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DeepFair: Deep Learning for Improving Fairness in Recommender Systems

DeepFair: Deep Learning for Improving Fairness in Recommender Systems

9 June 2020
Jesús Bobadilla
R. Lara-Cabrera
Ángel González-Prieto
Fernando Ortega
    FaML
ArXivPDFHTML

Papers citing "DeepFair: Deep Learning for Improving Fairness in Recommender Systems"

4 / 4 papers shown
Title
TFROM: A Two-sided Fairness-Aware Recommendation Model for Both
  Customers and Providers
TFROM: A Two-sided Fairness-Aware Recommendation Model for Both Customers and Providers
Yao Wu
Jian Cao
Guandong Xu
Yudong Tan
FaML
22
84
0
19 Apr 2021
Deep Learning feature selection to unhide demographic recommender
  systems factors
Deep Learning feature selection to unhide demographic recommender systems factors
Jesús Bobadilla
Ángel González-Prieto
Fernando Ortega
R. Lara-Cabrera
31
21
0
17 Jun 2020
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
323
4,212
0
23 Aug 2019
Improving fairness in machine learning systems: What do industry
  practitioners need?
Improving fairness in machine learning systems: What do industry practitioners need?
Kenneth Holstein
Jennifer Wortman Vaughan
Hal Daumé
Miroslav Dudík
Hanna M. Wallach
FaML
HAI
192
742
0
13 Dec 2018
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