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1905.12843
Cited By
Fair Regression: Quantitative Definitions and Reduction-based Algorithms
30 May 2019
Alekh Agarwal
Miroslav Dudík
Zhiwei Steven Wu
FaML
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Papers citing
"Fair Regression: Quantitative Definitions and Reduction-based Algorithms"
44 / 44 papers shown
Title
Fairness Perceptions in Regression-based Predictive Models
Mukund Telukunta
Venkata Sriram Siddhardh Nadendla
Morgan Stuart
Casey Canfield
43
0
0
08 May 2025
Machine Learning Fairness in House Price Prediction: A Case Study of America's Expanding Metropolises
Abdalwahab Almajed
Maryam Tabar
Peyman Najafirad
AI4TS
26
0
0
02 May 2025
Intersectional Divergence: Measuring Fairness in Regression
Joe Germino
Nuno Moniz
Nitesh V. Chawla
FaML
65
0
0
01 May 2025
ReLU integral probability metric and its applications
Yuha Park
Kunwoong Kim
Insung Kong
Yongdai Kim
48
0
0
26 Apr 2025
Discrimination-free Insurance Pricing with Privatized Sensitive Attributes
Tianhe Zhang
Suhan Liu
Peng Shi
FaML
69
0
0
16 Apr 2025
Oh the Prices You'll See: Designing a Fair Exchange System to Mitigate Personalized Pricing
Aditya Karan
Naina Balepur
Hari Sundaram
13
0
0
04 Sep 2024
Multi-Output Distributional Fairness via Post-Processing
Gang Li
Qihang Lin
Ayush Ghosh
Tianbao Yang
49
0
0
31 Aug 2024
On Fairness of Low-Rank Adaptation of Large Models
Zhoujie Ding
Ken Ziyu Liu
Pura Peetathawatchai
Berivan Isik
Sanmi Koyejo
48
4
0
27 May 2024
Fair Supervised Learning with A Simple Random Sampler of Sensitive Attributes
Jinwon Sohn
Qifan Song
Guang Lin
FaML
34
1
0
10 Nov 2023
A Trip Towards Fairness: Bias and De-Biasing in Large Language Models
Leonardo Ranaldi
Elena Sofia Ruzzetti
Davide Venditti
Dario Onorati
Fabio Massimo Zanzotto
27
33
0
23 May 2023
Improving Fairness in AI Models on Electronic Health Records: The Case for Federated Learning Methods
Raphael Poulain
Mirza Farhan Bin Tarek
Rahmatollah Beheshti
FedML
19
20
0
19 May 2023
Fairlearn: Assessing and Improving Fairness of AI Systems
Hilde Weerts
Miroslav Dudík
Richard Edgar
Adrin Jalali
Roman Lutz
Michael Madaio
FaML
16
63
0
29 Mar 2023
Beyond Accuracy: A Critical Review of Fairness in Machine Learning for Mobile and Wearable Computing
Sofia Yfantidou
Marios Constantinides
Dimitris Spathis
Athena Vakali
Daniele Quercia
F. Kawsar
HAI
FaML
26
18
0
27 Mar 2023
Robust probabilistic inference via a constrained transport metric
Abhisek Chakraborty
A. Bhattacharya
D. Pati
33
3
0
17 Mar 2023
Travel Demand Forecasting: A Fair AI Approach
Xiaojian Zhang
Qian Ke
Xilei Zhao
AI4TS
23
2
0
03 Mar 2023
Intersectional Fairness: A Fractal Approach
Giulio Filippi
Sara Zannone
Adriano Soares Koshiyama
8
1
0
24 Feb 2023
Fairguard: Harness Logic-based Fairness Rules in Smart Cities
Yiqi Zhao
Ziyan An
Xuqing Gao
Ayan Mukhopadhyay
Meiyi Ma
AI4TS
11
1
0
22 Feb 2023
Fairness-aware Regression Robust to Adversarial Attacks
Yulu Jin
Lifeng Lai
FaML
OOD
18
4
0
04 Nov 2022
Survey on Fairness Notions and Related Tensions
Guilherme Alves
Fabien Bernier
Miguel Couceiro
K. Makhlouf
C. Palamidessi
Sami Zhioua
FaML
31
24
0
16 Sep 2022
Algorithmic decision making methods for fair credit scoring
Darie Moldovan
FaML
30
7
0
16 Sep 2022
Adaptive Fairness Improvement Based on Causality Analysis
Mengdi Zhang
Jun Sun
19
31
0
15 Sep 2022
A Discussion of Discrimination and Fairness in Insurance Pricing
M. Lindholm
Ronald Richman
A. Tsanakas
M. Wüthrich
FaML
15
8
0
02 Sep 2022
Error Parity Fairness: Testing for Group Fairness in Regression Tasks
Furkan Gursoy
I. Kakadiaris
22
4
0
16 Aug 2022
Normalise for Fairness: A Simple Normalisation Technique for Fairness in Regression Machine Learning Problems
Mostafa M. Mohamed
Björn W. Schuller
11
5
0
02 Feb 2022
Towards Multi-Objective Statistically Fair Federated Learning
Ninareh Mehrabi
Cyprien de Lichy
John McKay
C. He
William Campbell
FedML
19
9
0
24 Jan 2022
Self-Paced Deep Regression Forests with Consideration of Ranking Fairness
Lili Pan
Mingming Meng
Yazhou Ren
Yali Zheng
Zenglin Xu
15
1
0
13 Dec 2021
Assessing Fairness in the Presence of Missing Data
Yiliang Zhang
Q. Long
FaML
26
35
0
07 Dec 2021
Modeling Techniques for Machine Learning Fairness: A Survey
Mingyang Wan
Daochen Zha
Ninghao Liu
Na Zou
SyDa
FaML
27
36
0
04 Nov 2021
Reliable and Trustworthy Machine Learning for Health Using Dataset Shift Detection
Chunjong Park
Anas Awadalla
Tadayoshi Kohno
Shwetak N. Patel
OOD
25
29
0
26 Oct 2021
Fairness guarantee in multi-class classification
Christophe Denis
Romuald Elie
Mohamed Hebiri
Franccois Hu
FaML
30
47
0
28 Sep 2021
Achieving Model Fairness in Vertical Federated Learning
Changxin Liu
Zhenan Fan
Zirui Zhou
Yang Shi
J. Pei
Lingyang Chu
Yong Zhang
FedML
58
12
0
17 Sep 2021
FairCanary: Rapid Continuous Explainable Fairness
Avijit Ghosh
Aalok Shanbhag
Christo Wilson
11
20
0
13 Jun 2021
Understanding and Mitigating Accuracy Disparity in Regression
Jianfeng Chi
Yuan Tian
Geoffrey J. Gordon
Han Zhao
16
25
0
24 Feb 2021
Exacerbating Algorithmic Bias through Fairness Attacks
Ninareh Mehrabi
Muhammad Naveed
Fred Morstatter
Aram Galstyan
AAML
23
67
0
16 Dec 2020
Grading video interviews with fairness considerations
A. Singhania
Abhishek Unnam
V. Aggarwal
25
6
0
02 Jul 2020
Fairness in Forecasting and Learning Linear Dynamical Systems
Quan-Gen Zhou
Jakub Mareˇcek
Robert Shorten
AI4TS
24
7
0
12 Jun 2020
Fair Bayesian Optimization
Valerio Perrone
Michele Donini
Muhammad Bilal Zafar
Robin Schmucker
K. Kenthapadi
Cédric Archambeau
FaML
16
83
0
09 Jun 2020
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
Statistical Equity: A Fairness Classification Objective
Ninareh Mehrabi
Yuzhong Huang
Fred Morstatter
FaML
14
10
0
14 May 2020
In Pursuit of Interpretable, Fair and Accurate Machine Learning for Criminal Recidivism Prediction
Caroline Linjun Wang
Bin Han
Bhrij Patel
Cynthia Rudin
FaML
HAI
59
84
0
08 May 2020
Algorithmic Fairness
Dana Pessach
E. Shmueli
FaML
27
387
0
21 Jan 2020
A Survey on Bias and Fairness in Machine Learning
Ninareh Mehrabi
Fred Morstatter
N. Saxena
Kristina Lerman
Aram Galstyan
SyDa
FaML
323
4,203
0
23 Aug 2019
Pairwise Fairness for Ranking and Regression
Harikrishna Narasimhan
Andrew Cotter
Maya R. Gupta
S. Wang
19
111
0
12 Jun 2019
Fair prediction with disparate impact: A study of bias in recidivism prediction instruments
Alexandra Chouldechova
FaML
207
2,082
0
24 Oct 2016
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