ResearchTrend.AI
  • Papers
  • Communities
  • Events
  • Blog
  • Pricing
Papers
Communities
Social Events
Terms and Conditions
Pricing
Parameter LabParameter LabTwitterGitHubLinkedInBlueskyYoutube

© 2025 ResearchTrend.AI, All rights reserved.

  1. Home
  2. Papers
  3. 2010.05887
  4. Cited By
Fairness Perception from a Network-Centric Perspective

Fairness Perception from a Network-Centric Perspective

7 October 2020
Farzan Masrour
P. Tan
A. Esfahanian
    FaML
ArXivPDFHTML

Papers citing "Fairness Perception from a Network-Centric Perspective"

12 / 12 papers shown
Title
PeerReview4All: Fair and Accurate Reviewer Assignment in Peer Review
PeerReview4All: Fair and Accurate Reviewer Assignment in Peer Review
Ivan Stelmakh
Nihar B. Shah
Aarti Singh
39
97
0
16 Jun 2018
Learning Adversarially Fair and Transferable Representations
Learning Adversarially Fair and Transferable Representations
David Madras
Elliot Creager
T. Pitassi
R. Zemel
FaML
379
681
0
17 Feb 2018
Preventing Fairness Gerrymandering: Auditing and Learning for Subgroup
  Fairness
Preventing Fairness Gerrymandering: Auditing and Learning for Subgroup Fairness
Michael Kearns
Seth Neel
Aaron Roth
Zhiwei Steven Wu
FaML
197
778
0
14 Nov 2017
Fairness in Criminal Justice Risk Assessments: The State of the Art
Fairness in Criminal Justice Risk Assessments: The State of the Art
R. Berk
Hoda Heidari
S. Jabbari
Michael Kearns
Aaron Roth
51
995
0
27 Mar 2017
Counterfactual Fairness
Counterfactual Fairness
Matt J. Kusner
Joshua R. Loftus
Chris Russell
Ricardo M. A. Silva
FaML
215
1,580
0
20 Mar 2017
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
300
2,114
0
24 Oct 2016
Equality of Opportunity in Supervised Learning
Equality of Opportunity in Supervised Learning
Moritz Hardt
Eric Price
Nathan Srebro
FaML
228
4,312
0
07 Oct 2016
Fairness in Learning: Classic and Contextual Bandits
Fairness in Learning: Classic and Contextual Bandits
Matthew Joseph
Michael Kearns
Jamie Morgenstern
Aaron Roth
FaML
59
475
0
23 May 2016
Censoring Representations with an Adversary
Censoring Representations with an Adversary
Harrison Edwards
Amos Storkey
AAML
FaML
66
505
0
18 Nov 2015
The Variational Fair Autoencoder
The Variational Fair Autoencoder
Christos Louizos
Kevin Swersky
Yujia Li
Max Welling
R. Zemel
DRL
223
633
0
03 Nov 2015
Certifying and removing disparate impact
Certifying and removing disparate impact
Michael Feldman
Sorelle A. Friedler
John Moeller
C. Scheidegger
Suresh Venkatasubramanian
FaML
201
1,986
0
11 Dec 2014
Automated Experiments on Ad Privacy Settings: A Tale of Opacity, Choice,
  and Discrimination
Automated Experiments on Ad Privacy Settings: A Tale of Opacity, Choice, and Discrimination
Amit Datta
Michael Carl Tschantz
Anupam Datta
72
734
0
27 Aug 2014
1