All Stories

  1. Dynamic Fairness-aware Recommendation Through Multi-agent Social Choice
  2. Social Choice for Heterogeneous Fairness in Recommendation
  3. Conducting Recommender Systems User Studies Using POPROX
  4. Recommend Me? Designing Fairness Metrics with Providers
  5. 6th Workshop on Fairness in User Modeling, Adaptation, and Personalization (FairUMAP 2023)
  6. The Many Faces of Fairness: Exploring the Institutional Logics of Multistakeholder Microlending Recommendation
  7. FAccTRec 2022: The 5th Workshop on Responsible Recommendation
  8. Recommender Systems and Algorithmic Hate
  9. 5th Workshop on Fairness in User Modeling, Adaptation, and Personalization (FairUMAP 2022)
  10. Multi-agent Social Choice for Dynamic Fairness-aware Recommendation
  11. A Graph-Based Approach for Mitigating Multi-Sided Exposure Bias in Recommender Systems
  12. librec-auto: A Tool for Recommender Systems Experimentation
  13. SimuRec: Workshop on Synthetic Data and Simulation Methods for Recommender Systems Research
  14. User-centered Evaluation of Popularity Bias in Recommender Systems
  15. What do users think about fairness in recommender systems?
  16. Flatter Is Better
  17. Feedback Loop and Bias Amplification in Recommender Systems
  18. Fairness-aware Recommendation with librec-auto
  19. The Connection Between Popularity Bias, Calibration, and Fairness in Recommendation
  20. Calibration in Collaborative Filtering Recommender Systems
  21. Opportunistic Multi-aspect Fairness through Personalized Re-ranking
  22. FairMatch: A Graph-based Approach for Improving Aggregate Diversity in Recommender Systems
  23. Personalized fairness-aware re-ranking for microlending
  24. An Algorithm for Allocating Sponsored Recommendations and Content: Unifying Programmatic Advertising and Recommender Systems
  25. Fairness and Discrimination in Retrieval and Recommendation
  26. Localized Fairness in Recommender Systems
  27. FairUMAP 2019 Chairs' Welcome Overview