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Unbiased Cascade Bandits: Mitigating Exposure Bias in Online Learning to Rank Recommendation


Aug 07, 2021
Masoud Mansoury, Himan Abdollahpouri, Bamshad Mobasher, Mykola Pechenizkiy, Robin Burke, Milad Sabouri


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A Graph-based Approach for Mitigating Multi-sided Exposure Bias in Recommender Systems


Jul 07, 2021
Masoud Mansoury, Himan Abdollahpouri, Mykola Pechenizkiy, Bamshad Mobasher, Robin Burke

* arXiv admin note: substantial text overlap with arXiv:2005.01148 

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Fairness and Discrimination in Information Access Systems


May 12, 2021
Michael D. Ekstrand, Anubrata Das, Robin Burke, Fernando Diaz

* Currently under review. Please send comments to the authors 

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Fairness and Transparency in Recommendation: The Users' Perspective


Mar 16, 2021
Nasim Sonboli, Jessie J. Smith, Florencia Cabral Berenfus, Robin Burke, Casey Fiesler


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User-centered Evaluation of Popularity Bias in Recommender Systems


Mar 10, 2021
Himan Abdollahpouri, Masoud Mansoury, Robin Burke, Bamshad Mobasher, Edward Malthouse

* Proceedings of the 29th ACM Conference on User Modeling, Adaptation and Personalization (UMAP '21), June 21--25, 2021, Utrecht, Netherlands. arXiv admin note: text overlap with arXiv:2007.12230 

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User Factor Adaptation for User Embedding via Multitask Learning


Feb 22, 2021
Xiaolei Huang, Michael J. Paul, Robin Burke, Franck Dernoncourt, Mark Dredze

* Accepted in the Second Workshop on Domain Adaptation for Natural Language Processing (Adapted-NLP) 

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"And the Winner Is...": Dynamic Lotteries for Multi-group Fairness-Aware Recommendation


Sep 05, 2020
Nasim Sonboli, Robin Burke, Nicholas Mattei, Farzad Eskandanian, Tian Gao


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Opportunistic Multi-aspect Fairness through Personalized Re-ranking


May 21, 2020
Nasim Sonboli, Farzad Eskandanian, Robin Burke, Weiwen Liu, Bamshad Mobasher


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Exploring User Opinions of Fairness in Recommender Systems


Apr 17, 2020
Jessie Smith, Nasim Sonboli, Casey Fiesler, Robin Burke


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Developing a Recommendation Benchmark for MLPerf Training and Inference


Apr 14, 2020
Carole-Jean Wu, Robin Burke, Ed H. Chi, Joseph Konstan, Julian McAuley, Yves Raimond, Hao Zhang


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Crank up the volume: preference bias amplification in collaborative recommendation


Sep 13, 2019
Kun Lin, Nasim Sonboli, Bamshad Mobasher, Robin Burke

* Presented at the RMSE workshop held in conjunction with the 13th ACM Conference on Recommender Systems (RecSys), 2019, in Copenhagen, Denmark 

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Bias Disparity in Collaborative Recommendation: Algorithmic Evaluation and Comparison


Aug 02, 2019
Masoud Mansoury, Bamshad Mobasher, Robin Burke, Mykola Pechenizkiy

* Workshop on Recommendation in Multi-Stakeholder Environments (RMSE) at ACM RecSys 2019, Copenhagen, Denmark 

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Flatter is better: Percentile Transformations for Recommender Systems


Jul 10, 2019
Masoud Mansoury, Robin Burke, Bamshad Mobasher


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Beyond Personalization: Research Directions in Multistakeholder Recommendation


May 01, 2019
Himan Abdollahpouri, Gediminas Adomavicius, Robin Burke, Ido Guy, Dietmar Jannach, Toshihiro Kamishima, Jan Krasnodebski, Luiz Pizzato

* 66 pages 

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Value-Aware Item Weighting for Long-Tail Recommendation


Feb 15, 2018
Himan Abdollahpouri, Robin Burke, Bamshad Mobasher


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