Get our free extension to see links to code for papers anywhere online!

Chrome logo  Add to Chrome

Firefox logo Add to Firefox

Who Pays? Personalization, Bossiness and the Cost of Fairness


Sep 08, 2022
Paresha Farastu, Nicholas Mattei, Robin Burke


   Access Paper or Ask Questions

  • Share via Twitter
  • Share via Facebook
  • Share via LinkedIn
  • Share via Whatsapp
  • Share via Messenger
  • Share via Email

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


   Access Paper or Ask Questions

  • Share via Twitter
  • Share via Facebook
  • Share via LinkedIn
  • Share via Whatsapp
  • Share via Messenger
  • Share via Email

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 

   Access Paper or Ask Questions

  • Share via Twitter
  • Share via Facebook
  • Share via LinkedIn
  • Share via Whatsapp
  • Share via Messenger
  • Share via Email

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 

   Access Paper or Ask Questions

  • Share via Twitter
  • Share via Facebook
  • Share via LinkedIn
  • Share via Whatsapp
  • Share via Messenger
  • Share via Email

Fairness and Transparency in Recommendation: The Users' Perspective


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


   Access Paper or Ask Questions

  • Share via Twitter
  • Share via Facebook
  • Share via LinkedIn
  • Share via Whatsapp
  • Share via Messenger
  • Share via Email

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 

   Access Paper or Ask Questions

  • Share via Twitter
  • Share via Facebook
  • Share via LinkedIn
  • Share via Whatsapp
  • Share via Messenger
  • Share via Email

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) 

   Access Paper or Ask Questions

  • Share via Twitter
  • Share via Facebook
  • Share via LinkedIn
  • Share via Whatsapp
  • Share via Messenger
  • Share via Email

"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


   Access Paper or Ask Questions

  • Share via Twitter
  • Share via Facebook
  • Share via LinkedIn
  • Share via Whatsapp
  • Share via Messenger
  • Share via Email

Opportunistic Multi-aspect Fairness through Personalized Re-ranking


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


   Access Paper or Ask Questions

  • Share via Twitter
  • Share via Facebook
  • Share via LinkedIn
  • Share via Whatsapp
  • Share via Messenger
  • Share via Email

Exploring User Opinions of Fairness in Recommender Systems


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


   Access Paper or Ask Questions

  • Share via Twitter
  • Share via Facebook
  • Share via LinkedIn
  • Share via Whatsapp
  • Share via Messenger
  • Share via Email
1
2
>>