 Feb 2023
FairRoad: Achieving Fairness for Recommender Systems with Optimized
  Antidote Data
FairRoad: Achieving Fairness for Recommender Systems with Optimized Antidote Data
Minghong Fang
Jia-Wei Liu
Michinari Momma
Yi Sun
30
4
0
13 Dec 2022
Efficient Classification with Counterfactual Reasoning and Active
  Learning
Efficient Classification with Counterfactual Reasoning and Active Learning
A. Mohammed
D. Nguyen
Bao Duong
T. Nguyen
CML
30
0
0
25 Jul 2022
Causal Conceptions of Fairness and their Consequences
Causal Conceptions of Fairness and their Consequences
H. Nilforoshan
Johann D. Gaebler
Ravi Shroff
Sharad Goel
FaML
134
45
0
12 Jul 2022
When Personalization Harms: Reconsidering the Use of Group Attributes in
  Prediction
When Personalization Harms: Reconsidering the Use of Group Attributes in Prediction
Vinith M. Suriyakumar
Marzyeh Ghassemi
Berk Ustun
35
6
0
04 Jun 2022
Marrying Fairness and Explainability in Supervised Learning
Marrying Fairness and Explainability in Supervised Learning
Przemyslaw A. Grabowicz
Nicholas Perello
Aarshee Mishra
FaML
46
43
0
06 Apr 2022
On Learning and Enforcing Latent Assessment Models using Binary Feedback
  from Human Auditors Regarding Black-Box Classifiers
On Learning and Enforcing Latent Assessment Models using Binary Feedback from Human Auditors Regarding Black-Box Classifiers
Mukund Telukunta
Venkata Sriram Siddhardh Nadendla
MLAU
FaML
20
0
0
16 Feb 2022
FairEdit: Preserving Fairness in Graph Neural Networks through Greedy
  Graph Editing
FairEdit: Preserving Fairness in Graph Neural Networks through Greedy Graph Editing
Donald Loveland
Jiayi Pan
A. Bhathena
Yiyang Lu
13
16
0
10 Jan 2022
Improving Fairness via Federated Learning
Improving Fairness via Federated Learning
Yuchen Zeng
Hongxu Chen
Kangwook Lee
FedML
19
60
0
29 Oct 2021
Fairness without Imputation: A Decision Tree Approach for Fair
  Prediction with Missing Values
Fairness without Imputation: A Decision Tree Approach for Fair Prediction with Missing Values
Haewon Jeong
Hao Wang
Flavio du Pin Calmon
FaML
51
33
0
21 Sep 2021
Towards a Unified Framework for Fair and Stable Graph Representation
  Learning
Towards a Unified Framework for Fair and Stable Graph Representation Learning
Chirag Agarwal
Himabindu Lakkaraju
Marinka Zitnik
27
156
0
25 Feb 2021
Fair for All: Best-effort Fairness Guarantees for Classification
Fair for All: Best-effort Fairness Guarantees for Classification
A. Krishnaswamy
Zhihao Jiang
Kangning Wang
Yu Cheng
Kamesh Munagala
FaML
12
10
0
18 Dec 2020
Minimax Pareto Fairness: A Multi Objective Perspective
Minimax Pareto Fairness: A Multi Objective Perspective
Natalia Martínez
Martín Bertrán
Guillermo Sapiro
FaML
11
189
0
03 Nov 2020
Getting a CLUE: A Method for Explaining Uncertainty Estimates
Getting a CLUE: A Method for Explaining Uncertainty Estimates
Javier Antorán
Umang Bhatt
T. Adel
Adrian Weller
José Miguel Hernández-Lobato
UQCV
BDL
40
111
0
11 Jun 2020
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
15
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
38
370
0
30 Apr 2020
Fairness With Minimal Harm: A Pareto-Optimal Approach For Healthcare
Fairness With Minimal Harm: A Pareto-Optimal Approach For Healthcare
Natalia Martínez
Martín Bertrán
Guillermo Sapiro
11
25
0
16 Nov 2019
Fair Adversarial Gradient Tree Boosting
Fair Adversarial Gradient Tree Boosting
Vincent Grari
Boris Ruf
Sylvain Lamprier
Marcin Detyniecki
FaML
19
33
0
13 Nov 2019
Efficient Fair Principal Component Analysis
Efficient Fair Principal Component Analysis
Mohammad Mahdi Kamani
Farzin Haddadpour
R. Forsati
M. Mahdavi
11
36
0
12 Nov 2019
Fairness Violations and Mitigation under Covariate Shift
Fairness Violations and Mitigation under Covariate Shift
Harvineet Singh
Rina Singh
Vishwali Mhasawade
R. Chunara
OOD
11
15
0
02 Nov 2019
ProPublica's COMPAS Data Revisited
ProPublica's COMPAS Data Revisited
M. Barenstein
FaML
14
50
0
11 Jun 2019
The invisible power of fairness. How machine learning shapes democracy
The invisible power of fairness. How machine learning shapes democracy
E. Beretta
A. Santangelo
Bruno Lepri
A. Vetrò
Juan Carlos De Martin
FaML
13
6
0
22 Mar 2019
Towards Robust Interpretability with Self-Explaining Neural Networks
Towards Robust Interpretability with Self-Explaining Neural Networks
David Alvarez-Melis
Tommi Jaakkola
MILM
XAI
35
933
0
20 Jun 2018
Classification with Fairness Constraints: A Meta-Algorithm with Provable
  Guarantees
Classification with Fairness Constraints: A Meta-Algorithm with Provable Guarantees
L. E. Celis
Lingxiao Huang
Vijay Keswani
Nisheeth K. Vishnoi
FaML
57
301
0
15 Jun 2018
Fairness Behind a Veil of Ignorance: A Welfare Analysis for Automated
  Decision Making
Fairness Behind a Veil of Ignorance: A Welfare Analysis for Automated Decision Making
Hoda Heidari
Claudio Ferrari
Krishna P. Gummadi
Andreas Krause
18
129
0
13 Jun 2018
Fairness GAN
Fairness GAN
P. Sattigeri
Samuel C. Hoffman
Vijil Chenthamarakshan
Kush R. Varshney
18
93
0
24 May 2018
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
207
2,087
0
24 Oct 2016
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