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Fair Inference On Outcomes
v1v2v3v4 (latest)

Fair Inference On Outcomes

29 May 2017
Razieh Nabi
I. Shpitser
    FaML
ArXiv (abs)PDFHTML

Papers citing "Fair Inference On Outcomes"

50 / 124 papers shown
Title
Learning to be Fair: A Consequentialist Approach to Equitable
  Decision-Making
Learning to be Fair: A Consequentialist Approach to Equitable Decision-Making
Alex Chohlas-Wood
Madison Coots
Henry Zhu
Emma Brunskill
Sharad Goel
FaML
84
25
0
18 Sep 2021
FADE: FAir Double Ensemble Learning for Observable and Counterfactual
  Outcomes
FADE: FAir Double Ensemble Learning for Observable and Counterfactual Outcomes
Alan Mishler
Edward H. Kennedy
FaML
135
23
0
01 Sep 2021
Transport-based Counterfactual Models
Transport-based Counterfactual Models
Lucas de Lara
Alberto González Sanz
Nicholas M. Asher
Laurent Risser
Jean-Michel Loubes
52
31
0
30 Aug 2021
Explaining Algorithmic Fairness Through Fairness-Aware Causal Path
  Decomposition
Explaining Algorithmic Fairness Through Fairness-Aware Causal Path Decomposition
Weishen Pan
Sen Cui
Jiang Bian
Changshui Zhang
Fei Wang
CMLFaML
122
35
0
11 Aug 2021
Fairness Through Counterfactual Utilities
Fairness Through Counterfactual Utilities
Jack Blandin
Ian A. Kash
FaML
76
2
0
11 Aug 2021
Trustworthy AI: A Computational Perspective
Trustworthy AI: A Computational Perspective
Haochen Liu
Yiqi Wang
Wenqi Fan
Xiaorui Liu
Yaxin Li
Shaili Jain
Yunhao Liu
Anil K. Jain
Jiliang Tang
FaML
192
212
0
12 Jul 2021
FairCanary: Rapid Continuous Explainable Fairness
FairCanary: Rapid Continuous Explainable Fairness
Avijit Ghosh
Aalok Shanbhag
Christo Wilson
107
22
0
13 Jun 2021
When Fair Ranking Meets Uncertain Inference
When Fair Ranking Meets Uncertain Inference
Avijit Ghosh
Ritam Dutt
Christo Wilson
114
46
0
05 May 2021
Explaining Black-Box Algorithms Using Probabilistic Contrastive
  Counterfactuals
Explaining Black-Box Algorithms Using Probabilistic Contrastive Counterfactuals
Sainyam Galhotra
Romila Pradhan
Babak Salimi
CML
105
110
0
22 Mar 2021
Fairness On The Ground: Applying Algorithmic Fairness Approaches to
  Production Systems
Fairness On The Ground: Applying Algorithmic Fairness Approaches to Production Systems
Chloé Bakalar
Renata Barreto
Stevie Bergman
Miranda Bogen
Bobbie Chern
...
J. Simons
Jonathan Tannen
Edmund Tong
Kate Vredenburgh
Jiejing Zhao
FaML
123
28
0
10 Mar 2021
Removing biased data to improve fairness and accuracy
Removing biased data to improve fairness and accuracy
Sahil Verma
Michael Ernst
René Just
FaML
123
25
0
05 Feb 2021
Agent Incentives: A Causal Perspective
Agent Incentives: A Causal Perspective
Tom Everitt
Ryan Carey
Eric D. Langlois
Pedro A. Ortega
Shane Legg
CML
67
56
0
02 Feb 2021
Through the Data Management Lens: Experimental Analysis and Evaluation
  of Fair Classification
Through the Data Management Lens: Experimental Analysis and Evaluation of Fair Classification
Maliha Tashfia Islam
Anna Fariha
A. Meliou
Babak Salimi
FaML
95
26
0
18 Jan 2021
Socially Responsible AI Algorithms: Issues, Purposes, and Challenges
Socially Responsible AI Algorithms: Issues, Purposes, and Challenges
Lu Cheng
Kush R. Varshney
Huan Liu
FaML
170
154
0
01 Jan 2021
Fairness in Machine Learning
Fairness in Machine Learning
L. Oneto
Silvia Chiappa
FaML
324
500
0
31 Dec 2020
FairBatch: Batch Selection for Model Fairness
FairBatch: Batch Selection for Model Fairness
Yuji Roh
Kangwook Lee
Steven Euijong Whang
Changho Suh
VLM
99
133
0
03 Dec 2020
Survey on Causal-based Machine Learning Fairness Notions
Survey on Causal-based Machine Learning Fairness Notions
K. Makhlouf
Sami Zhioua
C. Palamidessi
FaML
151
85
0
19 Oct 2020
Causal Multi-Level Fairness
Causal Multi-Level Fairness
Vishwali Mhasawade
R. Chunara
62
27
0
14 Oct 2020
On the Fairness of Causal Algorithmic Recourse
On the Fairness of Causal Algorithmic Recourse
Julius von Kügelgen
Amir-Hossein Karimi
Umang Bhatt
Isabel Valera
Adrian Weller
Bernhard Schölkopf
FaML
168
87
0
13 Oct 2020
A survey of algorithmic recourse: definitions, formulations, solutions,
  and prospects
A survey of algorithmic recourse: definitions, formulations, solutions, and prospects
Amir-Hossein Karimi
Gilles Barthe
Bernhard Schölkopf
Isabel Valera
FaML
70
172
0
08 Oct 2020
Metrics and methods for a systematic comparison of fairness-aware
  machine learning algorithms
Metrics and methods for a systematic comparison of fairness-aware machine learning algorithms
Gareth Jones
James M. Hickey
Pietro G. Di Stefano
C. Dhanjal
Laura C. Stoddart
V. Vasileiou
FaML
60
21
0
08 Oct 2020
Fairness in Machine Learning: A Survey
Fairness in Machine Learning: A Survey
Simon Caton
C. Haas
FaML
116
654
0
04 Oct 2020
A Causal Lens for Peeking into Black Box Predictive Models: Predictive
  Model Interpretation via Causal Attribution
A Causal Lens for Peeking into Black Box Predictive Models: Predictive Model Interpretation via Causal Attribution
A. Khademi
Vasant Honavar
CML
39
9
0
01 Aug 2020
Algorithmic Fairness in Education
Algorithmic Fairness in Education
René F. Kizilcec
Hansol Lee
FaML
111
126
0
10 Jul 2020
Decolonial AI: Decolonial Theory as Sociotechnical Foresight in
  Artificial Intelligence
Decolonial AI: Decolonial Theory as Sociotechnical Foresight in Artificial Intelligence
Shakir Mohamed
Marie-Therese Png
William S. Isaac
111
417
0
08 Jul 2020
Causal intersectionality for fair ranking
Causal intersectionality for fair ranking
Ke Yang
Joshua R. Loftus
Julia Stoyanovich
71
41
0
15 Jun 2020
What's Sex Got To Do With Fair Machine Learning?
What's Sex Got To Do With Fair Machine Learning?
Lily Hu
Issa Kohler-Hausmann
FaML
70
82
0
02 Jun 2020
Review of Mathematical frameworks for Fairness in Machine Learning
Review of Mathematical frameworks for Fairness in Machine Learning
E. del Barrio
Paula Gordaliza
Jean-Michel Loubes
FaMLFedML
69
40
0
26 May 2020
Contrastive Examples for Addressing the Tyranny of the Majority
Contrastive Examples for Addressing the Tyranny of the Majority
V. Sharmanska
Lisa Anne Hendricks
Trevor Darrell
Novi Quadrianto
72
29
0
14 Apr 2020
Abstracting Fairness: Oracles, Metrics, and Interpretability
Abstracting Fairness: Oracles, Metrics, and Interpretability
Cynthia Dwork
Christina Ilvento
G. Rothblum
Pragya Sur
FaML
79
8
0
04 Apr 2020
Fairness by Explicability and Adversarial SHAP Learning
Fairness by Explicability and Adversarial SHAP Learning
James M. Hickey
Pietro G. Di Stefano
V. Vasileiou
FAttFedML
125
19
0
11 Mar 2020
Counterfactual fairness: removing direct effects through regularization
Counterfactual fairness: removing direct effects through regularization
Pietro G. Di Stefano
James M. Hickey
V. Vasileiou
FaML
128
19
0
25 Feb 2020
FR-Train: A Mutual Information-Based Approach to Fair and Robust
  Training
FR-Train: A Mutual Information-Based Approach to Fair and Robust Training
Yuji Roh
Kangwook Lee
Steven Euijong Whang
Changho Suh
85
79
0
24 Feb 2020
Algorithmic Fairness
Algorithmic Fairness
Dana Pessach
E. Shmueli
FaML
102
395
0
21 Jan 2020
Algorithmic Fairness from a Non-ideal Perspective
Algorithmic Fairness from a Non-ideal Perspective
S. Fazelpour
Zachary Chase Lipton
FaML
66
103
0
08 Jan 2020
Perfectly Parallel Fairness Certification of Neural Networks
Perfectly Parallel Fairness Certification of Neural Networks
Caterina Urban
M. Christakis
Valentin Wüstholz
Fuyuan Zhang
105
72
0
05 Dec 2019
Fair Data Adaptation with Quantile Preservation
Fair Data Adaptation with Quantile Preservation
Drago Plečko
N. Meinshausen
69
30
0
15 Nov 2019
Fairness Violations and Mitigation under Covariate Shift
Fairness Violations and Mitigation under Covariate Shift
Harvineet Singh
Rina Singh
Vishwali Mhasawade
R. Chunara
OOD
79
15
0
02 Nov 2019
PC-Fairness: A Unified Framework for Measuring Causality-based Fairness
PC-Fairness: A Unified Framework for Measuring Causality-based Fairness
Yongkai Wu
Lu Zhang
Xintao Wu
Hanghang Tong
FaML
125
118
0
20 Oct 2019
Conditional Learning of Fair Representations
Conditional Learning of Fair Representations
Han Zhao
Amanda Coston
T. Adel
Geoffrey J. Gordon
FaML
87
109
0
16 Oct 2019
Optimal Training of Fair Predictive Models
Optimal Training of Fair Predictive Models
Razieh Nabi
Daniel Malinsky
I. Shpitser
60
14
0
09 Oct 2019
Alleviating Privacy Attacks via Causal Learning
Alleviating Privacy Attacks via Causal Learning
Shruti Tople
Amit Sharma
A. Nori
MIACVOOD
98
32
0
27 Sep 2019
Causal Modeling for Fairness in Dynamical Systems
Causal Modeling for Fairness in Dynamical Systems
Elliot Creager
David Madras
T. Pitassi
R. Zemel
85
67
0
18 Sep 2019
Learning Fair Rule Lists
Learning Fair Rule Lists
Ulrich Aïvodji
Julien Ferry
Sébastien Gambs
Marie-José Huguet
Mohamed Siala
FaML
64
11
0
09 Sep 2019
A Survey on Bias and Fairness in Machine Learning
A Survey on Bias and Fairness in Machine Learning
Ninareh Mehrabi
Fred Morstatter
N. Saxena
Kristina Lerman
Aram Galstyan
SyDaFaML
605
4,425
0
23 Aug 2019
Data Management for Causal Algorithmic Fairness
Data Management for Causal Algorithmic Fairness
Babak Salimi
B. Howe
Dan Suciu
CMLFaML
41
23
0
20 Aug 2019
Counterfactual Reasoning for Fair Clinical Risk Prediction
Counterfactual Reasoning for Fair Clinical Risk Prediction
Stephen Pfohl
Tony Duan
D. Ding
N. Shah
OODCML
71
58
0
14 Jul 2019
The Sensitivity of Counterfactual Fairness to Unmeasured Confounding
The Sensitivity of Counterfactual Fairness to Unmeasured Confounding
Niki Kilbertus
Philip J. Ball
Matt J. Kusner
Adrian Weller
Ricardo M. A. Silva
93
58
0
01 Jul 2019
Fairness criteria through the lens of directed acyclic graphical models
Fairness criteria through the lens of directed acyclic graphical models
Benjamin R. Baer
Daniel E. Gilbert
M. Wells
FaML
72
6
0
26 Jun 2019
Fairness in Algorithmic Decision Making: An Excursion Through the Lens
  of Causality
Fairness in Algorithmic Decision Making: An Excursion Through the Lens of Causality
A. Khademi
Sanghack Lee
David Foley
Vasant Honavar
FaML
76
96
0
27 Mar 2019
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