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Avoiding Discrimination through Causal Reasoning
v1v2 (latest)

Avoiding Discrimination through Causal Reasoning

8 June 2017
Niki Kilbertus
Mateo Rojas-Carulla
Giambattista Parascandolo
Moritz Hardt
Dominik Janzing
Bernhard Schölkopf
    FaMLCML
ArXiv (abs)PDFHTML

Papers citing "Avoiding Discrimination through Causal Reasoning"

50 / 312 papers shown
Title
Causal Feature Selection for Algorithmic Fairness
Causal Feature Selection for Algorithmic Fairness
Sainyam Galhotra
Karthikeyan Shanmugam
P. Sattigeri
Kush R. Varshney
FaML
89
43
0
10 Jun 2020
Achieving Equalized Odds by Resampling Sensitive Attributes
Achieving Equalized Odds by Resampling Sensitive Attributes
Yaniv Romano
Stephen Bates
Emmanuel J. Candès
FaML
39
51
0
08 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
AI Research Considerations for Human Existential Safety (ARCHES)
AI Research Considerations for Human Existential Safety (ARCHES)
Andrew Critch
David M. Krueger
112
53
0
30 May 2020
Distributional Random Forests: Heterogeneity Adjustment and Multivariate
  Distributional Regression
Distributional Random Forests: Heterogeneity Adjustment and Multivariate Distributional Regression
Domagoj Cevid
Loris Michel
Jeffrey Näf
N. Meinshausen
Peter Buhlmann
96
43
0
29 May 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
Gender Slopes: Counterfactual Fairness for Computer Vision Models by
  Attribute Manipulation
Gender Slopes: Counterfactual Fairness for Computer Vision Models by Attribute Manipulation
Jungseock Joo
Kimmo Karkkainen
69
48
0
21 May 2020
Principal Fairness for Human and Algorithmic Decision-Making
Principal Fairness for Human and Algorithmic Decision-Making
Kosuke Imai
Zhichao Jiang
FaML
85
31
0
21 May 2020
The Impact of Presentation Style on Human-In-The-Loop Detection of
  Algorithmic Bias
The Impact of Presentation Style on Human-In-The-Loop Detection of Algorithmic Bias
Po-Ming Law
Sana Malik
F. Du
Moumita Sinha
45
6
0
26 Apr 2020
REVISE: A Tool for Measuring and Mitigating Bias in Visual Datasets
REVISE: A Tool for Measuring and Mitigating Bias in Visual Datasets
Angelina Wang
Alexander Liu
Ryan Zhang
Anat Kleiman
Leslie Kim
Dora Zhao
Iroha Shirai
Arvind Narayanan
Olga Russakovsky
89
191
0
16 Apr 2020
Individual Fairness in Pipelines
Individual Fairness in Pipelines
Cynthia Dwork
Christina Ilvento
Meena Jagadeesan
FaML
58
40
0
12 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
Demographic Bias: A Challenge for Fingervein Recognition Systems?
Demographic Bias: A Challenge for Fingervein Recognition Systems?
P. Drozdowski
B. Prommegger
Georg Wimmer
R. Schraml
Christian Rathgeb
A. Uhl
C. Busch
78
10
0
03 Apr 2020
Fair inference on error-prone outcomes
Fair inference on error-prone outcomes
L. Boeschoten
E. V. Kesteren
A. Bagheri
Daniel L. Oberski
21
2
0
17 Mar 2020
Balancing Competing Objectives with Noisy Data: Score-Based Classifiers
  for Welfare-Aware Machine Learning
Balancing Competing Objectives with Noisy Data: Score-Based Classifiers for Welfare-Aware Machine Learning
Esther Rolf
Max Simchowitz
Sarah Dean
Lydia T. Liu
Daniel Björkegren
Moritz Hardt
J. Blumenstock
43
23
0
15 Mar 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
123
19
0
11 Mar 2020
Slice Tuner: A Selective Data Acquisition Framework for Accurate and
  Fair Machine Learning Models
Slice Tuner: A Selective Data Acquisition Framework for Accurate and Fair Machine Learning Models
Ki Hyun Tae
Steven Euijong Whang
85
41
0
10 Mar 2020
Causal Interpretability for Machine Learning -- Problems, Methods and
  Evaluation
Causal Interpretability for Machine Learning -- Problems, Methods and Evaluation
Raha Moraffah
Mansooreh Karami
Ruocheng Guo
A. Raglin
Huan Liu
CMLELMXAI
98
221
0
09 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
Learning Individually Fair Classifier with Path-Specific Causal-Effect
  Constraint
Learning Individually Fair Classifier with Path-Specific Causal-Effect Constraint
Yoichi Chikahara
Shinsaku Sakaue
Akinori Fujino
Hisashi Kashima
FaML
23
0
0
17 Feb 2020
Convex Fairness Constrained Model Using Causal Effect Estimators
Convex Fairness Constrained Model Using Causal Effect Estimators
Hikaru Ogura
Akiko Takeda
24
2
0
16 Feb 2020
Algorithmic Recourse: from Counterfactual Explanations to Interventions
Algorithmic Recourse: from Counterfactual Explanations to Interventions
Amir-Hossein Karimi
Bernhard Schölkopf
Isabel Valera
CML
100
346
0
14 Feb 2020
HypoML: Visual Analysis for Hypothesis-based Evaluation of Machine
  Learning Models
HypoML: Visual Analysis for Hypothesis-based Evaluation of Machine Learning Models
Qianwen Wang
W. Alexander
J. Pegg
Huamin Qu
Min Chen
VLM
63
10
0
12 Feb 2020
To Split or Not to Split: The Impact of Disparate Treatment in
  Classification
To Split or Not to Split: The Impact of Disparate Treatment in Classification
Hao Wang
Hsiang Hsu
Mario Díaz
Flavio du Pin Calmon
115
23
0
12 Feb 2020
Oblivious Data for Fairness with Kernels
Oblivious Data for Fairness with Kernels
Steffen Grunewalder
A. Khaleghi
55
6
0
07 Feb 2020
Algorithmic Fairness
Algorithmic Fairness
Dana Pessach
E. Shmueli
FaML
102
395
0
21 Jan 2020
Secure and Robust Machine Learning for Healthcare: A Survey
Secure and Robust Machine Learning for Healthcare: A Survey
A. Qayyum
Junaid Qadir
Muhammad Bilal
Ala I. Al-Fuqaha
AAMLOOD
98
392
0
21 Jan 2020
Incentives for Responsiveness, Instrumental Control and Impact
Incentives for Responsiveness, Instrumental Control and Impact
Ryan Carey
Eric D. Langlois
Chris van Merwijk
Shane Legg
Tom Everitt
CML
79
13
0
20 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
Learning from Discriminatory Training Data
Learning from Discriminatory Training Data
Przemyslaw A. Grabowicz
Nicholas Perello
Kenta Takatsu
FaML
87
1
0
17 Dec 2019
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
Towards Fairness in Visual Recognition: Effective Strategies for Bias
  Mitigation
Towards Fairness in Visual Recognition: Effective Strategies for Bias Mitigation
Zeyu Wang
Klint Qinami
Yannis Karakozis
Kyle Genova
P. Nair
Kenji Hata
Olga Russakovsky
104
366
0
26 Nov 2019
Causality for Machine Learning
Causality for Machine Learning
Bernhard Schölkopf
CMLAI4CELRM
117
465
0
24 Nov 2019
Feature Noise Induces Loss Discrepancy Across Groups
Feature Noise Induces Loss Discrepancy Across Groups
Fereshte Khani
Percy Liang
FaML
59
6
0
22 Nov 2019
Fair Data Adaptation with Quantile Preservation
Fair Data Adaptation with Quantile Preservation
Drago Plečko
N. Meinshausen
69
30
0
15 Nov 2019
Fairness through Equality of Effort
Fairness through Equality of Effort
Wen Huang
Yongkai Wu
Lu Zhang
Xintao Wu
FaML
57
33
0
11 Nov 2019
Reducing Sentiment Bias in Language Models via Counterfactual Evaluation
Reducing Sentiment Bias in Language Models via Counterfactual Evaluation
Po-Sen Huang
Huan Zhang
Ray Jiang
Robert Stanforth
Johannes Welbl
Jack W. Rae
Vishal Maini
Dani Yogatama
Pushmeet Kohli
106
217
0
08 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
Feature relevance quantification in explainable AI: A causal problem
Feature relevance quantification in explainable AI: A causal problem
Dominik Janzing
Lenon Minorics
Patrick Blobaum
FAttCML
106
286
0
29 Oct 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
Is There a Trade-Off Between Fairness and Accuracy? A Perspective Using
  Mismatched Hypothesis Testing
Is There a Trade-Off Between Fairness and Accuracy? A Perspective Using Mismatched Hypothesis Testing
Sanghamitra Dutta
Dennis L. Wei
Hazar Yueksel
Pin-Yu Chen
Sijia Liu
Kush R. Varshney
FaML
67
11
0
17 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
Asymmetric Shapley values: incorporating causal knowledge into
  model-agnostic explainability
Asymmetric Shapley values: incorporating causal knowledge into model-agnostic explainability
Christopher Frye
C. Rowat
Ilya Feige
105
183
0
14 Oct 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
Advancing subgroup fairness via sleeping experts
Advancing subgroup fairness via sleeping experts
Avrim Blum
Thodoris Lykouris
FedML
68
37
0
18 Sep 2019
Learning Fair Rule Lists
Learning Fair Rule Lists
Ulrich Aïvodji
Julien Ferry
Sébastien Gambs
Marie-José Huguet
Mohamed Siala
FaML
61
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
603
4,424
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
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