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. 1803.02453
  4. Cited By
A Reductions Approach to Fair Classification

A Reductions Approach to Fair Classification

6 March 2018
Alekh Agarwal
A. Beygelzimer
Miroslav Dudík
John Langford
Hanna M. Wallach
    FaML
ArXivPDFHTML

Papers citing "A Reductions Approach to Fair Classification"

24 / 24 papers shown
Title
Fairness Practices in Industry: A Case Study in Machine Learning Teams Building Recommender Systems
Fairness Practices in Industry: A Case Study in Machine Learning Teams Building Recommender Systems
Jing Nathan Yan
Junxiong Wang
Jeffrey M. Rzeszotarski
Allison Koenecke
FaML
51
0
0
26 May 2025
Liouville PDE-based sliced-Wasserstein flow for fair regression
Liouville PDE-based sliced-Wasserstein flow for fair regression
Pilhwa Lee
Jayshawn Cooper
50
0
0
22 May 2025
Enforcing Fairness Where It Matters: An Approach Based on Difference-of-Convex Constraints
Enforcing Fairness Where It Matters: An Approach Based on Difference-of-Convex Constraints
Yutian He
Yankun Huang
Yao Yao
Qihang Lin
FaML
47
0
0
18 May 2025
Fair Representation Learning for Continuous Sensitive Attributes using Expectation of Integral Probability Metrics
Fair Representation Learning for Continuous Sensitive Attributes using Expectation of Integral Probability Metrics
Insung Kong
Kunwoong Kim
Yongdai Kim
FaML
123
1
0
09 May 2025
Whence Is A Model Fair? Fixing Fairness Bugs via Propensity Score Matching
Whence Is A Model Fair? Fixing Fairness Bugs via Propensity Score Matching
Kewen Peng
Yicheng Yang
Hao Zhuo
83
0
0
23 Apr 2025
FaiREE: Fair Classification with Finite-Sample and Distribution-Free Guarantee
FaiREE: Fair Classification with Finite-Sample and Distribution-Free Guarantee
Puheng Li
James Zou
Linjun Zhang
FaML
336
4
0
13 Mar 2025
Enhancing Robust Fairness via Confusional Spectral Regularization
Enhancing Robust Fairness via Confusional Spectral Regularization
Gaojie Jin
Sihao Wu
Jiaxu Liu
Tianjin Huang
Ronghui Mu
154
1
0
22 Jan 2025
Fair Class-Incremental Learning using Sample Weighting
Fair Class-Incremental Learning using Sample Weighting
Jaeyoung Park
Minsu Kim
Steven Euijong Whang
65
0
0
02 Oct 2024
Oh the Prices You'll See: Designing a Fair Exchange System to Mitigate Personalized Pricing
Oh the Prices You'll See: Designing a Fair Exchange System to Mitigate Personalized Pricing
Aditya Karan
Naina Balepur
Hari Sundaram
57
0
0
04 Sep 2024
Multi-Output Distributional Fairness via Post-Processing
Multi-Output Distributional Fairness via Post-Processing
Gang Li
Qihang Lin
Ayush Ghosh
Tianbao Yang
108
0
0
31 Aug 2024
Balanced Mixed-Type Tabular Data Synthesis with Diffusion Models
Balanced Mixed-Type Tabular Data Synthesis with Diffusion Models
Zeyu Yang
Peikun Guo
Khadija Zanna
Akane Sano
Xiaoxue Yang
Akane Sano
DiffM
80
9
0
12 Apr 2024
Increasing Fairness via Combination with Learning Guarantees
Increasing Fairness via Combination with Learning Guarantees
Yijun Bian
Kun Zhang
FaML
88
2
0
25 Jan 2023
Efficient Fair Principal Component Analysis
Efficient Fair Principal Component Analysis
Mohammad Mahdi Kamani
Farzin Haddadpour
R. Forsati
M. Mahdavi
58
36
0
12 Nov 2019
What is Fair? Exploring Pareto-Efficiency for Fairness Constrained
  Classifiers
What is Fair? Exploring Pareto-Efficiency for Fairness Constrained Classifiers
Ananth Balashankar
Alyssa Lees
Chris Welty
L. Subramanian
51
21
0
30 Oct 2019
Unleashing Linear Optimizers for Group-Fair Learning and Optimization
Unleashing Linear Optimizers for Group-Fair Learning and Optimization
Daniel Alabi
Nicole Immorlica
Adam Tauman Kalai
FedML
FaML
39
27
0
11 Apr 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
443
0
23 Feb 2018
Preventing Fairness Gerrymandering: Auditing and Learning for Subgroup
  Fairness
Preventing Fairness Gerrymandering: Auditing and Learning for Subgroup Fairness
Michael Kearns
Seth Neel
Aaron Roth
Zhiwei Steven Wu
FaML
124
775
0
14 Nov 2017
Decoupled classifiers for fair and efficient machine learning
Decoupled classifiers for fair and efficient machine learning
Cynthia Dwork
Nicole Immorlica
Adam Tauman Kalai
Max D. M. Leiserson
FaML
58
43
0
20 Jul 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
49
990
0
27 Mar 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
293
2,098
0
24 Oct 2016
Equality of Opportunity in Supervised Learning
Equality of Opportunity in Supervised Learning
Moritz Hardt
Eric Price
Nathan Srebro
FaML
139
4,276
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
94
1,762
0
19 Sep 2016
Learning Reductions that Really Work
Learning Reductions that Really Work
A. Beygelzimer
Hal Daumé
John Langford
Paul Mineiro
AI4CE
57
24
0
09 Feb 2015
Certifying and removing disparate impact
Certifying and removing disparate impact
Michael Feldman
Sorelle A. Friedler
John Moeller
C. Scheidegger
Suresh Venkatasubramanian
FaML
153
1,978
0
11 Dec 2014
1