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AI Fairness 360: An Extensible Toolkit for Detecting, Understanding, and
  Mitigating Unwanted Algorithmic Bias

AI Fairness 360: An Extensible Toolkit for Detecting, Understanding, and Mitigating Unwanted Algorithmic Bias

3 October 2018
Rachel K. E. Bellamy
Kuntal Dey
Michael Hind
Samuel C. Hoffman
Stephanie Houde
Kalapriya Kannan
P. Lohia
Jacquelyn Martino
S. Mehta
Aleksandra Mojsilović
Seema Nagar
K. Ramamurthy
John T. Richards
Diptikalyan Saha
P. Sattigeri
Moninder Singh
Kush R. Varshney
Yunfeng Zhang
    FaML
    SyDa
ArXivPDFHTML

Papers citing "AI Fairness 360: An Extensible Toolkit for Detecting, Understanding, and Mitigating Unwanted Algorithmic Bias"

20 / 370 papers shown
Title
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
SyDa
FaML
326
4,223
0
23 Aug 2019
Paired-Consistency: An Example-Based Model-Agnostic Approach to Fairness
  Regularization in Machine Learning
Paired-Consistency: An Example-Based Model-Agnostic Approach to Fairness Regularization in Machine Learning
Yair Horesh
N. Haas
Elhanan Mishraky
Yehezkel S. Resheff
Shir Meir Lador
FaML
14
7
0
07 Aug 2019
The What-If Tool: Interactive Probing of Machine Learning Models
The What-If Tool: Interactive Probing of Machine Learning Models
James Wexler
Mahima Pushkarna
Tolga Bolukbasi
Martin Wattenberg
F. Viégas
Jimbo Wilson
VLM
43
484
0
09 Jul 2019
Training individually fair ML models with Sensitive Subspace Robustness
Training individually fair ML models with Sensitive Subspace Robustness
Mikhail Yurochkin
Amanda Bower
Yuekai Sun
FaML
OOD
19
119
0
28 Jun 2019
FlipTest: Fairness Testing via Optimal Transport
FlipTest: Fairness Testing via Optimal Transport
Emily Black
Samuel Yeom
Matt Fredrikson
10
93
0
21 Jun 2019
Adversarial training approach for local data debiasing
Adversarial training approach for local data debiasing
Ulrich Aïvodji
F. Bidet
Sébastien Gambs
Rosin Claude Ngueveu
Alain Tapp
11
7
0
19 Jun 2019
Balanced Ranking with Diversity Constraints
Balanced Ranking with Diversity Constraints
Ke Yang
Vasilis Gkatzelis
Julia Stoyanovich
14
69
0
04 Jun 2019
Optimized Score Transformation for Consistent Fair Classification
Optimized Score Transformation for Consistent Fair Classification
Dennis L. Wei
K. Ramamurthy
Flavio du Pin Calmon
18
15
0
31 May 2019
Fairness and Missing Values
Fairness and Missing Values
Fernando Martínez-Plumed
Cesar Ferri
David Nieves
José Hernández-Orallo
16
28
0
29 May 2019
Software Engineering for Fairness: A Case Study with Hyperparameter
  Optimization
Software Engineering for Fairness: A Case Study with Hyperparameter Optimization
Joymallya Chakraborty
Tianpei Xia
F. M. Fahid
Tim Menzies
FaML
22
40
0
14 May 2019
Assuring the Machine Learning Lifecycle: Desiderata, Methods, and
  Challenges
Assuring the Machine Learning Lifecycle: Desiderata, Methods, and Challenges
Rob Ashmore
R. Calinescu
Colin Paterson
AI4TS
24
116
0
10 May 2019
Estimating Kullback-Leibler Divergence Using Kernel Machines
Estimating Kullback-Leibler Divergence Using Kernel Machines
Kartik Ahuja
15
11
0
02 May 2019
Data Cleaning for Accurate, Fair, and Robust Models: A Big Data - AI
  Integration Approach
Data Cleaning for Accurate, Fair, and Robust Models: A Big Data - AI Integration Approach
Ki Hyun Tae
Yuji Roh
Young H. Oh
Hyunsub Kim
Steven Euijong Whang
11
71
0
22 Apr 2019
Fairness for Robust Log Loss Classification
Fairness for Robust Log Loss Classification
Ashkan Rezaei
Rizal Fathony
Omid Memarrast
Brian D. Ziebart
FaML
23
8
0
10 Mar 2019
Stable and Fair Classification
Stable and Fair Classification
Lingxiao Huang
Nisheeth K. Vishnoi
FaML
24
71
0
21 Feb 2019
Fairwashing: the risk of rationalization
Fairwashing: the risk of rationalization
Ulrich Aïvodji
Hiromi Arai
O. Fortineau
Sébastien Gambs
Satoshi Hara
Alain Tapp
FaML
19
142
0
28 Jan 2019
Faking Fairness via Stealthily Biased Sampling
Faking Fairness via Stealthily Biased Sampling
Kazuto Fukuchi
Satoshi Hara
Takanori Maehara
MLAU
11
16
0
24 Jan 2019
Bias Mitigation Post-processing for Individual and Group Fairness
Bias Mitigation Post-processing for Individual and Group Fairness
P. Lohia
K. Ramamurthy
M. Bhide
Diptikalyan Saha
Kush R. Varshney
Ruchir Puri
FaML
11
155
0
14 Dec 2018
AI Fairness for People with Disabilities: Point of View
AI Fairness for People with Disabilities: Point of View
Shari Trewin
9
74
0
26 Nov 2018
Aequitas: A Bias and Fairness Audit Toolkit
Aequitas: A Bias and Fairness Audit Toolkit
Pedro Saleiro
Benedict Kuester
Loren Hinkson
J. London
Abby Stevens
Ari Anisfeld
Kit T. Rodolfa
Rayid Ghani
29
319
0
14 Nov 2018
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