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As a key application of artificial intelligence, recommender systems are among the most pervasive computer aided systems to help users find potential items of interests.
Probabilistic matrix factorization. In NIPS
Andriy Mnih and Ruslan R Salakhutdinov. 2008 · 2008
Earlier work this paper cites.
Discrimination-aware data mining. In SIGKDD
Dino Pedreshi, Salvatore Ruggieri, and Franco Turini. 2008 · 2008
Earlier work this paper cites.
Music recommendation and discovery in the long tail
Òscar Celma Herrada et al · 2009
Earlier work this paper cites.
Matrix factorization techniques for recommender systems
Yehuda Koren, Robert Bell, and Chris Volinsky. 2009 · 2009
Earlier work this paper cites.
BPR: Bayesian personalized ranking from implicit feedback. In UAI
Steffen Rendle, Christoph Freudenthaler, Zeno Gantner, and Lars Schmidt-Thieme. 2009 · 2009
Earlier work this paper cites.
Fairness through awareness. In ITCS
Cynthia Dwork, Moritz Hardt, Toniann Pitassi, Omer Reingold, and Richard Zemel. 2012 · 2012
Earlier work this paper cites.
Private traits and attributes are predictable from digital records of human behavior
Michal Kosinski, David Stillwell, and Thore Graepel. 2013 · 2013
Earlier work this paper cites.
Discrimination in online ad delivery
Latanya Sweeney. 2013 · 2013
Earlier work this paper cites.
Learning fair representations. In ICML
Rich Zemel, Yu Wu, Kevin Swersky, Toni Pitassi, and Cynthia Dwork. 2013 · 2013
Earlier work this paper cites.
Generative adversarial nets. In NIPS
Ian Goodfellow, Jean Pouget-Abadie, Mehdi Mirza, Bing Xu, David Warde-Farley, Sherjil Ozair, Aaron Courville, and Yoshua Bengio. 2014 · 2014
Earlier work this paper cites.
The movielens datasets: History and context
F Maxwell Harper and Joseph A Konstan. 2015 · 2015
Earlier work this paper cites.
Deep neural networks for youtube recommendations. In RecSys
Paul Covington, Jay Adams, and Emre Sargin. 2016 · 2016
Earlier work this paper cites.
Censoring representations with an adversary. In ICLR
Harrison Edwards and Amos Storkey. 2016 · 2016
Cited alongside, same era.
Deep learning
Ian Goodfellow, Yoshua Bengio, Aaron Courville, and Yoshua Bengio. 2016 · 2016
Cited alongside, same era.
Equality of opportunity in supervised learning. In NIPS
Moritz Hardt, Eric Price, and Nati Srebro. 2016 · 2016
Cited alongside, same era.
Data decisions and theoretical implications when adversarially learning fair representations. In FAT/ML
Alex Beutel, Jilin Chen, Zhe Zhao, and Ed H Chi. 2017 · 2017
Cited alongside, same era.
Counterfactual fairness. In NIPS
Matt J Kusner, Joshua Loftus, Chris Russell, and Ricardo Silva. 2017 · 2017
Cited alongside, same era.
Beyond the words: Predicting user personality from heterogeneous information. In WSDM
Honghao Wei, Fuzheng Zhang, Nicholas Jing Yuan, Chuan Cao, Hao Fu, Xing Xie, Yong Rui, and Wei-Ying Ma. 2017 · 2017
User Fairness in Recommender Systems. In WWW
Jurek Leonhardt, Avishek Anand, and Megha Khosla. 2018 · 2018
Later among the works it cites.
Learning adversarially fair and transferable representations. In ICML
David Madras, Elliot Creager, Toniann Pitassi, and Richard Zemel. 2018 · 2018
Later among the works it cites.
Fairness-aware tensor-based recommendation. In CIKM
Ziwei Zhu, Xia Hu, and James Caverlee. 2018 · 2018
Later among the works it cites.
Fairness in recommendation ranking through pairwise comparisons. In SIGKDD
Alex Beutel, Jilin Chen, Tulsee Doshi, Hai Qian, Li Wei, Yi Wu, Lukasz Heldt, Zhe Zhao, Lichan Hong, Ed H Chi, et al · 2019
Later among the works it cites.
Compositional fairness constraints for graph embeddings. In ICML
Avishek Joey Bose and William Hamilton. 2019 · 2019
Later among the works it cites.
Fairness-aware ranking in search & recommendation systems with application to LinkedIn talent search. In SIGKDD
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Cited alongside, same era.
Modeling the evolution of users’ preferences and social links in social networking services
Le Wu, Yong Ge, Qi Liu, Enhong Chen, Richang Hong, Junping Du, and Meng Wang. 2017 · 2017
Cited alongside, same era.
Controllable invariance through adversarial feature learning. In NIPS
Qizhe Xie, Zihang Dai, Yulun Du, Eduard Hovy, and Graham Neubig. 2017 · 2017
Cited alongside, same era.
Beyond parity: Fairness objectives for collaborative filtering. In NIPS
Sirui Yao and Bert Huang. 2017 · 2017
Cited alongside, same era.
A note on using the F-measure for evaluating record linkage algorithms
David Hand and Peter Christen. 2018 · 2018
Cited alongside, same era.
Algorithmic bias? An empirical study into apparent gender-based discrimination in the display of STEM career ads
Anja Lambrecht and Catherine E Tucker. 2018 · 2018
Cited alongside, same era.
All the cool kids, how do they fit in?: Popularity and demographic biases in recommender evaluation and effectiveness. In FAT
Michael D Ekstrand, Mucun Tian, Ion Madrazo Azpiazu, Jennifer D Ekstrand, Oghenemaro Anuyah, David McNeill, and Maria Soledad Pera. 2018a
Cited in the paper.
Sahin Cem Geyik, Stuart Ambler, and Krishnaram Kenthapadi. 2019 · 2019
Later among the works it cites.
Fairness in algorithmic decision making: An excursion through the lens of causality. In WWW
Aria Khademi, Sanghack Lee, David Foley, and Vasant Honavar. 2019 · 2019
Later among the works it cites.
Neural Graph Collaborative Filtering. In SIGIR
Xiang Wang, Xiangnan He, Meng Wang, Fuli Feng, and Tat-Seng Chua. 2019 · 2019
Later among the works it cites.
A neural influence diffusion model for social recommendation. In SIGIR
Le Wu, Peijie Sun, Yanjie Fu, Richang Hong, Xiting Wang, and Meng Wang. 2019 · 2019
Later among the works it cites.
Revisiting Graph based Collaborative Filtering: A Linear Residual Graph Convolutional Network Approach. In AAAI
Chen Lei, Wu Le, Hong Richang, Zhang Kun, and Wang Meng. 2020 · 2020
Later among the works it cites.
Joint item recommendation and attribute inference: An adaptive graph convolutional network approach. In SIGIR
Le Wu, Yonghui Yang, Kun Zhang, Richang Hong, Yanjie Fu, and Meng Wang. 2020 · 2020
Later among the works it cites.