ResearchTrend.AI
  • Papers
  • Communities
  • Events
  • Blog
  • Pricing
Papers
Communities
Social Events
Terms and Conditions
Pricing
Parameter LabParameter LabTwitterGitHubLinkedInBlueskyYoutube

© 2025 ResearchTrend.AI, All rights reserved.

  1. Home
  2. Papers
  3. 1707.00010
  4. Cited By
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"

46 / 46 papers shown
Title
Fairness-aware Anomaly Detection via Fair Projection
Fairness-aware Anomaly Detection via Fair Projection
Feng Xiao
Xiaoying Tang
Jicong Fan
37
0
0
16 May 2025
Striking a Balance in Fairness for Dynamic Systems Through Reinforcement
  Learning
Striking a Balance in Fairness for Dynamic Systems Through Reinforcement Learning
Yaowei Hu
Jacob Lear
Lu Zhang
FaML
29
2
0
12 Jan 2024
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
38
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
142
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 Suriyakumar
Marzyeh Ghassemi
Berk Ustun
44
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
51
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
Adaptive Sampling Strategies to Construct Equitable Training Datasets
Adaptive Sampling Strategies to Construct Equitable Training Datasets
William Cai
R. Encarnación
Bobbie Chern
S. Corbett-Davies
Miranda Bogen
Stevie Bergman
Sharad Goel
89
30
0
31 Jan 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
24
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
157
0
25 Feb 2021
Through the Data Management Lens: Experimental Analysis and Evaluation
  of Fair Classification
Through the Data Management Lens: Experimental Analysis and Evaluation of Fair Classification
Maliha Tashfia Islam
Anna Fariha
A. Meliou
Babak Salimi
FaML
30
25
0
18 Jan 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
20
10
0
18 Dec 2020
WILDS: A Benchmark of in-the-Wild Distribution Shifts
WILDS: A Benchmark of in-the-Wild Distribution Shifts
Pang Wei Koh
Shiori Sagawa
Henrik Marklund
Sang Michael Xie
Marvin Zhang
...
A. Kundaje
Emma Pierson
Sergey Levine
Chelsea Finn
Percy Liang
OOD
108
1,386
0
14 Dec 2020
Minimax Pareto Fairness: A Multi Objective Perspective
Minimax Pareto Fairness: A Multi Objective Perspective
Natalia Martínez
Martín Bertrán
Guillermo Sapiro
FaML
25
190
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
52
112
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
39
0
26 May 2020
Ethical Adversaries: Towards Mitigating Unfairness with Adversarial
  Machine Learning
Ethical Adversaries: Towards Mitigating Unfairness with Adversarial Machine Learning
Pieter Delobelle
Paul Temple
Gilles Perrouin
Benoit Frénay
P. Heymans
Bettina Berendt
AAML
FaML
27
14
0
14 May 2020
Ensuring Fairness under Prior Probability Shifts
Ensuring Fairness under Prior Probability Shifts
Arpita Biswas
Suvam Mukherjee
OOD
24
33
0
06 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
52
371
0
30 Apr 2020
Fairness by Explicability and Adversarial SHAP Learning
Fairness by Explicability and Adversarial SHAP Learning
James M. Hickey
Pietro G. Di Stefano
V. Vasileiou
FAtt
FedML
33
19
0
11 Mar 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
19
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
13
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
27
15
0
02 Nov 2019
Avoiding Resentment Via Monotonic Fairness
Avoiding Resentment Via Monotonic Fairness
G. W. Cole
Sinead Williamson
FaML
27
7
0
03 Sep 2019
Operationalizing Individual Fairness with Pairwise Fair Representations
Operationalizing Individual Fairness with Pairwise Fair Representations
Preethi Lahoti
Krishna P. Gummadi
Gerhard Weikum
FaML
38
101
0
02 Jul 2019
ProPublica's COMPAS Data Revisited
ProPublica's COMPAS Data Revisited
M. Barenstein
FaML
14
50
0
11 Jun 2019
Fairness and Missing Values
Fairness and Missing Values
Fernando Martínez-Plumed
Cesar Ferri
David Nieves
José Hernández-Orallo
24
28
0
29 May 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
21
6
0
22 Mar 2019
Repairing without Retraining: Avoiding Disparate Impact with
  Counterfactual Distributions
Repairing without Retraining: Avoiding Disparate Impact with Counterfactual Distributions
Hao Wang
Berk Ustun
Flavio du Pin Calmon
FaML
36
83
0
29 Jan 2019
Fairness risk measures
Fairness risk measures
Robert C. Williamson
A. Menon
FaML
36
135
0
24 Jan 2019
NIPS - Not Even Wrong? A Systematic Review of Empirically Complete
  Demonstrations of Algorithmic Effectiveness in the Machine Learning and
  Artificial Intelligence Literature
NIPS - Not Even Wrong? A Systematic Review of Empirically Complete Demonstrations of Algorithmic Effectiveness in the Machine Learning and Artificial Intelligence Literature
Franz J. Király
Bilal A. Mateen
R. Sonabend
23
10
0
18 Dec 2018
Aequitas: A Bias and Fairness Audit Toolkit
Aequitas: A Bias and Fairness Audit Toolkit
Pedro Saleiro
Benedict Kuester
Loren Hinkson
J. London
Abby Stevens
Ari Anisfeld
Kit T. Rodolfa
Rayid Ghani
51
318
0
14 Nov 2018
A General Framework for Fair Regression
A General Framework for Fair Regression
Jack K. Fitzsimons
AbdulRahman Al Ali
Michael A. Osborne
Stephen J. Roberts
FaML
30
37
0
10 Oct 2018
Towards Robust Interpretability with Self-Explaining Neural Networks
Towards Robust Interpretability with Self-Explaining Neural Networks
David Alvarez-Melis
Tommi Jaakkola
MILM
XAI
56
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
66
302
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
20
128
0
13 Jun 2018
Blind Justice: Fairness with Encrypted Sensitive Attributes
Blind Justice: Fairness with Encrypted Sensitive Attributes
Niki Kilbertus
Adria Gascon
Matt J. Kusner
Michael Veale
Krishna P. Gummadi
Adrian Weller
28
149
0
08 Jun 2018
Fairness GAN
Fairness GAN
P. Sattigeri
Samuel C. Hoffman
Vijil Chenthamarakshan
Kush R. Varshney
18
93
0
24 May 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
38
439
0
23 Feb 2018
Does mitigating ML's impact disparity require treatment disparity?
Does mitigating ML's impact disparity require treatment disparity?
Zachary Chase Lipton
Alexandra Chouldechova
Julian McAuley
37
16
0
19 Nov 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
207
2,092
0
24 Oct 2016
1