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Recent work on machine learning has begun to consider issues of fairness.
An optimal deterministic algorithm for online b-matching
Bala Kalyanasundaram and Kirk R Pruhs. 2000 · 2000
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The targeting of advertising
Ganesh Iyer, David Soberman, and J Miguel Villas-Boas. 2005 · 2005
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Internet advertising and the generalized second-price auction: Selling billions of dollars worth of keywords
Benjamin Edelman, Michael Ostrovsky, and Michael Schwarz. 2007 · 2007
Earlier work this paper cites.
Discrimination-aware data mining. In Proceedings of the 14th ACM SIGKDD international conference on Knowledge discovery and data mining
Dino Pedreshi, Salvatore Ruggieri, and Franco Turini. 2008 · 2008
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Republic. com 2.0
Cass R Sunstein. 2009 · 2009
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Valuepick: Towards a value-oriented dual-goal recommender system. In 2010 IEEE International Conference on Data Mining Workshops
Leman Akoglu and Christos Faloutsos. 2010 · 2010
Earlier work this paper cites.
Discrimination aware decision tree learning. In Data Mining (ICDM), 2010 IEEE 10th International Conference on
Faisal Kamiran, Toon Calders, and Mykola Pechenizkiy. 2010 · 2010
Earlier work this paper cites.
Collaboration recommendation on academic social networks. In International Conference on Conceptual Modeling
Giseli Rabello Lopes, Mirella M Moro, Leandro Krug Wives, and José Palazzo Moreira De Oliveira. 2010 · 2010
Earlier work this paper cites.
RECON: a reciprocal recommender for online dating. In Proceedings of the fourth ACM conference on Recommender systems
Luiz Pizzato, Tomek Rej, Thomas Chung, Irena Koprinska, and Judy Kay. 2010 · 2010
Cited alongside, same era.
Advances in collaborative filtering
Y. Koren and R. Bell. 2011 · 2011
Cited alongside, same era.
The filter bubble: How the new personalized web is changing what we read and how we think
Eli Pariser. 2011 · 2011
Cited alongside, same era.
Rank and Relevance in Novelty and Diversity Metrics for Recommender Systems. In Proceedings of the Fifth ACM Conference on Recommender Systems
Saúl Vargas and Pablo Castells. 2011 · 2011
Cited alongside, same era.
Improving aggregate recommendation diversity using ranking-based techniques
G. Adomavicius and Y.O. Kwon. 2012 · 2012
Cited alongside, same era.
Internet Advertising: An Interplay among Advertisers, Online Publishers, Ad Exchanges and Web Users
Shuai Yuan, Ahmad Zainal Abidin, Marc Sloan, and Jun Wang. 2012 · 2012
Later among the works it cites.
Bias in algorithmic filtering and personalization
Engin Bozdag. 2013 · 2013
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Learning fair representations. In Proceedings of the 30th International Conference on Machine Learning (ICML-13)
Rich Zemel, Yu Wu, Kevin Swersky, Toni Pitassi, and Cynthia Dwork. 2013 · 2013
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Fairness-Aware Loan Recommendation for Microfinance Services. In Proceedings of the 2014 International Conference on Social Computing
Eric L Lee, Jing-Kai Lou, Wei-Ming Chen, Yen-Chi Chen, Shou-De Lin, Yen-Sheng Chiang, and Kuan-Ta Chen. 2014 · 2014
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Towards Multi-Stakeholder Utility Evaluation of Recommender Systems. In Proceedings of the International Workshop on Surprise, Opposition, and Obstruction in Adaptive and Personalized Systems (SOAP 2016)
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Fairness through awareness. In Proceedings of the 3rd Innovations in Theoretical Computer Science Conference
Cynthia Dwork, Moritz Hardt, Toniann Pitassi, Omer Reingold, and Richard Zemel. 2012 · 2012
Cited alongside, same era.
Fairness-Aware Classifier with Prejudice Remover Regularizer
Toshihiro Kamishima, Shotaro Akaho, Hideki Asoh, and Jun Sakuma. 2012 · 2012
Cited alongside, same era.
Cross-domain collaboration recommendation. In Proceedings of the 18th ACM SIGKDD international conference on Knowledge discovery and data mining
Jie Tang, Sen Wu, Jimeng Sun, and Hang Su. 2012 · 2012
Cited alongside, same era.
Robin Burke, Himan Abdollahpouri, Bamshad Mobasher, and Trinadh Gupta. 2016 · 2016
Later among the works it cites.
Matchmakers: The New Economics of Multisided Platforms
David S. Evans and Richard Schmalensee. 2016 · 2016
Later among the works it cites.
Recommender Systems as Multistakeholder Environments
Himan Abdollahpouri, Robin Burke, and Bamshad Mobasher. 2017 · 2017
Closest in time.
Anti-discrimination learning: a causal modeling-based framework
Lu Zhang and Xintao Wu. 2017 · 2017
Closest in time.