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Fairness Constraints: Mechanisms for Fair Classification
v1v2v3v4v5 (latest)

Fairness Constraints: Mechanisms for Fair Classification

19 July 2015
Muhammad Bilal Zafar
Isabel Valera
Manuel Gomez Rodriguez
Krishna P. Gummadi
    FaML
ArXiv (abs)PDFHTML

Papers citing "Fairness Constraints: Mechanisms for Fair Classification"

24 / 24 papers shown
Title
On Prediction-Modelers and Decision-Makers: Why Fairness Requires More
  Than a Fair Prediction Model
On Prediction-Modelers and Decision-Makers: Why Fairness Requires More Than a Fair Prediction Model
Teresa Scantamburlo
Joachim Baumann
Christoph Heitz
FaML
93
8
0
09 Oct 2023
COFFEE: Counterfactual Fairness for Personalized Text Generation in
  Explainable Recommendation
COFFEE: Counterfactual Fairness for Personalized Text Generation in Explainable Recommendation
Nan Wang
Qifan Wang
Yi-Chia Wang
Maziar Sanjabi
Jingzhou Liu
Hamed Firooz
Hongning Wang
Shaoliang Nie
137
6
0
14 Oct 2022
Counterfactual Fairness Is Basically Demographic Parity
Counterfactual Fairness Is Basically Demographic Parity
Lucas Rosenblatt
R. T. Witter
119
19
0
07 Aug 2022
Are Gender-Neutral Queries Really Gender-Neutral? Mitigating Gender Bias
  in Image Search
Are Gender-Neutral Queries Really Gender-Neutral? Mitigating Gender Bias in Image Search
Jialu Wang
Yang Liu
Xinze Wang
FaML
234
102
0
12 Sep 2021
Exacerbating Algorithmic Bias through Fairness Attacks
Exacerbating Algorithmic Bias through Fairness Attacks
Ninareh Mehrabi
Muhammad Naveed
Fred Morstatter
Aram Galstyan
AAML
101
70
0
16 Dec 2020
Fair Active Learning
Fair Active Learning
Hadis Anahideh
Abolfazl Asudeh
Saravanan Thirumuruganathan
FaML
302
56
0
06 Jan 2020
Practical Compositional Fairness: Understanding Fairness in
  Multi-Component Recommender Systems
Practical Compositional Fairness: Understanding Fairness in Multi-Component Recommender Systems
Xuezhi Wang
Nithum Thain
Anu Sinha
Flavien Prost
Ed H. Chi
Jilin Chen
Alex Beutel
FaMLCoGe
91
1
0
05 Nov 2019
Does Object Recognition Work for Everyone?
Does Object Recognition Work for Everyone?
Terrance Devries
Ishan Misra
Changhan Wang
Laurens van der Maaten
164
269
0
06 Jun 2019
Fairness risk measures
Fairness risk measures
Robert C. Williamson
A. Menon
FaML
272
142
0
24 Jan 2019
Learning Controllable Fair Representations
Learning Controllable Fair Representations
Jiaming Song
Pratyusha Kalluri
Aditya Grover
Shengjia Zhao
Stefano Ermon
FaML
148
181
0
11 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
193
344
0
14 Nov 2018
On preserving non-discrimination when combining expert advice
On preserving non-discrimination when combining expert advice
Avrim Blum
Suriya Gunasekar
Thodoris Lykouris
Nathan Srebro
FaML
74
30
0
28 Oct 2018
Active Fairness in Algorithmic Decision Making
Active Fairness in Algorithmic Decision Making
Alejandro Noriega-Campero
Michiel A. Bakker
Bernardo Garcia-Bulle
Alex Pentland
FaML
109
87
0
28 Sep 2018
Evaluating Fairness Metrics in the Presence of Dataset Bias
Evaluating Fairness Metrics in the Presence of Dataset Bias
J. Hinnefeld
Peter Cooman
Nat Mammo
Rupert Deese
FaML
66
37
0
24 Sep 2018
Hierarchical VampPrior Variational Fair Auto-Encoder
Hierarchical VampPrior Variational Fair Auto-Encoder
P. Botros
Jakub M. Tomczak
DRL
84
7
0
26 Jun 2018
Fairness Testing: Testing Software for Discrimination
Fairness Testing: Testing Software for Discrimination
Sainyam Galhotra
Yuriy Brun
A. Meliou
147
392
0
11 Sep 2017
On Fairness and Calibration
On Fairness and Calibration
Geoff Pleiss
Manish Raghavan
Felix Wu
Jon M. Kleinberg
Kilian Q. Weinberger
FaML
277
906
0
06 Sep 2017
Counterfactual Fairness
Counterfactual Fairness
Matt J. Kusner
Joshua R. Loftus
Chris Russell
Ricardo M. A. Silva
FaML
319
1,630
0
20 Mar 2017
Learning to Pivot with Adversarial Networks
Learning to Pivot with Adversarial Networks
Gilles Louppe
Michael Kagan
Kyle Cranmer
156
231
0
03 Nov 2016
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
326
1,234
0
26 Oct 2016
Equality of Opportunity in Supervised Learning
Equality of Opportunity in Supervised Learning
Moritz Hardt
Eric Price
Nathan Srebro
FaML
262
4,479
0
07 Oct 2016
Learning Optimized Risk Scores
Learning Optimized Risk Scores
Berk Ustun
Cynthia Rudin
374
90
0
01 Oct 2016
Inherent Trade-Offs in the Fair Determination of Risk Scores
Inherent Trade-Offs in the Fair Determination of Risk Scores
Jon M. Kleinberg
S. Mullainathan
Manish Raghavan
FaML
472
1,819
0
19 Sep 2016
Concrete Problems in AI Safety
Concrete Problems in AI Safety
Dario Amodei
C. Olah
Jacob Steinhardt
Paul Christiano
John Schulman
Dandelion Mané
518
2,507
0
21 Jun 2016
1