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Individual Fairness in Pipelines

Individual Fairness in Pipelines

12 April 2020
Cynthia Dwork
Christina Ilvento
Meena Jagadeesan
    FaML
ArXivPDFHTML

Papers citing "Individual Fairness in Pipelines"

12 / 12 papers shown
Title
When Are Two Lists Better than One?: Benefits and Harms in Joint
  Decision-making
When Are Two Lists Better than One?: Benefits and Harms in Joint Decision-making
Kate Donahue
Sreenivas Gollapudi
Kostas Kollias
37
3
0
22 Aug 2023
Sequential Strategic Screening
Sequential Strategic Screening
Lee Cohen
Saeed Sharifi-Malvajerd
Kevin Stangl
A. Vakilian
Juba Ziani
28
4
0
31 Jan 2023
Learning Antidote Data to Individual Unfairness
Learning Antidote Data to Individual Unfairness
Peizhao Li
Ethan Xia
Hongfu Liu
FedML
FaML
24
9
0
29 Nov 2022
Don't Throw it Away! The Utility of Unlabeled Data in Fair Decision
  Making
Don't Throw it Away! The Utility of Unlabeled Data in Fair Decision Making
Miriam Rateike
Ayan Majumdar
Olga Mineeva
Krishna P. Gummadi
Isabel Valera
OffRL
37
11
0
10 May 2022
Cascaded Debiasing: Studying the Cumulative Effect of Multiple
  Fairness-Enhancing Interventions
Cascaded Debiasing: Studying the Cumulative Effect of Multiple Fairness-Enhancing Interventions
Bhavya Ghai
Mihir A. Mishra
Klaus Mueller
32
7
0
08 Feb 2022
Fair Sequential Selection Using Supervised Learning Models
Fair Sequential Selection Using Supervised Learning Models
Mohammad Mahdi Khalili
Xueru Zhang
Mahed Abroshan
FaML
36
20
0
26 Oct 2021
Fairness Through Counterfactual Utilities
Fairness Through Counterfactual Utilities
Jack Blandin
Ian A. Kash
FaML
38
2
0
11 Aug 2021
Multiaccurate Proxies for Downstream Fairness
Multiaccurate Proxies for Downstream Fairness
Emily Diana
Wesley Gill
Michael Kearns
K. Kenthapadi
Aaron Roth
Saeed Sharifi-Malvajerdi
35
21
0
09 Jul 2021
Learning Certified Individually Fair Representations
Learning Certified Individually Fair Representations
Anian Ruoss
Mislav Balunović
Marc Fischer
Martin Vechev
FaML
15
92
0
24 Feb 2020
PrivacyNet: Semi-Adversarial Networks for Multi-attribute Face Privacy
PrivacyNet: Semi-Adversarial Networks for Multi-attribute Face Privacy
Vahid Mirjalili
S. Raschka
Arun Ross
PICV
CVBM
22
101
0
02 Jan 2020
Learning Adversarially Fair and Transferable Representations
Learning Adversarially Fair and Transferable Representations
David Madras
Elliot Creager
T. Pitassi
R. Zemel
FaML
236
676
0
17 Feb 2018
Fair prediction with disparate impact: A study of bias in recidivism
  prediction instruments
Fair prediction with disparate impact: A study of bias in recidivism prediction instruments
Alexandra Chouldechova
FaML
207
2,092
0
24 Oct 2016
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