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1910.12586
Cited By
PC-Fairness: A Unified Framework for Measuring Causality-based Fairness
20 October 2019
Yongkai Wu
Lu Zhang
Xintao Wu
Hanghang Tong
FaML
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Papers citing
"PC-Fairness: A Unified Framework for Measuring Causality-based Fairness"
23 / 23 papers shown
Title
Causality Is Key to Understand and Balance Multiple Goals in Trustworthy ML and Foundation Models
Ruta Binkyte
Ivaxi Sheth
Zhijing Jin
Mohammad Havaei
Bernhard Schölkopf
Mario Fritz
233
0
0
28 Feb 2025
Fair Clustering: A Causal Perspective
Fritz M. Bayer
Drago Plečko
N. Beerenwinkel
Jack Kuipers
FaML
27
0
0
14 Dec 2023
Unfair Utilities and First Steps Towards Improving Them
Frederik Hytting Jorgensen
S. Weichwald
J. Peters
FaML
61
0
0
01 Jun 2023
Causal Deep Learning
Jeroen Berrevoets
Krzysztof Kacprzyk
Zhaozhi Qian
M. Schaar
CML
AI4CE
21
25
0
03 Mar 2023
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
33
6
0
14 Oct 2022
SCALES: From Fairness Principles to Constrained Decision-Making
Sreejith Balakrishnan
Jianxin Bi
Harold Soh
FaML
28
2
0
22 Sep 2022
Causal Conceptions of Fairness and their Consequences
H. Nilforoshan
Johann D. Gaebler
Ravi Shroff
Sharad Goel
FaML
142
45
0
12 Jul 2022
Counterfactual Fairness with Partially Known Causal Graph
Aoqi Zuo
Susan Wei
Tongliang Liu
Bo Han
Kun Zhang
Biwei Huang
OOD
FaML
29
19
0
27 May 2022
Marrying Fairness and Explainability in Supervised Learning
Przemyslaw A. Grabowicz
Nicholas Perello
Aarshee Mishra
FaML
51
43
0
06 Apr 2022
Attainability and Optimality: The Equalized Odds Fairness Revisited
Zeyu Tang
Kun Zhang
FaML
21
11
0
24 Feb 2022
Stochastic Causal Programming for Bounding Treatment Effects
Kirtan Padh
Jakob Zeitler
David S. Watson
Matt J. Kusner
Ricardo M. A. Silva
Niki Kilbertus
CML
34
26
0
22 Feb 2022
Evaluation Methods and Measures for Causal Learning Algorithms
Lu Cheng
Ruocheng Guo
Raha Moraffah
Paras Sheth
K. S. Candan
Huan Liu
CML
ELM
29
51
0
07 Feb 2022
Causal Explanations and XAI
Sander Beckers
CML
XAI
28
35
0
31 Jan 2022
A Causal Approach for Unfair Edge Prioritization and Discrimination Removal
Pavan Ravishankar
Pranshu Malviya
Balaraman Ravindran
33
1
0
29 Nov 2021
Explaining Algorithmic Fairness Through Fairness-Aware Causal Path Decomposition
Weishen Pan
Sen Cui
Jiang Bian
Changshui Zhang
Fei Wang
CML
FaML
27
33
0
11 Aug 2021
Fairness via Representation Neutralization
Mengnan Du
Subhabrata Mukherjee
Guanchu Wang
Ruixiang Tang
Ahmed Hassan Awadallah
Xia Hu
30
78
0
23 Jun 2021
Algorithmic Recourse in Partially and Fully Confounded Settings Through Bounding Counterfactual Effects
Julius von Kügelgen
N. Agarwal
Jakob Zeitler
Afsaneh Mastouri
Bernhard Schölkopf
CML
17
2
0
22 Jun 2021
Personalized Counterfactual Fairness in Recommendation
Yunqi Li
Hanxiong Chen
Shuyuan Xu
Yingqiang Ge
Yongfeng Zhang
FaML
OffRL
29
142
0
20 May 2021
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
Outcome-Explorer: A Causality Guided Interactive Visual Interface for Interpretable Algorithmic Decision Making
Md. Naimul Hoque
Klaus Mueller
CML
59
30
0
03 Jan 2021
Achieving User-Side Fairness in Contextual Bandits
Wen Huang
Kevin Labille
Xintao Wu
Dongwon Lee
Neil T. Heffernan
FaML
87
18
0
22 Oct 2020
Generative causal explanations of black-box classifiers
Matthew R. O’Shaughnessy
Gregory H. Canal
Marissa Connor
Mark A. Davenport
Christopher Rozell
CML
35
73
0
24 Jun 2020
Causal Interpretability for Machine Learning -- Problems, Methods and Evaluation
Raha Moraffah
Mansooreh Karami
Ruocheng Guo
A. Raglin
Huan Liu
CML
ELM
XAI
32
213
0
09 Mar 2020
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