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Improving Fairness with Ensemble Combination: Margin-Dependent Bounds
v1v2v3v4v5 (latest)

Improving Fairness with Ensemble Combination: Margin-Dependent Bounds

25 January 2023
Yijun Bian
    FaML
ArXiv (abs)PDFHTMLGithub

Papers citing "Improving Fairness with Ensemble Combination: Margin-Dependent Bounds"

28 / 28 papers shown
FairSHAP: Preprocessing for Fairness Through Attribution-Based Data Augmentation
FairSHAP: Preprocessing for Fairness Through Attribution-Based Data Augmentation
Lin Zhu
Yijun Bian
Lei You
TDI
650
1
0
16 May 2025
Does Machine Bring in Extra Bias in Learning? Approximating Fairness in
  Models Promptly
Does Machine Bring in Extra Bias in Learning? Approximating Fairness in Models Promptly
Yijun Bian
Yujie Luo
FaML
236
2
0
15 May 2024
FairGBM: Gradient Boosting with Fairness Constraints
FairGBM: Gradient Boosting with Fairness ConstraintsInternational Conference on Learning Representations (ICLR), 2022
André F. Cruz
Catarina Belém
Sérgio Jesus
Joao Bravo
Pedro Saleiro
P. Bizarro
422
33
0
16 Sep 2022
Causal Conceptions of Fairness and their Consequences
Causal Conceptions of Fairness and their ConsequencesInternational Conference on Machine Learning (ICML), 2022
H. Nilforoshan
Johann D. Gaebler
Ravi Shroff
Sharad Goel
FaML
331
52
0
12 Jul 2022
FARF: A Fair and Adaptive Random Forests Classifier
FARF: A Fair and Adaptive Random Forests Classifier
Wenbin Zhang
Nikolaos Perrakis
Xiangliang Zhang
Jeremy C. Weiss
Wolfgang Nejdl
FaML
297
64
0
17 Aug 2021
Second Order PAC-Bayesian Bounds for the Weighted Majority Vote
Second Order PAC-Bayesian Bounds for the Weighted Majority Vote
A. Masegosa
S. Lorenzen
Christian Igel
Yevgeny Seldin
437
45
0
01 Jul 2020
AdaFair: Cumulative Fairness Adaptive Boosting
AdaFair: Cumulative Fairness Adaptive BoostingInternational Conference on Information and Knowledge Management (CIKM), 2019
Vasileios Iosifidis
Eirini Ntoutsi
FaML
165
93
0
17 Sep 2019
Fair Regression: Quantitative Definitions and Reduction-based Algorithms
Fair Regression: Quantitative Definitions and Reduction-based AlgorithmsInternational Conference on Machine Learning (ICML), 2019
Alekh Agarwal
Miroslav Dudík
Zhiwei Steven Wu
FaML
358
297
0
30 May 2019
Scalable Fair Clustering
Scalable Fair ClusteringInternational Conference on Machine Learning (ICML), 2019
A. Backurs
Piotr Indyk
Krzysztof Onak
B. Schieber
A. Vakilian
Tal Wagner
348
225
0
10 Feb 2019
A Primer on PAC-Bayesian Learning
A Primer on PAC-Bayesian Learning
Benjamin Guedj
694
234
0
16 Jan 2019
The Price of Fair PCA: One Extra Dimension
The Price of Fair PCA: One Extra Dimension
Samira Samadi
U. Tantipongpipat
Jamie Morgenstern
Mohit Singh
Santosh Vempala
FaML
501
179
0
31 Oct 2018
Fairness Under Composition
Fairness Under Composition
Cynthia Dwork
Christina Ilvento
FaML
327
133
0
15 Jun 2018
Ensemble Pruning based on Objection Maximization with a General
  Distributed Framework
Ensemble Pruning based on Objection Maximization with a General Distributed Framework
Yijun Bian
Yijun Wang
Yaqiang Yao
Huanhuan Chen
262
47
0
13 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
875
1,238
0
06 Mar 2018
Fair Clustering Through Fairlets
Fair Clustering Through Fairlets
Flavio Chierichetti
Ravi Kumar
Silvio Lattanzi
Sergei Vassilvitskii
FaML
421
510
0
15 Feb 2018
A comparative study of fairness-enhancing interventions in machine
  learning
A comparative study of fairness-enhancing interventions in machine learning
Sorelle A. Friedler
C. Scheidegger
Suresh Venkatasubramanian
Sonam Choudhary
Evan P. Hamilton
Derek Roth
FaML
407
718
0
13 Feb 2018
On Formalizing Fairness in Prediction with Machine Learning
On Formalizing Fairness in Prediction with Machine Learning
Pratik Gajane
Mykola Pechenizkiy
FaML
518
223
0
09 Oct 2017
On Fairness and Calibration
On Fairness and Calibration
Geoff Pleiss
Manish Raghavan
Felix Wu
Jon M. Kleinberg
Kilian Q. Weinberger
FaML
553
972
0
06 Sep 2017
Avoiding Discrimination through Causal Reasoning
Avoiding Discrimination through Causal ReasoningNeural Information Processing Systems (NeurIPS), 2017
Niki Kilbertus
Mateo Rojas-Carulla
Giambattista Parascandolo
Moritz Hardt
Dominik Janzing
Bernhard Schölkopf
FaMLCML
494
627
0
08 Jun 2017
Fairness in Criminal Justice Risk Assessments: The State of the Art
Fairness in Criminal Justice Risk Assessments: The State of the Art
R. Berk
Hoda Heidari
S. Jabbari
Michael Kearns
Aaron Roth
370
1,102
0
27 Mar 2017
Counterfactual Fairness
Counterfactual Fairness
Matt J. Kusner
Joshua R. Loftus
Chris Russell
Ricardo M. A. Silva
FaML
977
1,822
0
20 Mar 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
606
1,301
0
26 Oct 2016
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
1.0K
2,357
0
24 Oct 2016
Equality of Opportunity in Supervised Learning
Equality of Opportunity in Supervised LearningNeural Information Processing Systems (NeurIPS), 2016
Moritz Hardt
Eric Price
Nathan Srebro
FaML
544
4,996
0
07 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
1.0K
1,982
0
19 Sep 2016
Fairness in Learning: Classic and Contextual Bandits
Fairness in Learning: Classic and Contextual Bandits
Matthew Joseph
Michael Kearns
Jamie Morgenstern
Aaron Roth
FaML
408
503
0
23 May 2016
The Variational Fair Autoencoder
The Variational Fair Autoencoder
Christos Louizos
Kevin Swersky
Yujia Li
Max Welling
R. Zemel
DRL
1.0K
668
0
03 Nov 2015
Certifying and removing disparate impact
Certifying and removing disparate impactKnowledge Discovery and Data Mining (KDD), 2014
Michael Feldman
Sorelle A. Friedler
John Moeller
C. Scheidegger
Suresh Venkatasubramanian
FaML
938
2,204
0
11 Dec 2014
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